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Increasing concerns regarding the world´s natural resources and sustainability continue to be a major issue for global development. As a result several political initiatives and strategies for green or resource-efficient growth both on national and international levels have been proposed. A core element of these initiatives is the promotion of an increase of resource or material productivity. This dissertation examines material productivity developments in the OECD and BRICS countries between 1980 and 2008. By applying the concept of convergence stemming from economic growth theory to material productivity the analysis provides insights into both aspects: material productivity developments in general as well potentials for accelerated improvements in material productivity which consequently may allow a reduction of material use globally. The results of the convergence analysis underline the importance of policy-making with regard to technology and innovation policy enabling the production of resource-efficient products and services as well as technology transfer and diffusion.
Long-term stability of membranes in membrane distillation operation is a problem nowadays which prevents the industrial breakthrough of this separation process. Fouling or slow pore wetting are the basic reasons for this.
Membrane distillation membranes were made by NIPS process rendering the membrane asymmetrically to achieve low permeation resistance and pores which can be over coated with polyelectrolyte polymers thus leading to thermopervaporation membranes. Those membranes prohibit pore wetting and may strongly reduce resorption of organic substances on for membrane distillation typically used hydrophobic surfaces thus leading to longterm operation stability in dewatering including stable membrane cleaning.
Asymmetric PVDF membranes have been coated with cation exchange polyelectrolyte leading to a very thin, defect-free layer which has a high permeation rate for water due to the domain structure of phase-separated hydrophilic and hydrophobic three-dimensional structures.
One of strategically important issues of energy security of Ukraine and the countries of Europe today is to reduce the consumption of natural gas. This task is particularly relevant in winter, when a significant amount of natural gas is consumed for heating premises. Therefore, one can predict that in the nearest future, in Ukraine and European countries, premises will be heated more frequently by electrical energy.
A massive transition to electric heating of premises under conditions of the implementation of national objective in Ukraine and the countries of Europe related to a significant reduction in energy consumption necessitates to rethink the process of control over electric heating of premises. It is required that the algorithms that control power supply to premises should include mechanisms for planning the amount of electric energy consumed by an individual. This is especially true of such energy-intensive processes like heating the premises.
Therefore, it is an important task for Ukraine and the countries of Europe to work out an approach for creating systems to control electric heating of premises in a house or apartment that would take into consideration not only information about the desired temperature regime, but also information on the desired amount of electricity needed for heating.
Drug-induced liver toxicity is one of the most common reasons for the failure of drugs in clinical trials and frequent withdrawal from the market. Reasons for such failures include the low predictive power of in vivo studies, that is mainly caused by metabolic differences between humans and animals, and intraspecific variances. In addition to factors such as age and genetic background, changes in drug metabolism can also be caused by disease-related changes in the liver. Such metabolic changes have also been observed in clinical settings, for example, in association with a change in liver stiffness, a major characteristic of an altered fibrotic liver. For mimicking these changes in an in vitro model, this study aimed to develop scaffolds that represent the rigidity of healthy and fibrotic liver tissue. We observed that liver cells plated on scaffolds representing the stiffness of healthy livers showed a higher metabolic activity compared to cells plated on stiffer scaffolds. Additionally, we detected a positive effect of a scaffold pre-coated with fetal calf serum (FCS)-containing media. This pre-incubation resulted in increased cell adherence during cell seeding onto the scaffolds. In summary, we developed a scaffold-based 3D model that mimics liver stiffness-dependent changes in drug metabolism that may more easily predict drug interaction in diseased livers.
Health monitoring in a home environment can have broader use since it may provide continuous control of health parameters with relatively minor intrusiveness into regular life. This work aims to verify if it is possible to replace the typical in some sleep medicine areas subjective questioning by an objective measurement using electronic devices. For this purpose, a study was conducted with ten subjects, in which objective and subjective measurement of relevant sleep parameters took place. The results of both measurement methods were evaluated and analyzed. The results showed that while for some measures, such as Total Time in Bed, there is a high agreement between objective and subjective measurements, for others, such as sleep quality, there are significant differences. For this reason, currently, a combination of both measurement methods may be beneficial and provide the most detailed results, while a partial replacement can already reduce the number of questions at the subjective measurement by measurement through electronic devices.
