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We analyze economics PhDs’ collaborations in peer-reviewed journals from 1990 to 2014 and investigate such collaborations’ quality in relation to each co-author’s research quality, field and specialization. We find that a greater overlap between co-authors’ previous research fields is significantly related to a greater publication success of co-authors’ joint work and this is robust to alternative specifications. Co-authors that engage in a distant collaboration are significantly more likely to have a large research overlap, but this significance is lost when co-authors’ social networks are accounted for. High quality collaboration is more likely to emerge as a result of an interaction between specialists and generalists with overlapping fields of expertise. Regarding interactions across subfields of economics (interdisciplinarity), it is more likely conducted by co- authors who already have interdisciplinary portfolios, than by co-authors who are specialized or starred in different subfields.
New business opportunities appeared using the potential of the Internet and related digital technologies, like the Internet of Things, services computing, artificial intelligence, cloud, edge, and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber-physical systems. Companies are transforming their strategy and product base, as well as their culture, processes and information systems to adopt digital transformation or to approach for digital leadership. Digitalization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. Digitalization has a substantial impact for architecting the open and complex world of highly distributed digital servcies and products, as part of a new digital enterprise architecture, which structure and direct service-dominant digital products and services. The present research paper investigates mechanisms for supporting the evolution of digital enterprise architectures with user-friendly methods and instruments of interaction, visualization, and intelligent decision management during the exploration of multiple and interconnected perspectives by an architecture management cockpit.
Artificial Intelligence-based Assistants AIAs are spreading quickly both in homes and offices. They already have left their original habitats of "intelligent speakers" providing easy access to music collections. The initiated a multitude of new devices and are already populating devices such as TV sets. Characteristic for the intelligent digital assistants is the formation of platforms around their core functionality. Thus, AIS capabilities of the assistants are used to offer new services and create new interfaces for business processes. There are positive network effects between the assistants and the services as well as within the services. Therefore, many companies see the need to get involved in the field of digital assistants but lack a framework to align their initiatives with their corporate strategies. In order to lay the foundation for a comprehensive method, we are therefore investigating intelligent digital assistants. Based on this analysis, we are developing a framework of strategic opportunities and challenges.
The general conclusion of climate change studies is the necessity of eliminating net CO2 emissions in general and from the electric power systems in particular by 2050. The share of renewable energy is increasing worldwide, but due to the intermittent nature of wind and solar power, a lack of system flexibility is already hampering the further integration of renewable energy in some countries. In this study, we analyze if and how combinations of carbon pricing and power-to-gas (PtG) generation in the form of green power-to-hydrogen followed by methanation (which we refer to as PtG throughout) using captured CO2 emissions can provide transitions to deep decarbonization of energy systems. To this end, we focus on the economics of deep decarbonization of the European electricity system with the help of an energy system model. In different scenario analyses, we find that a CO2 price of 160 €/t (by 2050) is on its own not sufficient to decarbonize the electricity sector, but that a CO2 price path of 125 (by 2040) up to 160 €/t (by 2050), combined with PtG technologies, can lead to an economically feasible decarbonization of the European electricity system by 2050. These results are robust to higher than anticipated PtG costs.
Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power train. However, there are opportunities to increase energy-efficiency and safety by adapting the individual driving behaviour in the given driving situation. In this paper, an improved rule match algorithm is introduced, which is used in the expert system of a human-centred driving system. The goal of the driving system is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. The improved rule match algorithm checks the incoming information against the driving rules to recognise any breakings of a driving rule. The needed information is obtained by monitoring the driver, the current driving situation as well as the car, using in-vehicle sensors and serial-bus systems. On the basis of the detected broken driving rules, the expert system will create individual recommendations in terms of energy-efficiency and safety, which will allow eliminating bad driving habits, while considering the driver needs.
Detecting the adherence of driving rules in an energy-efficient, safe and adaptive driving system
(2016)
An adaptive and rule-based driving system is being developed that tries to improve the driving behavior in terms of the energy-efficiency and safety by giving recommendations. Therefore, the driving system has to monitor the adherence of driving rules by matching the rules to the driving behavior. However, existing rule matching algorithms are not sufficient, as the data within a driving system is changing frequently. In this paper a rule matching algorithm is introduced that is able to handle frequently changing data within the context of the driving system. 15 journeys were used to evaluate the performance of the rule matching algorithms. The results showed that the introduced algorithm outperforms existing algorithms in the context of the driving system. Thus, the introduced algorithm is suited for matching frequently changing data against rules with a higher performance, why it will be used in the driving system for the detection of broken energy-efficiency of safety-relevant driving rules.
Palladium-doped silica materials with SiCH3 groups were fabricated by sol-gel method under various calcination atmospheres and membranes were made thereof by coating process. The results showed that air atmosphere can lead to the partial oxidation of metallic Pd0 to PdO while N2 and H2 atmospheres can effectively prevent metallic Pd0 from being oxidized. H2 atmosphere is proved to be a more prominent way to slow down the decomposition of organic SiCH3 group than N2 and air atmospheres. The surface area, micropore volume and porosity of palladium-doped silica membrane material calcined in H2 atmosphere are much higher than those calcined in N2 atmosphere. Compared with N2 atmosphere, the palladium-doped silica membranes calcined in H2 atmosphere showed higher H2 permeability and H2/CO2 selectivity before and after the steam exposure. The apparent activation energy of H2 permeation through the palladium-doped silica membrane calcined under H2 atmosphere (2.51 ± 0.05 kJ/mol) was slightly lower than that calcined under N2 atmosphere (2.84 ± 0.04 kJ/mol). Calcination atmosphere plays some role in membrane performance, which has greater influence on the permeance than on the gas permselectivity. Calcination under H2 atmosphere is well conducive to improve the gas permeance and H2 permselectivity of palladium-doped silica membrane.
Introducing continuous experimentation in large software-intensive product and service organisations
(2017)
Software development in highly dynamic environments imposes high risks to development organizations. One such risk is that the developed software may be of only little or no value to customers, wasting the invested development efforts.Continuous experiment ation, as an experiment-driven development approach, may reduce such development risks by iteratively testing product and service assumptions that are critical to the success of the software. Although several experiment-driven development approaches are available, there is little guidance available on how to introduce continuous experimentation into an organization. This article presents a multiple-case study that aims at better understanding the process of introducing continuous experimentation into an organization with an already established development process. The results from the study show that companies are open to adopting such an approach and learning throughout the introduction process. Several benefits were obtained, such as reduced development efforts, deeper customer insights, and better support for development decisions. Challenges included complex stakeholder structures, difficulties in defining success criteria, and building experimen- tation skills. Our findings indicate that organizational factors may limit the benefits of experimentation. Moreover, introducing continuous experimentation requires fundamental changes in how companies operate, and a systematic introduction process can increase the chances of a successful start.
Powder coating of engineered wood panels such as medium density fibreboards (MDF) is gaining industrial interest due to ecological and economic advantages of powder coating technology. For transferring powder coating technology to temperature-sensitive substrates like MDF, a thorough understanding of the melting, flowing and curing behaviour of the used low-bake resins is required. In the present study, thermo-analysis in combination with iso-conversional kinetic data analysis as well as rheometry is applied to characterise the properties of an epoxy-based powder coating. Neat resin and cured powder coating films are examined in order to define an ideal production window within which the resin is preferably applied and processed to yield satisfactory surface performance on the one hand and without exposing the carrier MDF too high a temperature load on the other hand to prevent the panel from deteriorating in mechanical strength. In order to produce powder coated films of high surface gloss – a feature that has not yet successfully been realized on MDF with powder coatings – a new curing technology, in-mould surface finishing, has been applied.
Using predictive maintenance, more efficient processes can be implemented, leading to fewer maintenance costs and increased availability. The development of a predictive maintenance solution currently requires high efforts in time and capacity as well as often interdisciplinary cooperation. This paper presents a standardized model to describe a predictive maintenance use case. The description model is used to collect, present, and document the required information for the implementation of predictive maintenance use cases by and for different stakeholders. Based on this model, predictive maintenance solutions can be introduced more efficiently. The method is validated across departments in the automotive sector.
Railway operators are being challenged by increasing complexity and safeguarding the availability of passenger rolling stock, bringing maintenance and especially emerging technologies into the focus. This paper presents a model for selection and implementation of Industry 4.0 technologies in rolling stock maintenance. The model consists of different stages and considers the main components of rolling stock, the related appropriate maintenance strategies and Industry 4.0 technologies considering the maturity level of the railway operators. Relevant criteria and main prerequisites of the technologies were identified. The model proposes relevant activities and was validated by industry experts.
With the digital transformation, companies will experience a change that focuses on shaping the organization into an agile organizational form. In today's competitive and fast-moving business environment, it is necessary to react quickly to changing market conditions. Agility represents a promising option for overcoming these challenges. The path to an agile organization represents a development process that requires consideration of countless levels of the enterprise. This paper examines the impact of digital transformation on agile working practices and the benefits that can be achieved through technology. To enable a solution for today's so-called VUCA (Volatility, Uncertainty, Complexity und Ambiguity) world, agile ways of working can be applied project management requires adaptation. In the qualitative study, expert interviews were conducted and analyzed using the grounded theory method. As a result, a model can be presented that shows the influencing factors and potentials of agile management in the context of the digital transformation of medium-sized companies.
Nowadays CHP units are discussed for the production of electricity on demand rather than for generation of heat providing electricity as a by-product. By this means, CHP units are capable of satisfying a higher share of the electricity demand on-site and in this new role, CHP units are able to reduce the load on the power grid and to compensate for high fluctuations of solar and wind power.
Evidently, a novel control strategy for CHP units is required in order to shift the operation oriented at the heat demand to an operation led by the electricity demand. Nevertheless, the heat generated by the CHP unit needs to be utilized completely in any case, for maintaining energy as well as economic efficiency. Such a strategy has been developed at Reutlingen University, and it will be presented in the paper. Part of the strategy is an intelligent management for the thermal energy storage (TES) ensuring that the storage is at low level in terms of its heat content just before an electricity demand is calling the CHP unit into operation. Moreover, a proper forecast of both, heat and electricity demand, is incorporated and the requirements of the CHP unit in terms of maintenance and lifetime are considered by limiting the number of starts and stops per unit time and by maintaining a certain minimum length of the operation intervals.
All aspects of this novel control strategy are revealed in the paper, which has been implemented on a controller for further testing at two sites in the field. Results from these tests are given as well as results from a simulation model, which is able to evaluate the performance of the control strategy for an entire year.
