Refine
Document Type
- Journal article (199)
- Book chapter (21)
- Conference proceeding (18)
- Anthology (2)
- Book (1)
- Review (1)
- Working Paper (1)
Is part of the Bibliography
- yes (243)
Institute
- ESB Business School (96)
- Life Sciences (66)
- Informatik (47)
- Technik (25)
- Texoversum (9)
Publisher
- Elsevier (243) (remove)
Rare but extreme events, such as pandemics, terror attacks, and stock market collapses, pose a risk that could undermine cooperation in societies and groups. We extend the public goods game (PGG) to investigate the relationship between rare but extreme external risks and cooperation in a laboratory experiment. By incorporating risk as an external random variable in the PGG, independent of the participants’ contributions, we preserve the economic equilibrium of non-cooperation in the original game. Furthermore, we examine whether cooperation can be restored by the relatively simple intervention of informing about countermeasures while keeping the actual risk constant. Our experimental results reveal that on average extreme risks indeed decrease contributions by about 20%; however, countermeasure information increases contributions by about 10%. Specifically, in the first interactions, cooperation levels can even reach those observed in the riskless baseline. Our results suggest that countermeasure information could help reinforce social cohesion and resilience in the face of rare but extreme risks.
Wave-like differential equations occur in many engineering applications. Here the engineering setup is embedded into the framework of functional analysis of modern mathematical physics. After an overview, the –Hilbert space approach to free Euler–Bernoulli bending vibrations of a beam in one spatial dimension is investigated. We analyze in detail the corresponding positive, selfadjoint differential operators of 4-th order associated to the boundary conditions in statics. A comparison with free string wave swinging is outlined.
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.
Plasmonics and nanophotonics both deal with the interaction of light with structures of typically sub-wavelength size in one of more dimensions. Over the past decade or two, interest in these topics has grown significantly. This includes basic research towards detailed understanding of light-matter interaction and the manipulation of light on the nanometer scale as well as the search for applications ranging from quantum information processing, data storage, solar cells, spectroscopy and microscopy to (bio-)sensors and biomedical devices. Key enablers for this development are advanced materials and the variety of techniques to structure them with nanometer precision on the one hand, and progress in the theoretical description and numerical implementations, on the other. Besides the traditional metals Au, Ag, Al, and Cu also compounds such as refractory metal nitrides with much higher durability as well as semiconductors, dielectrics and hybrid structures have become of interest. Structuring techniques are not only aiming at the fabrication of individual elements with highest precision for detailed interaction analysis, but also at methods for large scale, low-cost nanofabrication mostly for sensor applications. In the former case, mostly electron beam lithography and focused ion beam milling are employed, while for high throughput various forms of nanoimprint and self-assembly based techniques are favored. Thin film deposition and pattern transfer techniques are mostly derived from those developed for nano-electronics, however more recently methods such as electroless plating, atomic layer deposition or etching and 3-D additive techniques are appearing. Thus, highly specialized expertise has been acquired in the different disciplines, and successful research and technology transfer will draw from this pool of knowledge.
Different network architectures are being used to build remote laboratories. Historically, it has been difficult to integrate industrial control systems with higher level IT systems like enterprise resource planning (ERP), manufacturing execution systems (MES), and manufacturing operations management (MOM). Getting these systems to communicate with one another has proven to be relatively difficult due to the absence of shared protocols between them. The Open Platform Communications United Architecture (OPC-UA) protocol was introduced as a remedy for this issue and is gaining popularity, but what if open-source protocols that are widely used in the IT industry could be used instead? This paper presents the development of an IT-Architecture for a cyber-physical industrial control systems laboratory that enables a seamless interconnection and integration of its elements. The architecture utilises Node-Red technology. Node-RED is an open-source programming platform developed by IBM that is focused on making it simple to link physical components, APIs, and web services. This cyber-physical laboratory is for learning principles of an industrial cascaded process control factory. Finally, this text will also discuss future work relating to digital twin (DT). A coupled tank system is selected as a teaching factory to illustrate a range of fluid control application in a typical chemical process factory.