Development of an IoT-based inventory management solution and training module using smart bins
(2023)
Flexibility, transparency and changeability of warehouse environments are playing an increasingly important role to achieve a cost-efficient production of small batch sizes. This results in increasing requirements for warehouses in terms of flexibility, scalability, reconfigurability and transparency of material and information flows to deal with large number of different components and variable material and information flows due to small batch sizes. Therefore, an IoT-based inventory management solution and training module has been developed, implemented and validated at Werk150 – the Factory on campus of the ESB Business School. Key elements of the developed solution are smart bins using weight mats to track the bin’s content and additional sensors and buttons which are connected to an IoT – Hub to collect data of material consumption and manual handling operations. The use of weight mats for the smart bins offers the possibility to measure the container content independent of the specific component geometry and thus for a variety of components based on the specific component weights. The developed solution enables focusing on key for success elements of the system to provide synchronization of the flow of materials and information resulting an increase of flexibility and significantly higher transparency of the material flow. AIbased algorithms are applied to analyse the gathered data and to initiate process optimizations by providing the logistics decision makers a profound and transparent basis for decision making. In order to provide students and industry visitors of the learning factory with the necessary competences and to support the transfer into practice, a training module on IoT-based inventory management was developed and implemented.
Manufacturing companies are confronted with external (e.g. short-term change of product configuration by the customer) and internal (e.g. production process deviations) turbulences which are affecting the performance of production. Predefined, centrally controlled logistics processes are limiting the possibilities of production to initiate countermeasures to react in an optimized way to these turbulences. The autonomous control of intralogistics offers a great potential to cope with these turbulences by using the respective flexibility corridors of production systems and applying intelligent logistic objects with decentralized decision and process execution capabilities to maintain a target-optimized production. A method for AI-based storage-location- and material-handling-optimization to achieve performance-optimized intralogistics system through continuous monitoring of performance-relevant parameters and influencing factors by using AI (e.g. for pattern recognition) has been developed. To provide the basis to investigate and demonstrate the potentials of autonomously controlled intralogistics in connection with turbulences of production and in combination with AI, an intelligent warehouse involving an indoor localization system, smart bins, manual, semi-automated/collaborative and autonomous transport systems has been developed and implemented at Werk150, the factory on campus of ESB Business School (Reutlingen University). This scenario, which has been integrated into graduate training modules, allows the analysis and demonstration of different measures of intralogistics to cope with turbulences in production involving amongst others storage and material provision processes. The target fulfilment of the applied intralogistics measures to master arising turbulences is assessed based on the overall performance of production considering lead times and adherence to delivery dates. By applying artificial intelligence (AI) algorithms the intelligent logistical objects (smart bin, transport systems, etc.) as well as the entire logistics system should be enabled to improve their decision and process execution capabilities to master short-term turbulences in the production system autonomously.
Development of an indoor positioning system to create a digital shadow of production plant layouts
(2023)
The objective of this dissertation is to develop an indoor positioning system that allows the creation of a digital shadow of the plant layout in order to continuously represent the actual state of the physical layout in the virtual space. In order to define the requirements for such a system, potential stakeholders who could benefit from a digital shadow in the context of the plant layout were analysed. In order to generate added value for their work, the requirements were derived from their perspective. As the core of an indoor positioning system is the sensory aspect to capture the physical layout parameters, different potential technologies were compared and evaluated in terms of their suitability for this particular application. Derived from this analysis, the selected concept is based on the use of a pan-tilt-zoom (PTZ) camera in combination with fiducial markers. In order to determine specific camera parameters, a series of experiments were conducted which were necessary to develop the measurement method as well as the mathematical calculation method and coordinate transformation for the determination of poses (positions and angular orientations) of the respective facilities in the plant. In addition, an experimental validation was performed to ensure that the limit values for individual parameters determined in the requirements analysis can be met.
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.