Adoption of artificial intelligence (AI) has risen sharply in recent years but many firms are not successful in realising the expected benefits or even terminate projects before completion. While there are a number of previous studies that highlight challenges in AI projects, critical factors that lead to project failure are mostly unknown. The aim of this study is therefore to identify distinct factors that are critical for failure of AI projects. To address this, interviews with experts in the field of AI from different industries are conducted and the results are analyzed using qualitative analysis methods. The results show that both, organizational and technological issues can cause project failure. Our study contributes to knowledge by reviewing previously identified challenges in terms of their criticality for project failure based on new empirical data, as well as, by identifying previously unknown factors.
Automatic content creation system for augmented reality maintenance applications for legacy machines
(2024)
Augmented reality (AR) applications have great potential to assist maintenance workers in their operations. However, creating AR solutions is time-consuming and laborious, which limits its widespread adoption in the industry. It therefore often happens that even with the latest generation machines, instead of an AR solution, the user only receives an electronic manual for the equipment operation and maintenance. This is commonplace with legacy machines. For this reason, solutions are required that simplify the creation of such AR solutions. This paper presents an approach using an electronic manual as a basis to create fast and cost-effective AR solutions for maintenance. As part of the approach, an application was developed to automatically identify and subdivide the chapters of electronic manuals via the bookmarks in the table of contents. The contents are then automatically uploaded to a central server and indexed with a suitable marker to make the data retrievable. The prepared content can then be accessed for creating context-related AR instructions via the marker. The application is characterized by the fact that no developers or experts are required to prepare the information. In addition to complying with common design criteria, the clear presentation of the contents and the intuitive use of the system offer added value for the performance of maintenance tasks. Together, these two elements form a novel way to retrofit legacy machines with AR maintenance instructions. The practical validation of the system took place in a factory environment. For this purpose, the content was created for a filter change on a CNC milling machine. The results show that inexperienced users can extract appropriate content with the software application. Furthermore, it is shown that maintenance workers, can access the content with an AR application developed for the Microsoft HoloLens 2 and complete simple tasks provided in the manufacturer's electronic manual.
In recent years, machine learning algorithms have made a huge development in performance and applicability in industry and especially maintenance. Their application enables predictive maintenance and thus offers efficiency increases. However, a successful implementation of such solutions still requires high effort in data preparation to obtain the right information, interdisciplinarity in teams as well as a good communication to employees. Here, small and medium sized enterprises (SME) often lack in experience, competence and capacity. This paper presents a systematic and practice-oriented method for an implementation of machine learning solutions for predictive maintenance in SME, which has already been validated.
The isothermal curing of melamine resin is investigated by in-line infrared spectroscopy at different temperatures. The infrared spectra are decomposed into time courses of characteristic spectral patterns using Multivariate Curve Resolution (MCR). It was found that depending on the applied curing temperature, melamine films with different spectral fingerprints and correspondingly different chemical network structures are formed. The network structures of fully cured resin films are specific for the applied curing temperatures used and cannot simply be compensated by changes in the curing time. For industrial curing processes, this means that cure temperature is the main system determining factor at constant M:F ratio. However, different MF resin networks can be specifically obtained from one and the same melamine resin by suitable selection of the curing time and temperatures profiles to design resin functionality. The spectral fingerprints after short curing time as well as after long curing time reflect the fundamental differences in the thermoset networks that can be obtained with industrial short-cycle and multi-daylight presses.
The incudo-malleal joint (IMJ) in the human middle ear is a true diarthrodial joint and it has been known that the flexibility of this joint does not contribute to better middle-ear sound transmission. Previous studies have proposed that a gliding motion between the malleus and the incus at this joint prevents the transmission of large displacements of the malleus to the incus and stapes and thus contributes to the protection of the inner ear as an immediate response against large static pressure changes. However, dynamic behavior of this joint under static pressure changes has not been fully revealed. In this study, effects of the flexibility of the IMJ on middle-ear sound transmission under static pressure difference between the middle-ear cavity and the environment were investigated. Experiments were performed in human cadaveric temporal bones with static pressures in the range of +/- 2 kPa being applied to the ear canal (relative to middle-ear cavity). Vibrational motions of the umbo and the stapes footplate center in response to acoustic stimulation (0.2-8 kHz) were measured using a 3D-Laser Doppler vibrometer for (1) the natural IMJ and (2) the IMJ with experimentally-reduced flexibility. With the natural condition of the IMJ, vibrations of the umbo and the stapes footplate center under static pressure loads were attenuated at low frequencies below the middle-ear resonance frequency as observed in previous studies. After the flexibility of the IMJ was reduced, additional attenuations of vibrational motion were observed for the umbo under positive static pressures in the ear canal (EC) and the stapes footplate center under both positive and negative static EC pressures. The additional attenuation of vibration reached 4~7 dB for the umbo under positive static EC pressures and the stapes footplate center under negative EC pressures, and 7~11 dB for the stapes footplate center under positive EC pressures. The results of this study indicate an adaptive mechanism of the flexible IMJ in the human middle ear to changes of static EC pressure by reducing the attenuation of the middle-ear sound transmission. Such results are expected to be used for diagnosis of the IMJ stiffening and to be applied to design of middle-ear prostheses.
The Circular Economy aims to reintroduce the value of products back into the economic cycle at the same value chain level. While the activities of the Circular Economy are already well-defined, there exists a gap in how returned products are treated by the industry. This study aims to examine how a process should be designed to handle returned products in the context of the Circular Economy. To achieve this, a machine learning-based algorithm is used to classify data and extract relevant information throughout the product life cycle. The focus of this research is limited to land transportation systems within the Sharing Economy sector.
Development of an expert system to overpass citizens technological barriers on smart home and living
(2023)
Adopting new technologies can be overwhelming, even for people with experience in the field. For the general public, learning about new implementations, releases, brands, and enhancements can cause them to lose interest. There is a clear need to create point sources and platforms that provide helpful information about the novel and smart technologies, assisting users, technicians, and providers with products and technologies. The purpose of these platforms is twofold, as they can gather and share information on interests common to manufacturers and vendors. This paper presents the ”Finde-Dein-SmartHome” tool. Developed in association with the Smart Home & Living competence center [5] to help users learn about, understand, and purchase available technologies that meet their home automation needs. This tool aims to lower the usability barrier and guide potential customers to clear their doubts about privacy and pricing. Communities can use the information provided by this tool to identify market trends that could eventually lower costs for providers and incentivize access to innovative home technologies and devices supporting long-term care.
In vitro models of human adipose tissue may serve as beneficial alternatives to animal models to study basic biological processes, identify new drug targets, and as soft tissue implants. With this approach, we aimed to evaluate adipose-derived stem cells (ASC) and mature adipocytes (MA) comparatively for the application in the in vitro setup of adipose tissue constructs to imitate native adipose tissue physiology. We used human primary MAs and human ASCs, differentiated for 14 days, and encapsulated them in collagen type I hydrogels to build up a three-dimensional (3D) adipose tissue model. The maintenance of the models was analyzed after seven days based on a viability staining. Further, the expression of the adipocyte specific protein perilipin A and the release of leptin and glycerol were evaluated. Gene transcription profiles of models based on dASCs and MAs were analyzed with regard to native adipose tissue. Compared to MAs, dASCs showed an immature differentiation state. Further, gene transcription of MAs suggests a behavior closer to native tissue in terms of angiogenesis, which supports MAs as preferred cell type. In contrast to native adipose tissue, genes of de novo lipogenesis and tissue remodeling were upregulated in the in vitro attempts.
Background aims: In vitro engineered adipose tissue is in great demand to treat lost or damaged soft tissue or to screen for new drugs, among other applications.However, today most attempts depend on the use of animal-derived sera. To pave the way for the application of adipose tissue-engineered
products in clinical trials or as reliable and robust in vitro test systems, sera should be completely excluded from the production process. In this study, we aimed to develop an in vitro adipose tissue model in the absence of sera and maintain its function long-term.
Methods: Human adipose tissue-derived stem cells were expanded and characterized in a xeno- and serum-free environment. Adipogenic differentiation was induced using a completely defined medium. Developed adipocytes were maintained in a completely defined maturation medium for additional 28 days. In addition to cell-viability and adherence, adipocyte-specific markers such as perilipin A expression of leptin release were evaluated.
Results: The defined differentiation medium enhanced cell adherence and lipid
accumulation at a significant level compared with the corresponding negative control. The defined maturation medium also significantly supported cell adherence and functional adipocyte maturation during the long-term culture period.
Conclusions: The process described here enables functional adipocyte generation and maintenance without the addition fo unknown or unimal-derived constituents, achieving an important milestone in the introduction of adipose tissue engineered products into clinical trials or in vitro screening.
In vitro composed vascularized adipose tissue is and will continue to be in great demand e.g. for the treatment of extensive high-graded burns or the replacement of tissue after tumor removal. Up to date, the lack of adequate culture conditions, mainly a culture medium, decelerates further achievements. In our study, we evaluated the influence of epidermal growth factor (EGF) and hydrocortisone (HC), often supplemented in endothelial cell (EC) specific media, on the co-culture of adipogenic differentiated adipose derived stem cells (ASCs) and microvascular endothelial cells (mvECs). In ASCs, EGF and HC are thought to inhibit adipogenic differentiation and have lipolytic activities. Our results showed that in indirect co-culture for 14 days, adipogenic differentiated ASCs further incorporated lipids and partly gained an univacuolar morphology when kept in media with low levels of EGF and HC. In media with high EGF and HC levels, cells did not incorporate further lipids, on the contrary, cells without lipid droplets appeared. Glycerol release, to measure lipolysis, also increased with elevated amounts of EGF and HC in the culture medium. Adipogenic differentiated ASCs were able to release leptin in all setups. MvECs were functional and expressed the cell specific markers, CD31 and von Willebrand factor (vWF), independent of the EGF and HC content as long as further EC specific factors were present. Taken together, our study demonstrates that adipogenic differentiated ASCs can be successfully co-cultured with mvECs in a culture medium containing low or no amounts of EGF and HC, as long as further endothelial cell and adipocyte specific factors are available.
The development of in vitro adipose tissue constructs is highly desired to cope with the increased demand for substitutes to replace damaged soft tissue after high graded burns, deformities or tumor removal. To achieve clinically relevant dimensions, vascularization of soft tissue constructs becomes inevitable but still poses a challenge. Adipose-derived stem cells (ASCs) represent a promising cell source for the setup of vascularized fatty tissue constructs as they can be differentiated into adipocytes and endothelial cells in vitro and are thereby available in sufficiently high cell numbers.
This review summarizes the currently known characteristics of ASCs and achievements in adipogenic and endothelial differentiation in vitro. Further, the interdependency of adipogenesis and angiogenesis based on the crosstalk of endothelial cells, stem cells and adipocytes is addressed at the molecular level. Finally, achievements and limitations of current co-culture conditions for the construction of vascularized adipose tissue are evaluated.