In the context of Industry 4.0, intralogistics faces an increasingly complex and dynamic environment driven by a high level of product customisation and complex manufacturing processes. One approach to deal with these changing conditions is the decentralised and intelligent connectivity of intralogistics systems. However, wireless connectivity presents a major challenge in the industry due to strict requirements such as safety and real-time data transmission. In this context, the fifth generation of mobile communications (5G) is a promising technology to meet the requirements of safety-critical applications. Particularly, since 5G offers the possibility of establishing private 5G networks, also referred to as standalone non-public networks. Through their isolation from public networks, private 5G networks provide exclusive coverage for private organisations offering them high intrinsic network control and data security. However, 5G is still under development and is being gradually introduced in a continuous release process. This process lacks transparency regarding the performance of 5G in individual releases, complicating the successful adoption of 5G as an industrial communication. Additionally, the evaluation of 5G against the specified target performance is insufficient due to the impact of the environment and external interfering factors on 5G in the industrial environment. Therefore, this paper aims to develop a technical decision-support framework that takes a holistic approach to evaluate the practicality of 5G for intralogistics use cases by considering two fundamental stages. The first of these analyses technical parameters and characteristics of the use case to evaluate the theoretical feasibility of 5G. The second stage investigates the application's environment, which substantially impacts the practicality of 5G, for instance, the influence of surrounding materials. Finally, a case study validates the proposed framework by means of an autonomous mobile robot. As a result, the validation proves the proposed framework's applicability and shows the practicality of the autonomous mobile robot, when integrating it into a private 5G network testbed.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
The present study investigated the possibilities and limitations of using a low-cost NIR spectrometer for the verification of the presence of the declared active pharmaceutical ingredients (APIs) in tablet formulations, especially for medicine screening studies in low-resource settings. Spectra from 950 to 1650 nm were recorded for 170 pharmaceutical products representing 41 different APIs, API combinations or placebos. Most of the products, including 20 falsified medicines, had been collected in medicine quality studies in African countries. After exploratory principal component analysis, models were built using data-driven soft independent modelling of class analogy (DD-SIMCA), a one-class classifier algorithm, for tablet products of penicillin V, sulfamethoxazole/trimethoprim, ciprofloxacin, furosemide, metronidazole, metformin, hydrochlorothiazide, and doxycycline. Spectra of amoxicillin and amoxicillin/clavulanic acid tablets were combined into a single model. Models were tested using Procrustes cross-validation and by projection of spectra of tablets containing the same or different APIs. Tablets containing no or different APIs could be identified with 100 % specificity in all models. A separation of the spectra of amoxicillin and amoxicillin/clavulanic acid tablets was achieved by partial least squares discriminant analysis. 15 out of 19 external validation products (79 %) representing different brands of the same APIs were correctly identified as members of the target class; three of the four rejected samples showed an API mass percentage of the total tablet weight that was out of the range covered in the respective calibration set. Therefore, in future investigations larger and more representative spectral libraries are required for model building. Falsified medicines containing no API, incorrect APIs, or grossly incorrect amounts of the declared APIs could be readily identified. Variation between different NIR-S-G1 spectroscopic devices led to a loss of accuracy if spectra recorded with different devices were pooled. Therefore, piecewise direct standardization was applied for calibration transfer. The investigated method is a promising tool for medicine screening studies in low-resource settings.
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.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
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.
The Industry 4.0 paradigm requires concepts for integrating intelligent/ smart IoT Solutions into manufacturing. Such intelligent solutions are envisioned to increase flexibility and adaptability in smart factories. Especially autonomous cobots capable of adapting to changing conditions are a key enabler for changeable factory concepts. However, identifying the requirements and solution scenarios incorporating intelligent products challenges the manufacturing industry, especially in the SME sector. In pick and place scenarios, changing coordinate systems of workpiece carriers cause placing process errors. Using the IPIDS framework, this paper describes the development of a tool-center-point positioning method to improve the process stability of a collaborative robot in a changeable assembly workstation. Applying the framework identifies the requirement for an intelligent workpiece carrier as a part of the solution. Implementing and evaluating the solution within a changeable factory validates the IPIDS framework.
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.
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.
Mesoporous silica microspheres (MPSMs) find broad application as separation materials in high liquid chromatography (HPLC). A promising preparation strategy uses p(GMA-co-EDMA) as hard templates to control the pore properties and a narrow size distribution of the MPMs. Here six hard templates were prepared which differ in their porosity and surface functionalization. This was achieved by altering the ratio of GMA to EDMA and by adjusting the proportion of monomer and porogen in the polymerization process. The various amounts of GMA incorporated into the polymer network of P1-6 lead to different numbers of tetraethylene pentamine in the p(GMA-co-EDMA) template. This was established by a partial least squares regression (PLS-R) model, based on FTIR spectra of the templates. Deposition of silica nanoparticles (SNP) into the template under Stoeber conditions and subsequent removal of the polymer by calcination result in MPSM1-6. The size of the SNPs and their incorporation depends on the pore parameters of the template and degree of TEPA functionalization. Moreover, the incorporated SNPs construct the silica network and control the pore parameters of the MPSMs. Functionalization of the MPSMs with trimethoxy (octadecyl) silane allows their use as a stationary phase for the separation of biomolecules. The pore characteristics and the functionalization of the template determine the pore structure of the silica particles and, consequently, their separation properties.