Process risks are omnipresent in the corporate world and repeatedly present organizations with the challenge of how to deal with these risks. Efforts in trying to analyze and prevent these risks are costly and require many resources, which do not always bring the desired added value. The goal of this work is to determine how a benefit-oriented resource allocation can be made for risk-oriented process management. For this purpose, the following research question is posed: "How can systematic prioritization decisions regarding risk-oriented process management be made?” To answer it, an evaluation procedure is developed which assesses processes based on their characteristics regarding potential risk disposition as well as entrepreneurial relevance. For this purpose, requirements for such a procedure are first collected and used to define selection criteria for it. After the detailed analysis of known selection and evaluation procedures, one of them is selected and used for further development. Next steps include the definition of relevant criteria for the evaluation of the processes by examining process characteristics regarding their suitability for process evaluation. The focus here lies on characteristics that provide indications of the risk disposition and business relevance of processes. The result of this approach is a scoring model with a criteria catalog consisting of 15 criteria according to which a process is evaluated. The evaluation result is presented both numerically and in a matrix. This enables the comparison of several processes and a derived prioritization of those for a more in-depth risk analysis. The application of this approach will ensure a benefit-oriented allocation of resources in the management of process risks and increased process reliability.
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 process for the production of customized bras is really challenging. Although the need is very clear, the lingerie industry is currently facing a lack of data, knowledge and expertise for the realization of an automated process chain. Different studies and surveys have shown, that the majority of women wear the incorrect bra size. In addition to aesthetic problems, health risks such as headaches, back problems or digestive problems of the wearers can result from this. An important prerequisite for improvements is the basic knowledge about the female breast, both in terms of body measurements and different breast shapes. The current size systematic for bras only defines a bra size by the relation between bust girth and underbust girth and standardized cup forms do not justice to the high variability of the human body. As the bra type shapes the female breast, basic knowledge about the relation of measurements and shapes from the clothed and the unclothed breast is missing.
In the present project, studies are conducted to explore the female breast and to derive new breast-specific body measurements, different breast shapes and deformation knowledge using existing bras.
Furthermore, an innovative process is being developed that leads from 3D scanning to individual and interactive pattern construction, which allows an automatic pattern creation based on individual body measurements and the influence of different material parameters.
In the course of the presentation, the current project status will be shown and the future developments and project steps will be introduced.
Circular economy aims to support reuse and extends the product life cycles through repair, remanufacturing, upgrades and retrofits, as well as closing material cycles through recycling. To successfully manage the necessary transformation processes to circular economy, manufacturing enterprises rely on the competency of their employees. The definition of competency requirements for circular economy-oriented production networks will contribute to the operationalization of circular economy. The International Association of Learning Factories (IALF) statesin its mission the development of learning systems addressing these challenges for training of students and further education of industry employees. To identify the required competencies for circular economy, the major changes of the product life cycle phases have been investigated based on the state of the science and compared to the socio-technical infrastructure and thematic fields of the learning factories considered in this paper. To operationalize the circular economy approach in the product design and production phase in learning factories, an approach for a cross learning factory network (so called "Cross Learning Factory Product Production System (CLFPPS)") has been developed. The proposed CLFPPS represents a network on the design dimensions of learning factories. This approach contributes to the promotion of circular economy in learning factories as it makes use of and combines the focus areas of different learning factories. This enables the CLFPPS to offer a holistic view on the product life cycle in production networks.
Recent advances in artificial intelligence have enabled promising applications in neurosurgery that can enhance patient outcomes and minimize risks. This paper presents a novel system that utilizes AI to aid neurosurgeons in precisely identifying and localizing brain tumors. The system was trained on a dataset of brain MRI scans and utilized deep learning algorithms for segmentation and classification. Evaluation of the system on a separate set of brain MRI scans demonstrated an average Dice similarity coefficient of 0.87. The system was also evaluated through a user experience test involving the Department of Neurosurgery at the University Hospital Ulm, with results showing significant improvements in accuracy, efficiency, and reduced cognitive load and stress levels. Additionally, the system has demonstrated adaptability to various surgical scenarios and provides personalized guidance to users. These findings indicate the potential for AI to enhance the quality of neurosurgical interventions and improve patient outcomes. Future work will explore integrating this system with robotic surgical tools for minimally invasive surgeries.