This paper presents the concept of the system architecture of a flexible cyber-physical factory control system. The system allows the automation of process structures using cyber-physical fractal nodes. These nodes have a functional and independent form and can be clustered to larger structures. This makes it possible to equip the factory with a flexible, freely scalable, modular system. The description of this system architecture and the associated rules and conditions is outlined in the concept.
The maintenance of railway infrastructure remains a challenge. Data acquisition technologies have evolved because of Industry 4.0, expanding the capabilities of predictive maintenance. Despite the advances, the potential of these emerging technologies has not been fully realised. This paper presents a technology selection framework in support of railway infrastructure predictive maintenance, which is based on qualitative methods. It consists of three stages, including the mapping of the infrastructure characteristics with the identified technologies, the evaluation of the most appropriate technologies, and the sourcing thereof. This presents the collective decision support output of the framework.
Functionalised particles are highly requested in materials research, as they can be used as vital components in many advanced applications such as smart materials, functional coatings, drug carrier systems or adsorption materials. In this study, furan-functionalised melamine-formaldehyde (MF) particles were successfully prepared for the first time using an organic sol-gel process. Commercially available 2-Aminomethylfuran (AMF) and 2-Aminomethyl-5-methylfuran (AMMF) were used as modifying agents. In the isolated polymer particles, a melamine (M) to modifying agent ratio of M:AMF mol/mol 2.04:1 and M:AMMF ratio of mol/mol 1.25:1 was used. The obtained particles were isolated in various centrifugation and re-dispersion cycles and analysed using ATR-FT-IR, Raman and solid state 13C NMR spectroscopy, TGA, SEM and DSC measurements. Upon functionalisation the size of the MF particles increased (MF 1.59 µm, 27% CV (coefficient of variation); MF-AMF 2.56 µm, 25% CV; MF-AMMF 2.20 µm, 35% CV). DSC measurements showed that another type of exothermic residual reactivity besides condensation-based curing takes place with the furan-modified particles that is not related to the liberation of volatile compounds. The newly obtained particles are able to undergo Diels-Alder reactions with maleimide groups. The characteristic IR and Raman absorbance bands of the reaction products after the particles were reacted with 4,4′-Diphenylmethanebismaleimide reagent confirm the formation of a Diels-Alder adduct.
The data present in this article affords insides in the characterization of a newly described bi-functional furan-melamine monomer, which is used for the production of monodisperse, furan-functionalized melamine formaldehyde particles. In the related research article Urdl et al., 2019 data interpretations can be found. The furan functionalization of particles is necessary to perform reversible Diels-Alder reactions with maleimide (BMI) crosslinker to form thermoreversible network systems. To understand the reaction conditions of Diels Alder (DA) reaction with a Fu-Mel monomer and a maleimide crosslinker, model DA reaction were performed and evaluated using dynamic FT-IR measurements. During retro Diels-Alder (rDA) reactions of the monomer system, it was found out that some side reaction occurred at elevated temperatures. The data of evaluating the side reaction is described in one part of this manuscript. Additional high resolution SEM images of Fu Mel particles are shown and thermoreversible particle networks with BMI2 are shown. The data of different Fu-Mel particle networks with maleimide crosslinker are presented. Therefore, the used maleimide crosslinker with different spacer lengths were synthesized and the resulting networks were analyzed by ATR-FT-IR, SEM and DSC.
The self-healing effect of melamine-based surfaces, triggered by temperature, was investigated. The temperature triggered reversible healing chemistry, on which the self-healing effect is based, was the Diels-Alder (DA) reaction between furan and malemeide groups. Melamine-furan containing building blocks were connected by multi-functional maleimide crosslinker via a Diels-Alder (DA) reaction to giva a DA adduct. The DA adduct was then reacted with formaldehyde to form a network by conventional condensation reaction of melamine amino groups with formaldehyde. The obtained resin was characterised and used for the impregnation of paper. Impregnated papers and neat resin werde used to perform scratch-healing tests and mechanical analysis of the novel coating system.
The data presented in this article characterize the thermomechanical and microhardness properties of a novel melamine-formaldehyde resin (MF) intended for the use as a self-healing surface coating. The investigated MF resin is able to undergo reversible crosslinking via Diels Alder reactive groups. The microhardness data were obtained from nanoindentation measurements performed on solid resin film samples at different stages of the self-healing cycle. Thermomechanical analysis was performed under dynamic load conditions. The data provide supplemental material to the manuscript published by Urdl et al. 2020 (https://doi.org/10.1016/j.eurpolymj.2020.109601) on the self-healing performance of this resin, where a more thorough discussion on the preparation, the properties of this coating material and its application in impregnated paper-based decorative laminates can be found.
Homogeneous and monodispersed furan functionalised melamine-formaldehyde particles were produced. As a precursor, 2-chloro-1,3,5-triazine-2,4-diamine (Mel) was selectively substituted with 2-aminomethyl furan (Fu) units in a convenient one step reaction. The pure reaction product Fu-Mel, which was used without further purification, was reacted with formaldehyde by conventional sol-gel condensation in aqueous medium to yield chemically homogenous, spherically shaped and monodispersed particles. The particles were analysed using ATR-FT-IR, Raman, 1H and 13C NMR spectroscopy, TGA, SEM and DSC measurements. The reactivity of the furan groups located at the particle surface was studied by performing a thermoreversible Diels-Alder cycloaddition reaction with bis-maleimide coupling agents. The formed networks showed thermoreversible behaviour, which was characterised by dynamic IR and DSC measurements.
Structural and functional thermosetting composite materials are exposed to different kinds of stress which can damage the polymer matrix, thus impairing the intended properties. Therefore, self-healing materials have attracted the attention of many research groups over the last decades in order to provide satisfactory material properties and outstanding product durability. The present article provides a critical overview of promising self-healing strategies for crosslinked thermoset polymers. It is organized in two parts: an overview about the different approaches to self-healing is given in the first part, whereas the second part focuses on the specific chemistries of the main strategies to achieve self-healing through crosslinking. It is attempted to provide a comprehensive discussion of different approaches which are described in the scientific literature. By comparison of the advantages and disadvantages, the authors wish to provide helpful insights on the assessment of the potential to transfer the extensive present knowledge about self-healing materials and methods to surface varnishing thermoset coatings.
Respiratory diseases are leading causes of death and disability in the world. The recent COVID-19 pandemic is also affecting the respiratory system. Detecting and diagnosing respiratory diseases requires both medical professionals and the clinical environment. Most of the techniques used up to date were also invasive or expensive.
Some research groups are developing hardware devices and techniques to make possible a non-invasive or even remote respiratory sound acquisition. These sounds are then processed and analysed for clinical, scientific, or educational purposes.
We present the literature review of non-invasive sound acquisition devices and techniques.
The results are about a huge number of digital tools, like microphones, wearables, or Internet of Thing devices, that can be used in this scope.
Some interesting applications have been found. Some devices make easier the sound acquisition in a clinic environment, but others make possible daily monitoring outside that ambient. We aim to use some of these devices and include the non-invasive recorded respiratory sounds in a Digital Twin system for personalized health.
Context
In a world of high dynamics and uncertainties, it is almost impossible to have a long-term prediction of which products, services, or features will satisfy the needs of the customer. To counter this situation, the conduction of Continuous Improvement or Design Thinking for product discovery are common approaches. A major constraint in conducting product discovery activities is the high effort to discover and validate features and requirements. In addition, companies struggle to integrate product discovery activities into their agile processes and iterations.
Objective
This paper aims at suggests a supportive tool, the “Discovery Effort Worthiness (DEW) Index”, for product owners and agile teams to determine a suitable amount of effort that should be spent on Design Thinking activities. To operationalize DEW, proposals for practitioners are presented that can be used to integrate product discovery into product development and delivery.
Method
A case study was conducted for the development of the DEW index. In addition, we conducted an expert workshop to develop proposals for the integration of product discovery activities into the product development and delivery process.
Results
First, we present the "Discovery Effort Worthiness Index" in form of a formula. Second, we identified requirements that must be fulfilled for systematic integration of product discovery activities into product development and delivery. Third, we derived from the requirements proposals for the integration of product discovery activities with a company's product development and delivery.
Conclusion
The developed "Discovery Effort Worthiness Index" provides a tool for companies and their product owners to determine how much effort they should spend on Design Thinking methods to discover and validate requirements. Integrating product discovery with product development and delivery should ensure that the results of product discovery are incorporated into product development. This aims to systematically analyze product risks to increase the chance of product success.
Coupling electricity and heat sector is one of the most necessary actions for the successful energy transition. Efficient electrification for space heating and domestic hot water generation is needed for buildings, which are not connected to any district heating network, as distributed heating demand momentarily is largely met by fossil fuels. Hence, hybrid energy systems will play a pivotal role for the energy transition in buildings. Heat pumps running on PV-electricity is one of the most widely discussed combination for this purpose. In this paper, a heuristic optimization method for the optimal operation of a heat pump driven by the objective for maximum onsite PV electricity utilization is presented. In this context, the thermal flexibility of the building and a thermal energy storage (TES) for generation of domestic hot water (DHW) are activated in order to shift the operation of the heat pump to times of PV-generation. Yearly simulations for a system consisting of heat pump, PV modules, building with floor heating installation and TES for DHW generation are carried out. Variation parameters for the simulation include room temperature amplitude (0.5, 1, 1.5 and 2 K) based on mean room temperature (21 °C), PV-capacity (4, 6, 8 and 10 kW) and type of heat pump (ground source and air source type). The yearly energy balances show that buildings offer significant thermal storage capacity avoiding an additional, large TES for space heating fulfillment and improving the share of onsite PV electricity utilization. With introduction of a battery, which has been analyzed as well for different sizes (1.9, 4.8, 7.7 and 10.6 kWh), the share of onsite PVelectricity utilization can even be improved. However, thermal flexibility supplemented by the varying room temperature amplitude for a bigger battery does not improve the share of onsite PV-electricity utilization. Nevertheless, even with a battery not more than 50% of the electrical load including operation of the heat pump can be covered by PV-electricity for the specific system under investigation. This is noteworthy on the one hand, since it indicates that a hybrid heating system consisting of heat pump and PV cannot solely cover the heat demand of residential buildings. One the other hand, this emphasizes the necessity to include further renewable sources like wind power, in order to draw the complete picture. This, however, is beyond the scope of this paper, which mainly focuses on introduction and verification of the novel control method with regard to a practical building.