The fifth generation of mobile communication (5G) is a wireless technology developed to provide reliable, fast data transmission for industrial applications, such as autonomous mobile robots and connect cyber-physical systems using Internet of Things (IoT) sensors. In this context, private 5G networks enable the full performance of industrial applications built on dedicated 5G infrastructures. However, emerging wireless communication technologies such as 5G are a complex and challenging topic for training in learning factories, often lacking physical or visual interaction. Therefore, this paper aims to develop a real-time performance monitoring system of private 5G networks and different industrial 5G devices to visualise the performance and impact factors influencing 5G for students and future connectivity experts. Additionally, this paper presents the first long-term measurements of private 5G networks and shows the performance gap between the actual and targeted performance of private 5G networks.
Since its first publication in 2015, the learning factory morphology has been frequently used to design new learning factories and to classify existing ones. The structuring supports the concretization of ideas and promotes exchange between stakeholders.
However, since the implementation of the first learning factories, the learning factory concept has constantly evolved.
Therefore, in the Working Group "Learning Factory Design" of the International Association of Learning Factories, the existing morphology has been revised and extended based on an analysis of the trends observed in the evolution of learning factory concepts. On the one hand, new design elements were complemented to the previous seven design dimensions, and on the other hand, new design dimensions were added. The revised version of the morphology thus provides even more targeted support in the design of new learning factories in the future.
High-performance liquid chromatography is one of the most important analytical tools for the identification and separation of substances. The efficiency of this method is largely determined by the stationary phase of the columns. Although monodisperse mesoporous silica microspheres (MPSM) represent a commonly used material as stationary phase their tailored preparation remains challenging. Here we report on the synthesis of four MPSMs via the hard template method. Silica nanoparticles (SNPs) which form the silica network of the final MPSMs were generated in situ from tetraethyl orthosilicate (TEOS) in the presence of (3-aminopropyl) triethoxysilane (APTES) functionalized p(GMA-co-EDMA) as hard template. Methanol, ethanol, 2-propanol, and 1-butanol were applied as solvents to control the size of the SNPs in the hybrid beads (HB). After calcination, MPSMs with different sizes, morphology and pore properties were obtained and characterized by scanning electron microscopy, nitrogen adsorption and desorption measurements, thermogravimetric analysis, solid state NMR and DRIFT IR spectroscopy. Interestingly, the 29Si NMR spectra of the HBs show T and Q group species which suggests that there is no covalent linkage between the SNPs and the template. The MPSMs were functionalized with trimethoxy (octadecyl) silane and used as stationary phases in reversed-phase chromatography to separate a mixture of eleven different amino acids. The separation characteristics of the MPSMs strongly depend on their morphology and pore properties which are controlled by the solvent during the preparation of the MPSMs. Overall, the separation behavior of the best phases is comparable with those of commercially available columns. The phases even achieve faster separation of the amino acids without loss of quality.
The increase in product variance and shorter product lifecycles result in higher production ramp-up frequencies and promote the usage of mixed-model lines. The ramp-up is considered a critical step in the product life cycle and in the automotive industry phases of the ramp-up are often executed on separated production lines (pilot lines) or factories (pilot plants) to verify processes and to qualify employees without affecting the production of other products in the mixed-model line. The required financial funds for planning and maintaining dedicated pilot lines prevent small and medium-sized enterprises (SMEs) from the application. Hence, SMEs require different tools for piloting and training during the production ramp-up. Learning islands on which employees can be trained through induced and autonomous learning propose a solution. In this work, a concept for the development and application which contains the required organization, activities, and materials is developed through expert interviews. The results of a case study application with a medium-sized automotive manufacturer show that learning islands are a viable tool for employee qualification and process verification during the ramp-up of mixed-model lines.
Monitoring heart rate and breathing is essential in understanding the physiological processes for sleep analysis. Polysomnography (PSG) system have traditionally been used for sleep monitoring, but alternative methods can help to make sleep monitoring more portable in someone's home. This study conducted a series of experiments to investigate the use of pressure sensors placed under the bed as an alternative to PSG for monitoring heart rate and breathing during sleep. The following sets of experiments involved the addition of small rubber domes - transparent and black - that were glued to the pressure sensor. The resulting data were compared with the PSG system to determine the accuracy of the pressure sensor readings. The study found that the pressure sensor provided reliable data for extracting heart rate and respiration rate, with mean absolute errors (MAE) of 2.32 and 3.24 for respiration and heart rate, respectively. However, the addition of small rubber hemispheres did not significantly improve the accuracy of the readings, with MAEs of 2.3 bpm and 7.56 breaths per minute for respiration rate and heart rate, respectively. The findings of this study suggest that pressure sensors placed under the bed may serve as a viable alternative to traditional PSG systems for monitoring heart rate and breathing during sleep. These sensors provide a more comfortable and non-invasive method of sleep monitoring. However, the addition of small rubber domes did not significantly enhance the accuracy of the readings, indicating that it may not be a worthwhile addition to the pressure sensor system.