Especially, if the potential of technical and organizational measures for ergonomic workplace design is limited, exoskeletons can be considered as innovative ergonomic aids to reduce the physical workload of workers. Recent scientific findings from ergonomic analyses with and without exoskeletons are indicating that strain reduction can be achieved, particularly at workplaces with lifting, holding, and carrying processes. Currently, a work system design method is under development incorporating criteria and characteristics for the design of work systems in which a human worker is supported by an exoskeleton. Based on the properties of common passive and active exoskeletons, factors influencing the human on which an exoskeleton can have a positive or negative effect (e.g. additional weight) were derived. The method will be validated by the conceptualization and setup of several work system demonstrators at Werk150, the factory of ESB Business School on campus of Reutlingen University, to prove the positive ergonomic effect on humans and the supporting process to choose the suitable exoskeleton. The developed method and demonstrators enable the user to experience the positive ergonomic effects of exoskeletal support in lifting, holding and carrying processes in logistics and production. The new work system design method will contribute to the fact that employees can pursue their professional activity longer without substantial injuries or can be used more flexibly at different work stations. Also new work concepts, strategies and scenarios are opened up to reduce the risk of occupational accidents and to promote the compatibility of work for employees. A training module is being developed and evaluated with participants from industry and master students to build up competence.
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.
The increasing urban population growth leads to challenges in cities in many aspects: Urbanisation problems such as excessive environmental pollution or increasing urban traffic demand new and innovative solutions. In this context, the concept of smart cities is discussed. An enabling element of the smart city concept is applying information technology (IT) to improve administrative efficiency and quality of life while reducing costs and resource consumption and ensuring greater citizen participation in administrative and urban development issues. While these smart city services are technologically studied and implemented, government officials, citizens or businesses are often unaware of the large variety of smart city service solutions. Therefore, this work deals with developing a smart city services catalogue that documents best practice services to create a platform that brings citizens, city government, and businesses together. Although the concept of IT service catalogues is not new and guidelines and recommendations for the design and development of service catalogues already exist in the corporate context, there is little work on smart city service catalogues. Therefore, approaches from agile software development and pattern research were adapted to develop the smart city service catalogue platform in this work.
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.
Endogenous electrical fields play an important role in various physiological and pathological events. Yet the effects of electrical cues on processes such as wound healing, tumor development or metastasis are still rarely investigated, though it is known that direct current electrical fields can alter cell migration or proliferation in vitro. Several 2D experimental models for studying cell responses to direct current electrical fields have been presented and characterized but suitable experimental models for electrotaxis studies in 3D are rare. Here we present a novel, easy-to-produce, multi-well-based galvanotactic-chamber for the use in 2D and 3D cell experiments for investigations on the influence of electrical fields on tumor cell migration and tumor spheroid growth. Our presented system allows the simultaneous application of electrical field to cells in four chambers, either cultured on the bottom of the culture-plate (2D) or embedded in hydrogel filled channels(3D). The set-up is also suitable for, live-cell-imaging. Validation tests show stable electrical fields and high cell viabilities inside the channel. Tumor spheroids of various diameters can be exposed to direct current electrical fields up to one week.
The focus of the developed maturity model was set on processes. The concept of the widespread CMM and its practices has been transferred to the perioperative domain and the concept of the new maturity model. Additional optimization goals and technological as well as networking-specific aspects enable a process- and object-focused view of the maturity model in order to ensure broad coverage of different subareas. The evaluation showed that the model is applicable to the perioperative field. Adjustments and extensions of the maturity model are future steps to improve the rating and classification of the new maturity model.
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.
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 global demand for individualized products leading to decreasing production batch sizes requires innovative approaches how to organize production and logistics systems in a dynamic manner. Current material flow systems mainly rely on predefined system structures and processes, which result in a huge increase of complexity and effort for system and process changes to realize an optimized production and material provision of individualized products. Autonomous production and logistics entities in combination with intelligent products or logistic load carriers following the vision of the “Internet of Things” offer a promising solution for mastering this complexity based on autonomous, decentralized and target size-optimized decision making and structure formation without the need for predefined processes and central decision-making bodies. Customer orders are going to prioritize themselves and communicate directly with the required production and logistics resources. Bins containing the required materials are going to communicate with the conveyors or workers of the respective intralogistics system organizing and controlling the material flow to the autonomously selected workstation. A current research project is the development of a collaborative tugger train combing the potential of automation and human-robot collaboration in intralogistics. This tugger train is going to be integrated into a self organized intralogistics scenario involving individualized customer orders (low to high batch sizes). To classify the application of self-organization within intralogistics systems, a criteria catalogue has been developed. The application of this criteria catalogue will be demonstrated on the example of a self-organization scenario involving the collaborative tugger train and an intelligent bin system.