Allyls
(2014)
This chapter addresses the importance and usage of the commercially low volume thermoset plastics group known as allyls. The three significant sub-elements of this group are poly(diallylphthalates), poly(diallylisophthalates), and poly(allyldiglycol carbonate). Chemistry, processing, and properties are also described. Allyl polymers are synthesized by radical polymerizations of allyl monomers that usually do not produce high-molecular-mass macromolecules. Therefore, only a few specific monomers can produce thermosetting materials. Diallyldiglycolcarbonate (CR-39) and diallylphthalates are the most significant examples that have considerably improved our everyday life.
Allyls
(2022)
This chapter addresses the importance and usage of the commercially low-volume thermoset plastics group known as allyls. The three significant subelements of this group are poly(diallylphthalates), poly(diallylisophthalates), and poly(allyldiglycol carbonate). Chemistry, processing, and properties are also described. Allyl polymers are synthesized by radical polymerizations of allyl monomers that usually do not produce high-molecular-mass macromolecules. Therefore only a few specific monomers can produce thermosetting materials. Diallyldiglycolcarbonate (CR-39) and diallylphthalates are the most significant examples that have considerably improved our everyday life.
The interaction between lipid bilayers in water has been intensively studied over the last decades. Osmotic stress was applied to evaluate the forces between two approaching lipid bilayers in aqueous solution. The force–distance relation between lipid mono- or bilayers deposited on mica sheets using a surface force apparatus (SFA) was also measured. Lipid stabilised foam films offer another possibility to study the interactions between lipid monolayers. These films can be prepared comparatively easy with very good reproducibility. Foam films consist usually of two adsorbed surfactant monolayers separated by a layer of the aqueous solution from which the film is created. Their thickness can be conveniently measured using microinterferometric techniques. Studies with foam films deliver valuable information on the interactions between lipid membranes and especially their stability and permeability. Presenting inverse black lipid membrane (BLM) foam films supply information about the properties of the lipid self-organisation in bilayers. The present paper summarises results on microscopic lipid stabilised foam films by measuring their thickness and contact angle. Most of the presented results concern foam films prepared from dispersions of the zwitterionic lipid 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) and some of its mixtures with the anionic lipid — 1,2-dimyristoyl-sn-glycero-3-[phospho-rac-(1-glycerol)] (DMPG).
The strength of the long range and short range forces between the lipid layers is discussed. The van der Waals attractive force is calculated. The electrostatic repulsive force is estimated from experiments at different electrolyte concentrations (NaCl, CaCl2) or by modification of the electrostatic double layer surface potential by incorporating charged lipids in the lipid monolayers. The short range interactions are studied and modified by using small carbohydrates (fructose and sucrose), ethanol (EtOH) or dimethylsulfoxide (DMSO). Some results are compared with the structure of lipid monolayers deposited at the liquid/air interface (monolayers spread in Langmuir trough), which are one of most studied biomembrane model system. The comparison between the film thickness and the free energy of film formation is used to estimate the contribution of the different components of the disjoining pressure to the total interaction in the film and their dependence on the composition of the film forming solution.
Impact of phenolic resin preparation on its properties and its penetration behavior in Kraft paper
(2018)
The core of decorative laminates is generally made of stacked Kraft paper sheets impregnated with a phenolic resin. As the impregnation process in industry is relatively fast, new methods need to be developed to characterize it for different paper-resin systems. Several phenolic resins were synthesized with the same Phenol:Formaldehyde ratio of 1:1.8 and characterized by Fourier Transform Infrared Spectrometry (FTIR) as well as Size-Exclusion Chromatography (SEC). In addition, their viscosities and surface tensions when diluted in methanol to 45% of solid content were measured. The capacity of each resin to penetrate a Kraft paper sheet was characterized using a new method, which measures the conductivities induced by the liquid resin crossing the paper substrate. With this method, crossing times could be measured with a good accuracy. Surprisingly, the results showed that the penetration time of the resin samples is not correlated to the viscosity values, but rather to the surface tension characteristics and the chemical characteristics of paper. Furthermore, some resins had a higher swelling effect on the fibers that delayed the crossing of the liquid through the paper.
Properties data of phenolic resins synthetized for the impregnation of saturating Kraft paper
(2018)
The quality of decorative laminates boards depends on the impregnation process of Kraft papers with a phenolic resin,which constitute the raw materials for the manufacture of the cores of such boards.In the laminates industries,the properties of resins are adapted via their syntheses,usually by mixing phenol and formaldehyde in a batch,where additives,temperature and stirring parameters can be controlled. Therefore, many possibilities of preparation and phenolic resins exist, that leads to different combinations of physico chemical properties. In this article, the properties data of eight phenolic resins synthetized with different parameters of pH and reaction times at 60 °C and 90 °C are presented: the losses of pH after synthesis and the dynamic viscosities measured after synthesis and one the solid content is adjusted to 45%w/w in methanol. Data aquired by Differential Scanning Calorimetry (DSC) of the resins and Inverse Gas Chromatography (IGC) of cured solids are given as well.
In the course of a more intensive energy generation from regenerative sources, an increased number of energy storages is required. In addition to the widespread means of storing electric energy, storing energy thermally can contribute significantly. However, limited research exists on the behaviour of thermal energy storages (TES) in practical operation. While the physical processes are well known, it is nevertheless often not possible to adequately evaluate its performance with respect to the quality of thermal stratification inside the tank, which is crucial for the thermodynamic effectiveness of the TES. The behaviour of a TES is experimentally investigated in cyclic charging and discharging operation in interaction with a cogeneration (CHP) unit at a test rig in the lab. From the measurements the quality of thermal stratification is evaluated under varying conditions using different metrics such as normalised stratification factor, modified MIX number, exergy number and exergy efficiency, which extends the state of art for CHP applications. The results show that the positioning of the temperature sensors for turning the CHP unit on and off has a significant influence on both the effective capacity of a TES and the quality of thermal stratification inside the tank. It is also revealed that the positioning of at least one of these sensors outside the storage tank, i.e. in the return line to the CHP unit, prevents deterioration of thermal stratification, thereby enhancing thermodynamic effectiveness. Furthermore, the effects of thermal load and thermal load profile on effective capacity and thermal stratification are discussed, even though these are much smaller compared to the effect of positioning the temperature sensors.
Since November 2011 the standard DIN 4709 stipulates performance tests for Micro-CHP units in Germany. In contrast to steady state measurements of the CHP unit itself, the test according to DIN 4709 includes the thermal storage tank as well as the internal control unit, and it is based on a 24 h test cycle following a specified thermal load profile. Hence, heat losses from the storage tank are as well taken into account as transient losses of the CHP unit. In addition, the control strategy for loading and unloading the storage tank affects the test results.
The DIN 4709 test cycle has been applied at the test stand for Micro-CHP units at Reutlingen University, and results for the Micro-CHP unit WhisperGen and the EC Power units XRGI 15® and XRGI 20® are available. During the analysis a method has been developed to evaluate the results in case the test cycle does not end in a time slot between 24 and 24.5 h after the starting as demanded by DIN 4709. Since this method has been successfully applied to the test of various CHP units of different size and technology so far, it is suggested to incorporate it to DIN 4709 during the next revision of the standard.
The performance numbers obtained reveal the differences in efficiencies measured at steady-state on the one hand and following the DIN 4709 test cycle on the other hand. While the deviations in electrical efficiencies are small, thermal efficiencies according to DIN 4709 fall below steady state data by 3–6 percentage points. This is attributed to transient thermal losses and heat losses from the storage tank, which are not included in steady state and separate testing of the CHP unit, only.
Computers are increasingly used in teams in various contexts, for example in negotiations. Especially when using computer-support for decision making processes, it is an important question whether active collaboration within the team - for example via audio-conference - has additional benefits beyond the supply of full task-relevant information via computer. In team negotiations, team representatives are only able to represent the whole team, if diverse preferences of the team members are aligned prior to the negotiation. In an experimental study with 150 participants, we provided team members with the complete information about each other's preferences during an either collaboratively (computer-mediated) or seperately conducted computer-supported negotiation preparation and subsequently asked them for their priorities as representatives of the team. Our results showed that providing complete task-relevant information via computer is insufficient to compensate for the absence of active collaboration within the team.
Several ionic liquids are excellent solvents for cellulose. Starting from that finishing of PET fabrics with cellulose dissolved in ionic liquids like 1-ethyl 3-methyl imidazolium acetate, diethylphosphate and chloride, or the chloride of butyl-methyl imidazolium has been investigated. Finishing has been carried out from solutions of different concentrations, using microcrystalline cellulose or cotton and by employing different cross-linkers. Viscosity of solutions has been investigated for different ionic liquids,concentrations, cellulose sources, linkers and temperatures. Since ionic liquids exhibit no vapor pressure,simple pad-dry-cure processes are excluded. Before drying the ionic liquid has to be removed by a rinsing step. Accordingly rinsing with fresh ionic liquid followed by water or the direct rinsing with waterhave been tested. The amount of cellulose deposited has been investigated by gravimetry, zinc chlorideiodine test as well as reactive dyeing. Results concerning wettability, water up-take, surface resistance,wear-resistance or washing stability are presented.
Electric freight vehicles have the potential to mitigate local urban road freight transport emissions, but their numbers are still insignificant. Logistics companies often consider electric vehicles as too costly compared to vehicles powered by combustion engines. Research within the body of the current literature suggests that increasing the driven mileage can enhance the competitiveness of electric freight vehicles. In this paper we develop a numeric simulation approach to analyze the cost-optimal balance between a high utilization of medium-duty electric vehicles – which often have low operational costs – and the common requirement that their batteries will need expensive replacements. Our work relies on empirical findings of the real-world energy consumption from a large German field test with medium-duty electric vehicles. Our results suggest that increasing the range to the technical maximum by intermediate (quick) charging and multi-shift usage is not the most cost-efficient strategy in every case. A low daily mileage is more cost-efficient at high energy prices or consumptions, relative to diesel prices or consumptions, or if the battery is not safeguarded by a long warranty. In practical applications our model may help companies to choose the most suitable electric vehicle for the application purpose or the optimal trip length from a given set of options. For policymakers, our analysis provides insights on the relevant parameters that may either reduce the cost gap at lower daily mileages, or increase the utilization of medium-duty electric vehicles, in order to abate the negative impact of urban road freight transport on the environment.
Thin radio-frequency magnetron sputter deposited nano-hydroxyapatite (HA) films were prepared on the surface of a Fe-tricalcium phosphate (Fe-TCP) bioceramic composite, which was obtained using a conventional powder injection moulding technique. The obtained nano-hydroxyapatite coated Fe-TCP biocomposites (nano HA-Fe-TCP) were studied with respect to their chemical and phase composition, surface morphology, water contact angle, surface free energy and hysteresis. The deposition process resulted in a homogeneous, single-phase HA coating. The ability of the surface to support adhesion and the proliferation of human mesenchymal stem cells (hMSCs) was studied using biological short-term tests in vitro. The surface of the uncoated Fe-TCP bioceramic composite showed an initial cell attachment after 24 h of seeding, but adhesion, proliferation and growth did not persist during 14 days of culture.However, the HA-Fe-TCP surfaces allowed cell adhesion, and proliferation during 14 days. The deposition of the nano-HA films on the Fe-TCP surface resulted in higher surface energy, improved hydrophilicity and biocompatibility compared with the surface of the uncoated Fe-TCP. Furthermore, it is suggested that an increase in the polar component of the surface energy was responsible for the enhanced cell adhesion and proliferation in the case of the nano-HA Fe-TCP biocomposites.
Driven by digital transformation, manufacturing systems are heading towards autonomy. The implementation of autonomous elements in manufacturing systems is still a big challenge. Especially small and medium sized enterprises (SME) often lack experience to assess the degree of Autonomous Production. Therefore, a description model for the assessment of stages for Autonomous Production has been identified as a core element to support such a transformation process. In contrast to existing models, the developed SME-tailored model comprises different levels within a manufacturing system, from single manufacturing cells to the factory level. Furthermore, the model has been validated in several case studies.
The wet chemical deposition of solution processed transparent conducting oxides (TCO) provides an alternative low cost and economical deposition technique to realize large-areas of conducting films. Since the price for the most common TCO Indium Tin Oxide rises enormously, Aluminum Zinc Oxide (AZO) as alternative TCO reaches more and more interest. The optoelectronical properties of nanoparticle coatings strongly depend beneath the porosity of the coating on the shape and size of the used particles. By using bigger or rod-shaped particles it is possible to minimize the amount of grain boundaries resulting in an improvement of the electrical properties, whereas particles bigger than 100 nm should not be used if highly transparent coatings are necessary as these big particles scatter the visible light and lower the transmittance of the coatings. In this work we present a simple method to synthesize AZO particles with different shape and size, but comparable electronical properties. We use a simple, well reproducible polyol method for synthesis and influence the shape and size of the particles by adding different amounts of water to the precursor solution. We can show that the addition of aluminum as dopant strongly hinders the crystal growth but the addition of water counteracts this, so that both, spherical and rod-shaped particles can be obtained.
We report an investigation into the distribution of copper oxidation states in oxide films formed on the surfaces of technical copper. The oxide films were grown by thermal annealing at ambient conditions and studied using Auger depth profiling and UV–Vis spectroscopy. Both Auger and UV–Vis data were evaluated applying multivariate curve resolution (MCR). Both experimental techniques revealed that the growth of Cu2O dominates the initial ca. 40 nm of oxide films grown at 175 °C, while further oxide growth is dominated by CuO formation. The largely coincident results from both experimental approaches demonstrates the huge benefit of the application of UV–Vis spectroscopy in combination with MCR analysis, which provides access to information on chemical state distributions without the need for destructive sample analysis. Both approaches are discussed in detail.
Machine failures’ consequences – a classification model considering ultra-efficiency criteria
(2023)
To strive for a sustainable production, maintenance has to evaluate possible machine failure consequences not just economically but also holistically. Approaches such as the ultra-efficiency factory consider energy, material, human/staff, emission, and organization as optimization dimensions. These ultra-efficiency dimensions can be considered for analyzing not only the respective machine failure but also the effects on the entire production system holistically. This paper presents an easy to use method, based on a questionnaire, for assessing the failure consequences of a machine malfunction in a production system considering the ultra-efficiency dimensions. The method was validated in a battery production.
Increasing complexity in manufacturing processes poses new challenges for industrial maintenance. In addition, advanced machine monitoring and lifetime forecasting options expand the tools and maintenance strategies available. Today, maintenance strategy selection is performed sequentially usually based on prioritised machines and components. These selections are optimized locally for each machine isolated, not considering the context of other machines within the value-adding network. To overcome these challenges, this paper presents an approach for an integrated maintenance strategy selection in one-step by an integrated model considering possible machine failures and the context of other machines within the value-adding network in parallel.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
The use of deep learning models with medical data is becoming more widespread. However, although numerous models have shown high accuracy in medical-related tasks, such as medical image recognition (e.g. radiographs), there are still many problems with seeing these models operating in a real healthcare environment. This article presents a series of basic requirements that must be taken into account when developing deep learning models for biomedical time series classification tasks, with the aim of facilitating the subsequent production of the models in healthcare. These requirements range from the correct collection of data, to the existing techniques for a correct explanation of the results obtained by the models. This is due to the fact that one of the main reasons why the use of deep learning models is not more widespread in healthcare settings is their lack of clarity when it comes to explaining decision making.
The development of automatic solutions for the detection of physiological events of interest is booming. Improvements in the collection and storage of large amounts of healthcare data allow access to these data faster and more efficiently. This fact means that the development of artificial intelligence models for the detection and monitoring of a large number of pathologies is becoming increasingly common in the medical field. In particular, developing deep learning models for detecting obstructive apnea (OSA) events is at the forefront. Numerous scientific studies focus on the architecture of the models and the results that these models can provide in terms of OSA classification and Apnea-Hypopnea-Index (AHI) calculation. However, little focus is put on other aspects of great relevance that are crucial for the training and performance of the models. Among these aspects can be found the set of physiological signals used and the preprocessing tasks prior to model training. This paper covers the essential requirements that must be considered before training the deep learning model for obstructive sleep apnea detection, in addition to covering solutions that currently exist in the scientific literature by analyzing the preprocessing tasks prior to training.
The citizen-centered health platform project is intended to provide a platform that can be used in EU cross-border regions, where social and economic exchange occurs across national borders. The overriding challenges are: (a) social: improving citizen-centered health and care provision; (b) technical: providing a digital platform for networking citizens, service providers, and municipal actors; (c) economic: developing long-term successful (sustainable) business models/value chains. The platform should strengthen and expand existing networks and establish new regional networks. Each network addresses particular challenges and apply them in a region-specific manner. Here, the national boundary conditions and the interregional needs play an essential role. These objectives require sufficient participation of civil society representatives. Furthermore, the platform will establish an overarching, sustainable, and knowledge-based network of health experts. The platform is to be jointly developed and implemented in the regions and follow an open-access approach. Therefore, synergies will be shared more quickly, strengthening competencies and competitiveness. In addition to practice partners, scientific and municipal institutions and SMEs are involved. The actors thus contribute to scientific performance, innovative strength, and resilience.
The approach of self-organized and autonomous controlled systems offers great potential to meet new requirements for the economical production of customized products with small batch sizes based on a distributed, flexible management of dynamics and complexity within the production and intralogistics system. To support the practical application of self-organization for intralogistics systems, a catalogue of criteria for the evaluation of the self-organization of flexible logistics systems has been developed and validated, which enables the classification of logistics systems as well as the identification and evaluation of corresponding potentials that can be achieved by increasing the degree of self-organization.
The persistent development towards decreasing batch sizes due to an ongoing product individualization, as well as increasingly dynamic market and competitive conditions lead to new changeability requirements in production environments. Since each of the individualized products mgith require different base materials or components and manufacturing resources, the paths of the products giong through the factory as well as the required internal transport and material supply processes are going to differ for every product. Conventional planning and control systems, which rely on predifined processes and central decision-making, are not capable to deal with the arising system's complexity along the dimensions of changing goods, layouts and throughput requirements. The concepts of "self-organization" in combination with "autonomous ocntrol" provide promising solutions to solve these new requirements by using among other things the potential of autonomous, decentralized and target-optimized logistical objects (e.g. smart products, bins and conveyor systems) wich are able to communicate and interact with each other as well as with human wokers. To investigate the potential of automation and human-robot collaboration for intralogistics, a research project for the development of a collaborative tugger train has been started at the ESB Logistics Learning Factory in lin with various student projects in neighboring research areas. This collaboraive tugger train system in combination with other manual (e.g. handcarts) and (semi-) automated conveyoer systems (e.g. automated guided forklift) will be integrated into a dynamic, self-organized scenario with varying production batch sizes to develop a method for target-oriented sefl-organization and autonomous control of intralogistics systems. For a structured investigation of self-organized scenarios a generic intralogistics model as well as a criteria cataloghe has been developed. The ESB Logistics Learning will serve as a practice-oriented research, validation and demonstration environment for these purposes.
Future intralogistics systems need to adapt flexibly to changing material flow requirements in line with future versatile factory environments, producing personalized products under the performance and cost conditions of today's mass production. Small batch sized down to a batch size of "1" lead to a high complexity in the design and economical manufacturing of these customized products. Intralogistics systems are integrated into higher-level areas (segment level) as well as into upsteam and downstream performance units (system-wide areas). This includes the logistic activities relevant for the system (organized according to storage, picking, transport) such as transportation or storage tasks of tools, semi-finished products, components, assemblies and containers, and waste. Today's centralized material flow control systems, which work based on predefined processes, are not capable and more specifically not suitable to deal with the arising complexity of changeable intralogistics systems. Autononomous, decentralized material flow control systems distribute the required decision-making and control processes on intelligent logistic entities. A major step for the development of an autonomous control method for hybrid intralogistics systems (manual, semi-automated and automated) is the development of a generic archetype for intralogistics systems regarding the system boundaries, elements and relations resulting in a descriptive model taking into account amongst others the time of demand, availability of resources, economic efficiency and technical performance parameters. The ESB Logistics Learning Factory at ESB Business School (Reutlingen University) serves for this as a close-to-reality development and validation environment.
The increasing emergence of cyber-physical systems (CPS) and a global crosslinking of these CPS to cyber-physical production systems (CPPS) are leading to fundamental changes of future work and logistic systems requiring innovative methods to plan, control and monitor changeable production systems and new forms of human-machine-collaboration. Particularly logistic systems have to obey the versatility of CPPS and will be transferred to so-called cyber physical logistic systems, since the logistical networks will underlie the requirements of constant changes initiated by changeable production systems. This development is driven and enhanced by increasingly volatile and globalized market and manufacturing environments combined with a high demand for individualized products and services. Also nowadays mainly used centralized control systems are pushed to their limits regarding their abilities to deal with the arising complexity to plan, control and monitor changeable work and logistic systems. Decentralized control systems bear the potential to cope with these challenges by distributing the required operations on various nodes of the resulting decentralized control system.
Learning factories, like the ESB Logistics Learning Factory at ESB Business School (Reutlingen University), provide a wide range of possibilities to develop new methods and innovative technical solutions in a risk-free and close-to-reality factory environment and to transfer knowledge as well as specific competences into the training of students and professionals. To intensify the research and training activities in the field of future work and logistics systems, ESB Business School is transferring its existing production system into a CPPS involving decentralized planning, control and monitoring methods and systems, human-machine-collaboration as well as technical assistance systems for changeable work and logistics systems.