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.
Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability to ensure a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. However, as the dissertation’s systematic literature review reveals, the currently available blockchain-based traceability solutions lack the ability to map object-related supply chain events holistically, which involves mapping objects’ creation and deletion, aggregation and disaggregation, transformation, and transaction. Therefore, this dissertation proposes a novel blockchain-based traceability architecture that integrates governance and token concepts to overcome the limitations of existing architectures. While the governance concept manages the supply chain structure on an application level, the token concept includes all functions to conduct object-related supply chain events. For this to be possible, this dissertation’s token concept introduces token ‘blueprints’, which allow clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which are, for example, necessary when mapping assembly or delivery processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. This ultimately leads to end-to-end traceability of tokens and their physical or abstract representatives on the blockchain. For validation purposes, this dissertation implements the architecture’s components and their update and request relationships in code and proves its applicability based on the Ethereum blockchain. Finally, this dissertation provides a scenario-based evaluation based on two industrial case studies from a manufacturing and logistics perspective to validate the architecture’s capabilities when applied in real-world industrial settings. The proposed blockchain-based traceability architecture thus covers all object-related supply chain events derived from the two industrial case studies and therefore proves its general-purpose end-to-end traceability capabilities of object flows.
Today's pattern making methods for industrial purposes are including construction principles, which are based on mathematical formula and sizing charts. As a result, there are two-dimensional flats, which can be converted into a three-dimensional garment. Because of their high linearity, those patterns are incapable of recreating the complexity of the human body, which results in insufficient fit. Subsequent changes of the pattern require a high degree of experience and lead to an inefficient product development process. It is known that draping allows the development of more complex and demanding patterns, which corresponds more to the actual body shape. Therefore, this method is used in custom tailoring and haute couture to achieve perfect garment fit but is also associated with time.
So, there is the act of defiance to improve the fit of garments, to speed up production but maintain a good value for money. Reutlingen University is therefore working on the development of 3D-modelled body shapes for 3D draping, considering different layers of clothing, such as jackets or coats. For this purpose, 3D modelling is used to develop 3D-bodies that correspond to the finished dimensions of the garment. By flattening of the modelled body, it is then possible to obtain an optimal 2D Pattern of the body. The comparison of the conventional method and the developed method is done by 3D simulation.
Finally, the optical fit test is demonstrated by the simulated basic cuts, that a significantly better body wrapping through the newly developed methodology could be achieved. Unlike in the basic cuts, which were achieved by classical design principles have been created, only a few adjustments are necessary to obtain an optimized basic cut. Also, when considering the body distance, it is shown that the newly developed basic patterns provide a more even enclosure of the body.
This paper presents the preliminary results of a setof research projects being developed at the distributed resources laboratory at the University of Reutlingen. The main aim of these projects is to couple distributed ledger technologies (DLTs) with distributed control of microgrids. Firstly, a DLT based solution for a local market platform has been developed. This enables end customers to participate in new local micro-energy-markets by providing them with a distributed, decentralized, transparent and secure Peer to Peer (P2P) payment system. Secondly, this solution has been integrated with an autonomous (agent-based) grid management. The integrated solution of both marked platform as well as agent based control has been implemented and tested in a real microgrid with different distributed components such as PV System, CHP and different kinds of controllable loads. This microgrid is located in the distributed energy resources laboratory at the University of Reutlingen. Thirdly, the resulting solution is being implemented as an easy to customize market solution by AC2SG Software Oy, a Finland based software company, developing solutions for the Indian market. In a next phase, the solution is going to be tested in real environment in off-grids systems in India.