Decreasing batch sizes in production in line with Industrie 4.0 will lead to tremendous changes of the control of logistic processes in future production systems. Intelligent bins are crucial enablers to establish decentrally controlled material flow systems in value chain networks as well as at the intralogistics level. These intelligent bins have to be integrated into an overall decentralized monitoring and control approach and have to interact with humans and other entities just like other cyber-physical systems (CPS) within the cyber-physical production system (CPPS). To realize a decentralized material supply following the overall aim of a decentralized control of all production and logistics processes, an intelligent bin system is currently developed at the ESB Logistics Learning Factory. This intelligent bin system will be integrated into the self developed, cloud-based and event-oriented SES system (so-called “Self Execution System”) which goes beyond the common functionalities and capabilities of traditional manufacturing execution systems (MES).
To ensure a holistic integration of the intelligent bin for different material types into the SES framework, the required hard- and software components for the decentrally controlled bin system will be split into a common and an adaptable component. The common component represents the localization and network layer which is common for every bin, whereas the flexible component will be customizable to different requirements, like to the specific characteristics of the parts.
Comparative analysis of the R&D efficiency of 14 leading pharmaceutical companies for the years 1999–2018 shows that there is a close positive correlation between R&D spending and the two investigated R&D output parameters, approved NMEs and the cumulative impact factor of their publications. In other words, higher R&D investments (input) were associated with higher R&D output. Second, our analyses indicate that there are "economies of scale" (size) in pharmaceutical R&D.
We investigated the state of artificial intelligence (AI) in pharmaceutical research and development (R&D) and outline here a risk and reward perspective regarding digital R&D. Given the novelty of the research area, a combined qualitative and quantitative research method was chosen, including the analysis of annual company reports, investor relations information, patent applications, and scientific publications of 21 pharmaceutical companies for the years 2014 to 2019. As a result, we can confirm that the industry is in an ‘early mature’ phase of using AI in R&D. Furthermore, we can demonstrate that, despite the efforts that need to be managed, recent developments in the industry indicate that it is worthwhile to invest to become a ‘digital pharma player’.
Today, virtualizing pharma R&D is increasingly related with data analytics and artificial intelligence (AI), technologies that have been developed by software companies outside the healthcare sector. The process of virtualizing pharma R&D is closely related to the technological advancements that result in the generation of large data sets ranging from genomics, proteomics, metabolomics, medical imaging, IoT wearables and large clinical trials, making it necessary for pharma companies to find new ways to store and ultimately analyze information. As a consequence, pharma companies are experimenting with AI in R&D ranging from in-silico drug design to clinical trail participants identification or dosage error reduction.
Artificial intelligence (AI) technologies, such as machine learning or deep learning, have been predicted to highly impact future organizations and radically change the way how projects are managed. The Project Management Institute (PMI), the network of around 1.1 million certified project managers, ranked AI as one of the top three disruptors of their profession. In an own study on the effect of AI, 37% of the project management processes can be executed by machine learning and other AI technologies. In addition, Gartner recently postulated that 80% of the work of today's project managers may be eliminated by AI in 2030.
This editorial aims to outline today's project and portfolio management in context of pharmaceutical research and development (R&D), followed by an AI-vision and a more tangible mission, and illustrate what the consequences of an AI-enabled project and portfolio management could be for pharmaceutical R&D.
In smart factories, maintenance is still an important aspect to safeguard the performance of their production. Especially in case of failures of machine components diagnosis is a time-consuming task. This paper presents an approach for a cyber-physical failure management system, which uses information from machines such as programmable logic controller or sensor data and IT systems to support the diagnosis and repairing process. Key element is a model combining the different information sources to detect deviations and to determine a probable failed component. Furthermore, the approach is prototypically implemented for leakage detection in compressed air networks.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
For the widespread establishment of a circular economy, the acceptance of used products among consumers is a prerequisite. This paper investigates the customer experience of product service systems related to used products (PSSuP), such as renting, remanufacturing, and second-hand models, and aims to point out the offering characteristics that effect customer response and customer engagement. This study was conducted by means of a content analysis-based literature review of 69 empirical PSSuP studies. A frequency analysis of the categories that determine customer experience creation was conducted, as well as a contingency analysis to reveal the interrelationship between these categories. On this basis, the different PSSuP types were compared, and four strategic orientations of customer experience creation in PSSuP are pointed out: price, confidence, convenience, and delight orientation. For each of these strategic orientations, supportive PSSuP offering characteristics are specified. Building on the findings of this study, theoretical and managerial implications for product–service systems marketing are pointed out, and the need for research on the role of information and communication technology as an enabler of customer experience creation in PSSuP is highlighted.
Age-dependent migratory behavior of human endothelial cells revealed by substrate microtopography
(2019)
Cell migration is part of many important in vivo biological processes and is influenced by chemical and physical factors such as substrate topography. Although the migratory behavior of different cell types on structured substrates has already been investigated, up to date it is largely unknown if specimen's age affects cell migration on structures. In this work, we investigated age-dependent migratory behavior of human endothelial cells from young (≤ 31 years old) and old (≥ 60 years old) donors on poly(dimethylsiloxane) microstructured substrates consisting of well-defined parallel grooves. We observed a decrease in cell migration velocity in all substrate conditions and in persistence length perpendicular to the grooves in cells from old donors. Nevertheless, in comparison to young cells, old cells exhibited a higher cell directionality along grooves of certain depths and a higher persistence time. We also found a systematic decrease of donor age dependent responses of cell protrusions in orientation, velocity and length, all of them decreased in old cells. These observations lead us to hypothesize a possible impairment of actin cytoskeleton network and affected actin polymerization and steering systems, caused by aging.
Model-based hearing diagnosis based on wideband tympanometry measurements utilizing fuzzy arithmetic
(2019)
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves that represent the statistical range of normal hearing responses. Because of large inter-individual variances in the middle ear, especially in wideband tympanometry (WBT), specificity and quantitative evaluation are greatly restricted. A new model-based approach could transform today's predominantly qualitative hearing diganostics into a quantitative and tailored, patient-specific diagnosis, by evaluating WBT measurements with the aid of a middle-ear model. For this particular investigation, a finite element model of a human ear was used. It consisted of an acoustic ear canal and a tympanic cavity model, a middle-ear with detailed nonlinear models of the tympanic membrane and annular ligament, and a simplified inner-ear model. This model has made it possible to identify pathologies from measurements, by analyzing the parameters through senstivity studies and parameter clustering. Uncertainties due to the lack of knowledge, subjectivity in numerical implementation and model simplification are taken into account by the application of fuzzy arithmetic. The most confident parameter set can be determined by applying an inverse fuzzy method on the measurement data. The principle and the benefits of this model-based approach are illustrated by the example of a two-mass oscillator, and also by the simulation of the energy absorbance of an ear with malleus fixation, where the parameter changes that are introduced can be determined quantitatively through the system identification.
In vitro cultured cells produce a complex extracellular matrix (ECM) that remains intact after decellularization. The biological complexity derived from the variety of distinct ECM molecules makes these matrices ideal candidates for biomaterials. Biomaterials with the ability to guide cell function are a topic of high interest in biomaterial development. However, these matrices lack specific addressable functional groups, which are often required for their use as a biomaterial. Due to the biological complexity of the cell-derived ECM, it is a challenge to incorporate such functional groups without affecting the integrity of the biomolecules within the ECM. The azide-alkyne cycloaddition (click reaction, Huisgen-reaction) is an efficient and specific ligation reaction that is known to be biocompatible when strained alkynes are used to avoid the use of copper (I) as a catalyst. In our work, the ubiquitous modification of a fibroblast cell-derived ECM with azides was achieved through metabolic oligosaccharide engineering by adding the azide-modified monosaccharide Ac4GalNAz (1,3,4,6 tetra-O-acetyl-N-azidoacetylgalactosamine) to the cell culture medium. The resulting azide-modified network remained intact after removing the cells by lysis and the molecular structure of the ECM proteins was unimpaired after a gentle homogenization process. The biological composition was characterized in order to show that the functionalization does not impair the complexity and integrity of the ECM. The azides within this ‘‘clickECM” could be accessed by small molecules (such as an alkyne modified fluorophore) or by surface-bound cyclooctynes to achieve a covalent coating with clickECM.
Herein, biochar from biomass residues is demonstrated as active materials for the catalytic cracking of waste motor oil into diesel-like fuels. Above all, alkali-treated rice husk biochar showed great activity with a 250% increase in the kinetic constant compared to the thermal cracking. It also showed better activity than synthetic materials, as previously reported. Moreover, much lower activation energy (185.77 to 293.48 kJ/mol) for the cracking process was also obtained. According to materials characterization, the catalytic activity was more related to the nature of the biochar’s surface than its specific surface area. Finally, liquid products complied with all the physical properties defined by international standards for diesel-like fuels, with the presence of hydrocarbons chains between C10 - C27 similar to the ones obtained in commercial diesel.
On-chip metallization, especially in modern integrated BCD technologies, is often subject to high current densities and pronounced temperature cycles due to heat dissipation from power switches like LDMOS transistors. This paper continues the work on a sensor concept where small sense lines are embedded in the metallization layers above the active area of a switching LDMOS transistor. The sensors show a significant resistance change that correlates with the number of power cycles. Furthermore, influences of sense line layer, geometry and the dissipated energy are shown. In this paper, the focus lies on a more detailed analysis of the observed change in sense line resistance.
LDMOS transistors in integrated power technologies are often subject to thermo-mechanical stress, which degrades the on-chip metallization and eventually leads to a short. This paper investigates small sense lines embedded in the LDMOS metallization. It will be shown that their resistance depends strongly on the stress cycle number. Thus, they can be used as aging sensors and predict impending failures. Different test structures have been investigated to identify promising layout configurations. Such sensors are key components for resilient systems that adaptively reduce stress to allow aggressive LDMOS scaling without increasing the risk of failure.