Cloud resources can be dynamically provisioned according to application-specific requirements and are payed on a per-use basis. This gives rise to a new concept for parallel processing: Elastic parallel computations. However, it is still an open research question to which extent parallel applications can benefit from elastic scaling, which requires resource adaptation at runtime and corresponding coordination mechanisms. In this work, we analyze how to address these system-level challenges in the context of developing and operating elastic parallel tree search applications. Based on our findings, we discuss the design and implementation of TASKWORK, a cloud-aware runtime system specifically designed for elastic parallel tree search, which enables the implementation of elastic applications by means of higher-level development frameworks. We show how to implement an elastic parallel branch-and-bound application based on an exemplary development framework and report on our experimental evaluation that also considers several benchmarks for parallel tree search.
Rapidly changing market conditions and global competition are leading to an increasing complexity of logistics systems and require innovative approaches with respect to the organisation and control of these systems. In scientific research, concepts of autonomously controlled logistics systems show a promising approach to meet the increasing requirements for flexible and efficient order processing. In this context, this work aims to introduce a system that is able to adjust order processing dynamically, and optimise intralogistics transportation regarding various generic intralogistics target criteria. The logistics system under consideration consists of various means of transport for autonomous decision-making and fulfilment of transport orders with defined source-sink relationships. The context of this work is set by introducing the Learning Factory Werk 150 with its existing hardware and software infrastructure and its defined target figures to measure the performance of the system. Specifically, the important target figures cost and performance are considered for the transportation system. The core idea of the system’s logic is to solve the problem of order allocation to specific means of transport by linking a Genetic Algorithm with a Multi-Agent System. The implementation of the developed system is described in an application scenario at the learning factory.
There is no denying that organizations, whether domestic or global, whether educational, governmental, or business, are undergoing rapid transformation. However, what is causing it? Prompted by the need to remain relevant and competitive, organizations constantly try to reinvent themselves. Those that do not, according to the laws of economics, will simply serve no purpose and will eventually cease to exist. Regardless of sector or industry, an organization's success pivots around its human talent. Hence, it is crucial to manage it and cultivate certain traits, knowledge, and skills. In today's global economy, organizations are more interconnected than ever before and thus the challenges they face require that employees possess not only expert knowledge, problem-solving, cross-cultural, and cross-functional teaming skills, but also good communications skills and agile thinking.
The purpose of this paper sought to develop a collaborative framework that provides wine bottling facilities, wine cellars and their direct supply chain partner guidelines to facilitate a collaborative partnership – aiming to aid responsive decision making and improve reliability. The framework was developed using a triangulation approach, consisting of an in-depth literature review, 14 semi-structured interviews with industry experts and a theoretical case study. The developed framework was presented to wine bottling facilities and their supply chain stakeholders. Indication are that the proposed wine industry collaborative framework should enhance supply chain collaboration and will contribute towards the guidance and facilitation in developing collaboration platforms to align supply chain operations, while improving bottling responsiveness and meeting demand requirements.
Deutschland, quo vadis?
(2020)
Shutdown in Deutschland im März 2020. Stillstand in Handel und Industrie. Der Börsenwert einer beachtlichen Anzahl von Unternehmen hat sich in kürzester Zeit halbiert. Anleger warfen alles auf den Markt. Und bei der hohen Unsicherheit verloren sämtliche Anlageklassen, zeitweise sogar Gold. Selbst Konzerne wie die Lufthansa werden es ohne Staatshilfe nicht mehr schaffen zu existieren.
Fußball-Weltmeisterschaften sind immer auch Materialschlachten der Ausrüster. Manchmal ist sogar die Rede vom "Krieg der Triktos und Schuhe". Der vorliegende Beitrag zeigt, welcher Sportartikelhersteller bei der WM 2014 in Brasilien und im globalen Kampf um die Vorherrschaft auf die richtigen Mannschaften und Verkaufsstrategien setzt.
This study determines the correlation between industry-specific success patterns of Germany’s engineering industry and the business models applied within. In order to identify this correlation, the following objectives are addressed within the framework of this paper: (1) identification and description of business models used by Germany’s engineering industry; (2) analysis of industry-specific success patterns of Germany’s engineering industry by the usage of Key-Performance-Indicators (KPIs); and (3) determination of correlation between the KPIs and Germany’s engineering industry’s business models’ effectiveness. These objectives are mainly achieved by literature research and expert surveys. The findings highlight the KPIs (overall 41) that are relevant for the respective business models. This enables a better understanding of the interrelationships of the business model, in order to derive relevant conclusions. The paper contributes to the literature as it advances this field of research in Germany, and it is one of the first studies to examine the relationship between business models and industry-specific success patterns with relevant KPIs.
Purpose – This paper aims to determine the affecting factors of the brand authenticity of startups in social media.
Design/methodology/approach – Using a qualitative method based on a grounded theory approach, this research specifies and classifies the affecting factors of brand authenticity of startups in social media through in-depth semi-structured interviews.
Findings – Multiple factors affecting the brand authenticity of startups in social media are determined and categorized as indexical, iconic and existential cues through this research. Connection to heritage and having credible support are determined as indexical cues. Founder intellectuality, brand intellectuality, commitment toward customers and proactive clear and interesting communications are identified as iconic cues. Having self-confidence and self-satisfaction, having intimacy with the brand and a joyful feeling for interactions with the community around the brand are determined as existential cues in this research. This research furthers previous arguments on a multiplicity of brand authenticity by shedding light on the relationship between the different aspects of authenticity and the form that different affecting factors can be organized together. Consumers eventually evaluate a strengthened perception of brand authenticity through existential cues that reflect the cues of other aspects (iconic and indexical) which passed through the goal-based assessment and self-authentication filter.
Research limitations/implications – The research sampling population can be more diversified in terms of sociodemographic attributes. Due to the qualitative methodology of this research, assessment of the findings through quantitative methods can be considered in future research. Practical implications – Using the findings of this research, startup managers can properly build a perception of authenticity in their consumers’ minds by using alternate factors while lacking major indexical cues such as heritage. This research helps startup businesses to design their brand communications better to convey their authenticity to their audiences.
Originality/value – This research determines the factors affecting the authenticity of startup brands in social media. It also defines the process of authenticity perception through different aspects of brand authenticity.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. To extend the so far statistical construction of hybrid development methods, we analyze 829 data points to investigate which context factors influence the choice of methods or practices. Using exploratory factor analysis, we derive five base clusters consisting of up to 10 methods. Logistic regression analysis then reveals which context factors have an influence on the integration of methods from these clusters in the development process. Our results indicate that only a few context factors including project/product size and target application domain significantly influence the choice. This summary refers to the paper “Determining Context Factors for Hybrid Development Methods with Trained Models”. This paper was published in the proceedings of the International Conference on Software and System Process in 2020.
Determination of the gel point of formaldehyde-based wood adhesives by using a multiwave technique
(2023)
Determining the instant of gelation of formaldehyde-based wood adhesives as an assessment parameter for their curing rate is important for optimizing the curing behavior. Due to the stoichiometrically imbalanced networks of formaldehyde-based adhesives, the crossover point of storage G′ and loss modulus G″ cannot unconditionally be assumed as the gel point in oscillatory time sweeps as the material response is frequency-dependent. This study aims to determine the gel point of selected adhesives by the isothermal multiwave oscillatory shear test. A thorough comparison between the gel and the crossover point of G′ and G″ is performed. Rheokinetic analysis showed no significant difference between the activation energies calculated at the gel point determined by a multiwave test and the crossover point obtained by the time sweep test. Hence, for resins with similar curing reactions, a reliable determination of gel point by applying a multiwave test is needed for a comparison of their reactivity.
Determination of accelerometer sensor position for respiration rate detection: initial research
(2022)
Continuous monitoring of a patient's vital signs is essential in many chronic illnesses. The respiratory rate (RR) is one of the vital signs indicating breathing diseases. This article proposes the initial investigation for determining the accelerometric sensor position of a non-invasive and unobtrusive respiratory rate monitoring system. This research aims to determine the sensor position in relation to the patient, which can provide the most accurate values of the mentioned physiological parameter. In order to achieve the result, the particular system setup, including a mechanical sensor holder construction was used. The breathing signals from 5 participants were analyzed corresponding to the relaxed state. The main criterion for selecting a suitable sensor position was each patient's average acceleration amplitude excursion, which corresponds to the respiratory signal. As a result, we provided one more defined important parameter for the considered system, which was not determined before.