Soft thermoplastic polysiloxane-urea-elastomers (PSUs) were prepared for the application as a biomaterial to replace the human natural lens after cataract surgery. PSUs were synthesized from amino-terminated polydimethylsiloxanes (PDMS), 4,4′-Methylenebis(cyclohexylisocyanate) (H12MDI) and 1,3–Bis(3-aminopropyl)-1,1,3,3–tetramethyldisiloxane (APTMDS) by a two-step polyaddition route. Such a material has to be highly transparent and must exhibit a low Young’s Modulus and excellent dimensional stability. Polydimethylsiloxanes in the range of 3000–33,000 g·mol−1 were therefore prepared by ring-chain-equilibration of octamethylcyclotetrasiloxane (D4) and APTMDS in order to study the influence of the soft segment molecular weight on the mechanical properties and the transparency of the PSU-elastomers. 2,4,6,8-Tetramethyl-2,4,6,8-tetraphenylcyclotetrasiloxane (D4Me,Ph) was co-polymerized with D4 in order to adjust the refractive index of the polydimethyl-methyl-phenyl-siloxane-copolymers to a value equivalent to a young human natural lens. Very elastic PSUs with Elongation at Break values higher than 700% were prepared. PSU-elastomers, synthesized from PDMS of molecular weights up to 18,000 g·mol−1, showed transmittance values of over 90% within the visible spectrum range. The soft segment refractive index was increased through the incorporation of 14 mol % of methyl-phenyl-siloxane from 1.4011 to 1.4346 (37 °C). Young’s Moduli of PSU-elastomers were around 1 MPa and lower at PDMS molecular weights up to 15,000 g·mol−1. 10-cycle hysteresis measurements were applied to evaluate the mechanical stability of the PSUs at repeated stress. Hysteresis values at 100% strain decreased from 32 to 2% (10th cycle) with increasing PDMS molecular weight. Furthermore, hysteresis at 5% strain was only detected in PSU-elastomers with low PDMS molecular weights. Finally, preliminary results of in vitro cytotoxicity tests on a PSU-elastomer showed no toxic effects on HaCaT-cells.
This article contains data on the synthesis and mechanical characterization of polysiloxane-based urea-elastomers (PSUs) and is related to the research article entitled “Influence of PDMS molecular weight on transparency and mechanical properties of soft polysiloxane-urea-elastomers for intraocular lens application” (Riehle et al., 2018) [1]. These elastomers were prepared by a two-step polyaddition using the aliphatic diisocyanate 4,4′-Methylenbis(cyclohexylisocyanate) (H12MDI), a siloxane-based chain extender 1,3-Bis(3-aminopropyl)-1,1,3,3-tetramethyldisiloxane (APTMDS) and amino-terminated polydimethylsiloxanes (PDMS) or polydimethyl-methyl-phenyl-siloxane-copolymers (PDMS-Me,Ph), respectively. (More details about the synthesis procedure and the reaction scheme can be found in the related research article (Riehle et al., 2018) [1]).
Amino-terminated polydimethylsiloxanes with varying molecular weights and PDMS-Me,Ph-copolymers were prepared prior by a base-catalyzed ring-chain equilibration of a cyclic siloxane and the endblocker APTMDS. This DiB article contains a procedure for the synthesis of the base catalyst tetramethylammonium-3-aminopropyl-dimethylsilanolate and a generic synthesis procedure for the preparation of a PDMS having a targeted number average molecular weight of 3000 g mol−1. Molecular weights and the amount of methyl-phenyl-siloxane within the polysiloxane-copolymers were determined by 1H NMR and 29Si NMR spectroscopy. The corresponding NMR spectra and data are described in this article.
Additionally, this DiB article contains processed data on in line and off line FTIR-ATR spectroscopy, which was used to follow the reaction progress of the polyaddition by showing the conversion of the diisocyanate. All relevant IR band assignments of a polydimethylsiloxane-urea spectrum are described in this article.
Finally, data on the tensile properties and the mechanical hysteresis-behaviour at 100% elongation of PDMS-based polyurea-elastomers are shown in dependence to the PDMS molecular weight.
Managerial accountants spend a large part of their working time on more operational activities in cost accounting, reporting, and operational planning and budgeting. In all these areas, there has been increasing discussion in recent years, both in theory and practice, about using more digital technologies. For reporting, this means not only an intensified discussion of technologies such as RPA and AI but also more intensive changes to existing reporting systems. In particular, management information systems (MIS), which are maintained by managerial accountants and used by managers for corporate management, should be mentioned here. Based on an empirical survey in a large German company, this article discusses the requirements and assessments of users when switching from a regular MIS to a cloud-based system.
Papermaking waste liquid (black liquor) is a serious source of water pollution worldwide. The subsequent treatment of it is very difficult cause it contains a large amount of lignin, inorganic salts, organic matter, and pigments, which lead to serious water pollution. Lignin is the main by-product of the paper industry and is the only natural aromatic recyclable resource. Its effective utilization rate is currently less than 3%. Therefore, how to effectively recycle lignin in papermaking waste liquid and further synthesize industrialized products is of great significance to the sustainable development and environmental protection. Besides, based on the shortage of petroleum resources in recent years, the application of biomass resources instead of petroleum resources in the industry is also an important issue. In this article, we explored the best optimal conditions for the oxypropylation and esterification of lignin, and prepared bio-bitumen based on modified lignin, and then applied it to the waterproof coating sheets. FTIR and mechanical properties (softening point, low-temperature flexibility, peel strength, etc.) were tested on the obtained waterproof coating sheets. The results show that the addition of modified lignin reduced the softening point and peel strength of the coating sheets. Interestingly, both oxypropylated lignin (OL) and esterified lignin (OEL) were very beneficial to resist the decrease in peel strength during the aging process, showing a significant improvement in the performance of the coating sheets after aging compared to the control.
Pokémon Go was the first mobile augmented reality (AR) game to reach the top of the download charts of mobile applications. However, little is known about this new generation of mobile online AR games. Existing theories provide limited applicability for user understanding. Against this background, this research provides a comprehensive framework based on uses and gratification theory, technology risk research, and flow theory. The proposed framework aims to explain the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to invest money in in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. The results show that hedonic, emotional, and social benefits and social norms drive consumer reactions while physical risks (but not data privacy risks) hinder consumer reactions. However, the importance of these drivers differs depending on the form of user behavior.
Towards a sustainable future, looking beyond the system boundaries of a single manufacturing company is necessary to promote meaningful collaborations in terms of circular economy principles. In this context digital data processing technologies to connect the potential collaborators are seen as enablers to make use of proven collaborative circular business models (CCBMs). Since most of such data processing technologies rely on features to describe the entities involved, it is essential to provide guidance for identifying and selecting the relevant and most appropriate ones. Defining critical success factors (CSFs) is considered a suitable instrument to describe the decisive factors. A systematic literature review (SLR), followed by a qualitative synthesis is investigating two scientific fields of work, namely (1) the general relevant features of CCBMs and, (2) methodologies for determining CSFs. This results in the development of a conceptual framework which provides guidance for digital applications that perform further digital processing based on the relevant CSFs relating to the specific CCBM.
In recent years, the numer of hybrid work systems using human robot collaboration (HRC) increased in industrial production environments - enhancing productivity while reducing work-related burden. Despite growing availability of HRC-suitable manipulation and safety technology, tools and techniques facilitating the design, planning and implementation process are still lacking. System engineers who strive to implement technically feasible, ergonomically meaningful and economically beneficial HRC application need to make design and technology decisions in various subject areas, whereas the design alternatives per morphological analysis is applied to establish a description model that can serve as both a supporting design guideline for future HRC application of value-adding, industrial quality as well as a tool to characterize and compare existing applications. It focuses on HRC within assembly processes, and illustrates the complexity of HRC applications in a comprehensible manner through its multi-dimensional structure. The morphology has been validated through its application on various existing industrial HRC applications, research demonstrators and interviews of experts from academia.
Close and safe interaction of humans and robots in joint production environments is technically feasible, however should not be implemented as an end in itself but to deliver improvement in any of a production system’s target dimensions. Firstly, this paper shows that an essential challenge for system integrators during the design of HRC applications is to identify a suitable distribution of available tasks between a robotic and a human resource. Secondly, it proposes an approach to determine task allocation by considering the actual capabilities of both human and robot in order to improve work quality. It matches those capabilities with given requirements of a certain task in order to identify the maximum congruence as the basis for the allocation decision. The approach is based on a study and subsequent generic description of human and robotic capabilities as well as a heuristic procedure that facilities the decision making process.
Film formation of self synthesized Polymer EPM–g–VTMDS (ethylene–propylene rubber, EPM, grafted with vinyltetramethyldisiloxane, VTMDS) was studied regarding bonding to adhesion promoter vinyltrimethoxysilane (VTMS) on oxidized 18/10 chromium/nickel–steel (V2A) stainless steel surfaces. Polymer films of different mixed solutions including commercial siloxane and silicone, dimethyl, vinyl group terminated crosslinker (HANSA SFA 42100, CAS# 68083-19-2, 0.35 mmol Vinyl/g) and platinum, 1,3-diethenyl-1,1,3,3-tetramethyldisiloxane complex Karstedt's catalyst (ALPA–KAT 1, CAS# 68478-92-2) were spin coated on V2A stainless steel surfaces with adsorbed VTMS thin layers in order to analyze film formation of EPM–g–VTMDS at early stages. Surface topography and chemical bonding of the high performance polymers on different oxidized V2A surfaces were investigated with X–ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), scanning electron microscopy (SEM) and surface enhanced Raman spectroscopy (SERS). AFM and SEM as well as XPS results indicated that the formation of the polymer film proceeds via growth of polymer islands. Chemical signatures of the essential polymer contributions, linker and polymer backbones, could be identified using XPS core level peak shape analysis and also SERS. The appearance of signals which are related to Si–O–Si can be seen as a clear indication of lateral crosslinking and silica network formation in the films on the V2A surface.
In visual adaptive tracking, the tracker adapts to the target, background, and conditions of the image sequence. Each update introduces some error, so the tracker might drift away from the target over time. To increase the robustness against the drifting problem, we present three ideas on top of a particle filter framework: An optical-flow-based motion estimation, a learning strategy for preventing bad updates while staying adaptive, and a sliding window detector for failure detection and finding the best training examples. We experimentally evaluate the ideas using the BoBoT dataseta. The code of our tracker is available online.
Crosslinked thermoplastics
(2014)
Cross-linked thermoplastics represent an important class of materials for numerous applications such as heat-shrinkable tubing, rotational molded parts, and polyolefin foams. By cross-linking olefins, their mechanical performance can be significantly enhanced. This chapter covers the three main methods for the cross-linking of thermoplastics: radiation cross-linking, chemical cross-linking with organic peroxides, and cross-linking using silane-grafting agents. It also considers the major effects of the cross-linking procedure on the performance of the thermoplastic materials discussed.
Cross-linked thermoplastics
(2022)
Cross-linked thermoplastics represent an important class of materials for numerous applications such as heat-shrinkable tubing, rotational molded parts, and polyolefin foams. By cross-linking olefins, their mechanical performance can be significantly enhanced. This chapter covers the three main methods for the cross-linking of thermoplastics: radiation cross-linking, chemical cross-linking with organic peroxides, and cross-linking using silane-grafting agents. It also considers the major effects of the cross-linking procedure on the performance of the thermoplastic materials discussed.
Preliminary results of homomorphic deconvolution application to surface EMG signals during walking
(2021)
Homomorphic deconvolution is applied to sEMG signals recorded during walking. Gastrocnemius lateralis and tibialis anterior signals were acquired according to SENIAM recommendation. MUAP parameters like amplitude and scale were estimated, whilst the MUAP shape parameter was fixed. This features a useful time-frequency representation of sEMG signal. Estimation of scale MUAP parameter was verified extracting the mean frequency of filtered EMG signal, extracted from the scale parameter estimated with two different MUAP shape values.
The present work proposes the use of modern ICT technologies such as smartphones, NFCs, internet, and web technologies, to help patients in carrying out their therapies. The implemented system provides a calendar with a reminder of the assumptions, ensures the drug identification through NFC, allows remote assistance from healthcare staff and family members to check and manage the therapy in real-time. The system also provides centralized information on the patient's therapeutic situation, helpful in choosing new compatible therapies.
Relationship marketing is an important issue in every business. Knowing the customers and establishing, maintaining and enhancing long-term customer relationships is a key component of long-term business success. Considering that sport is such big business today, it is surprising that this crucial approach to marketing has yet to be fully recognised either in literature or in the sports business itself. Relationship Marketing in Sports aims to fill this void by discussing and reformulating the principles of relationship marketing and by demonstrating how relationship marketing can be successfully applied in practice within a sports context. Written by a unique author team of academic and practitioner experience, the book provides the reader with: the first book to apply the principles of relationship marketing specifically to a sports context case studies from around the world to provide a uniquely global approach applicable worldwide strong pedagogical features including learning outcomes, overviews, discussion questions, glossary, guided reading and web links practical advice for professional, semi-professional and non-professional sporting organisations a companion website providing web links, case studies and PowerPoint slides for lecturers. Relationship Marketing in Sports is crucial reading for both students and professionals alike and marks a turning point in the marketing of sports.
Development of an easy teaching and simulation solution for an autonomous mobile robot system
(2019)
With mass customized production becoming the mainstream, industries are shifting from large-scale manufacturing to flexible and customized production of small batch sizes. Agile manufacturing strategies adopted by SMEs are driving the usage of collaborative robots in today's factories. Major challenges in the adoption of cobots in the industry are the lack of a highly trained workforce to program the robot to perform complex tasks and integration of robot systems to other smart devices in the factory. In addition, the teaching and simulation by non-robotics experts of many industrial collaborative robot systems like the KUKA LBR iiwa is a major challenge, since these systems are designed to be programmed by robot experts and not by shop floor workers or other non-experts. This paper describes the research and development activities done for reducing the barriers in operation and ensure holistic integration of LBR iiwa cobot in the assembly on the example of the ESB Logistics Learning Factory. These include a visual programming solution for the easy teaching of various tasks. Robotic tasts are classified based on common robotics applications and application-specific blocks abstracting specific actions are implemented. A factory worker with no programming competency cour create robot programs by combining these blocks using a Graphical User Interface. In addition, a simulation solution was developed to visualized, analyse, and optimize robotic workflow before deployment. an autonomous mobile robot is integrated with the LBR iiw to improve reconfigurability and thus also the productivity. The system as a whole is controlled using an event-driven distributed control system. Finally, the capabilities of the system are analysed based on the design principles of Industrie 4.0 and potential future research ideas are discussed to further improve the system.
The troubles began when Tom, the business analyst, asked the customer what he wants. The customer came up with good ideas for software features. Tom created a brilliant roadmap and defined the requirements for a new software product. Mary, the development team leader, was already eager to start developing and happy when she got the requirements. She and her team went ahead and created the software right away. Afterwards, Paul tested the software against the requirements. As soon as the software fulfilled the requirements, Linda, the product manager, deployed it to the customer. The customer did not like the software and ignored it. Ringo, the head of software development, was fired. How come? Nowadays, we have tremendous capabilities for creating nearly all kinds of software to fulfill the needs of customers. We can apply agile practices for reacting flexibly to changing requirements, we can use distributed development, open source, or other means for creating software at low cost, we can use cloud technologies for deploying software rapidly, and we can get enormous amounts of data showing us how customers actually use software products. However, the sad reality is that around 90% of products fail, and more than 60% of the features of a typical software product are rarely or never used. But there is a silver lining – an insight regarding successful features: Around 60% of the successes stem from a significant change of an initial idea. This gives us a hint on how to build the right software for users and customers.
A systematic study using a central composite design of experiments (DoE) was performed on the oxygen plasma surface modifications of two different polymers—Pellethane 2363-55DE, which is a polyurethane, and vinyltrimethoxysilane-grafted ethylene-propylene (EPR-g-VTMS), a cross-linked ethylene-propylene rubber. The impacts of four parameters—gas pressure, generator power, treatment duration, and process temperature—were assessed, with static contact angles and calculated surface free energies (SFEs) as the main responses in the DoE. The plasma effects on the surface roughness and chemistry were determined using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Through the sufficiently accurate DoE model evaluation, oxygen gas pressure was established as the most impactful factor, with the surface energy and polarity rising with falling oxygen pressure. Both polymers, though different in composition, exhibited similar modification trends in surface energy rise in the studied system. The SEM images showed a rougher surface topography after low pressure plasma treatments. XPS and subsequent multivariate data analysis of the spectra established that higher oxidized species were formed with plasma treatments at low oxygen pressures of 0.2 mbar.
Human bestrophin-1 (hBest1) is a transmembrane Ca2+- dependent anion channel, associated with the transport of Cl−, HCO3- ions, γ-aminobutiric acid (GABA), glutamate (Glu), and regulation of retinal homeostasis. Its mutant forms cause retinal degenerative diseases, defined as Bestrophinopathies. Using both physicochemical - surface pressure/mean molecular area (π/A) isotherms, hysteresis, compressibility moduli of hBest1/sphingomyelin (SM) monolayers, Brewster angle microscopy (BAM) studies, and biological approaches - detergent membrane fractionation, Laurdan (6-dodecanoyl-N,N-dimethyl-2-naphthylamine) and immunofluorescence staining of stably transfected MDCK-hBest1 and MDCK II cells, we report:
1) Ca2+, Glu and GABA interact with binary hBest1/SM monolayers at 35 °C, resulting in changes in hBest1 surface conformation, structure, self-organization and surface dynamics. The process of mixing in hBest1/SM monolayers is spontaneous and the effect of protein on binary films was defined as “fluidizing”, hindering the phase-transition of monolayer from liquid-expanded to intermediate (LE-M) state;
2) in stably transfected MDCK-hBest1 cells, bestrophin-1 was distributed between detergent resistant (DRM) and detergent-soluble membranes (DSM) - up to 30 % and 70 %, respectively; in alive cells, hBest1 was visualized in both liquid-ordered (Lo) and liquid-disordered (Ld) fractions, quantifying protein association up to 35 % and 65 % with Lo and Ld. Our results indicate that the spontaneous miscibility of hBest1 and SM is a prerequisite to diverse protein interactions with membrane domains, different structural conformations and biological functions.
Parallel grippers offer multiple applications thanks to their flexibility. Their application field ranges from aerospace and automotive to medicine and communication technologies. However, the application of grippers has the problem of exhibition wear and errors during the execution of their operation. This affects the performance of the gripper. In this context, the remaining useful life (RUL) defines the remaining lifespan until failure for an asset at a particular time of operation occurs. The exact lifespan of an asset is uncertain, thus the RUL model and estimation must be derived from available sources of information. This paper presents a method for the estimation of the RUL for a two-jaw parallel gripper. After the introduction to the topic, an overview of existing literature and RUL methods are presented. Subsequently, the method for estimating the RUL of grippers is explained. Finally, the results are summarized and discussed before the outlook and further challenges are presented.
Due to constantly changing conditions, demand, and technologies, companies increasingly seek flexibility. Productivity results from automation, improved working conditions and the focus of people in production in interaction with machines. Unfortunately, the human factor is often not considered to increase flexibility and productivity with new concepts. This work aims to develop a hybrid assistance system that allows a dynamic configuration of cyber-physical production systems considering the current order situation and available resources utilizing simulation. The system also considers human factors in addition to economic factors, which contributes to the extended economic appraisal.
Propofol is a commonly used intravenous general anesthetic. Multi-capillary column (MCC) coupled ion-mobility spectrometry (IMS) can be used to quantify exhaled propofol, and thus estimate plasma drug concentration. Here, we present results of the calibration and analytical validation of a MCC/IMS pre-market prototype for propofol quantification in exhaled air.
Nanocoatings based on sol–gel coatings are presented as suitable tool to modify materials based on polymers. The main focus is set onto textiles as the most common polymer materials. It presents which types of functionalization can be reached by modified sol–gel processes. Also a suitable categorization of functions is given and set into relation to common applications. A special focus is set on the functional properties, antimicrobial, UV protective, and flame retardant. The concept of bifunctional coatings is discussed and especially the combination of water-repellent and antistatic is presented.
The paper illustrates the status quo of a research project for the development of a control system enabling CHP units for a demand-oriented electricity production by an intelligent management of the heat storage tank. Thereby the focus of the project is twofold. One is the compensation of the fluctuating power production by the renewable energies solar and wind. Secondly, a reduction of the load on the power grid is intended by a better match of local electricity demand and production. In detail, the general control strategy is outlined, the method utilized for forecasting heat and electricity demand is illustrated as well as a correlation method for the temperature distribution in the heat storage tank based on a Sigmoid function is proposed. Moreover, the simulation model for verification and optimization of the control system and the two field test sites for implementing and testing the system are introduced.
Instead of waiting for and constantly adapting to details of political interventions, utilities need to focus on their environment from a holistic perspective. The unique position of the company - be it a local utility, a bigger player, or an international utility specializing in specitic segments - has to be the basis of goals and strategies. But without consistent translation of these goals and strategies into processes, structures, and company culture, a strategy remains pure theory. Companies need to engage in a continuing learning process. This means being willing to pass on strategies, to slow down or speed up, to work from a different angle etc.
The generous feed-in tariffs (FiTs) introduced in Germany—which resulted in major growth in decentralized solar photovoltaic (PV) systems—will phase out in the coming years, making many of the existing distributed generation assets stranded. This challenge creates an opportunity for community-focused energy utilities, such as Elektrizitätswerke Schönau eG (EWS) based in Schönau, Germany, to try a new approach to assist its customers, makes the transition to a more sustainable future. This chapter describes how EWS is developing products and offering community-based solutions including peer-to-peer trading using automated platforms. Such innovative offering may lead to successful differentiation in a competitive and highly decentralized future.