A lens-based Raman spectrometer is characterized by studying the optical elements in the optical path and we study the measure of aberration–diffraction effects. This is achieved by measuring the spectral resolution (SR) thus encompassing almost all optical elements of a spectrometer that are mostly responsible for such effects. An equation for SR is used to determine the quality factor Q which measures aberration/diffraction effects occurring in a spectrometer. We show how the quality factor changes with different spectrometer parameters such as grating groove density, the wavelength of excitation, pinhole width, charge-coupled device (CCD) pixel density, etc. This work provides an insight into the quality of a spectrometer and helps to monitor the performance of the spectrometer over a certain period. Commercially available spectrometers or home-built spectrometers are prone to misalignment in optical elements and can benefit from this work that allows maintaining the overall quality of the setup. Performing such experiments over a period helps to minimize the aberration/ diffraction effects occurring as a result of time and maintaining the quality of measurements.
Determinants of customer recovery in retail banking - lessons from a German banking case study
(2023)
Due to the increased willingness of retail banking customers to switch and churn their banking relationships, a question arises: Is it possible to win back lost customers, and if so, is such a possibility even desirable after all economic factors have been considered? To answer these questions, this paper examines selected determinants for the recovery of terminated customer–bank relationships from the perspective of former customers. This study therefore evaluates for the first time, empirically and systematically with reference to a German Sparkasse as a case-study setting, whether lost customers have a sufficient general willingness to return (GWR) a retail banking relationship. From our results, a correlation is shown between the GWR a banking relationship and some specific determinants: seeking variety, attractiveness of alternatives and customer satisfaction with the former business relationship. In addition, we show that a customer’s GWR varies depending on the reason for churn and is surprisingly greater when the customer defected for reasons that lie within the scope of the customer himself. Despite the case-study character, however, our results provide relevant insights for other banks and, in particular, this applies to countries with a comparable banking system.
Omnichannel retailing and sustainability are two important challenges for the fast fashion industry. However, the sustainable behavior of fast fashion consumers in an omnichannel environment has not received much attention from researchers. This paper aims to examine the factors that determine consumers’ willingness to participate in fast fashion brands’ used clothes recycling plans in an omnichannel retail environment. In particular, we examine the impact of individual consumer characteristics (environmental attitudes, consumer satisfaction), organizational arrangements constitutive for omnichannel retailing (channel integration), and their interplay (brand identification, impulsive consumption). A conceptual model was developed based on findings from previous research and tested on data that were collected online from Chinese fast fashion consumers. Findings suggest that consumers’ intentions for clothes recycling are mainly determined by individual factors, such as environmental attitudes and consumer satisfaction. Organizational arrangements (perceived channel integration) showed smaller effects. This study contributes to the literature on omnichannel (clothing) retail, as well as on sustainability in the clothing industry, by elucidating individual and organizational determinants of consumers’ recycling intentions for used clothes in an omnichannel environment. It helps retailers to organize used clothes recycling plans in an omnichannel environment and to motivate consumers to participate in them.
The proposed approach applies current unsupervised clustering approaches in a different dynamic manner. Instead of taking all the data as input and finding clusters among them, the given approach clusters Holter ECG data (longterm electrocardiography data from a holter monitor) on a given interval which enables a dynamic clustering approach (DCA). Therefore advanced clustering techniques based on the well known Dynamic TimeWarping algorithm are used. Having clusters e.g. on a daily basis, clusters can be compared by defining cluster shape properties. Doing this gives a measure for variation in unsupervised cluster shapes and may reveal unknown changes in healthiness. Embedding this approach into wearable devices offers advantages over the current techniques. On the one hand users get feedback if their ECG data characteristic changes unforeseeable over time which makes early detection possible. On the other hand cluster properties like biggest or smallest cluster may help a doctor in making diagnoses or observing several patients. Further, on found clusters known processing techniques like stress detection or arrhythmia classification may be applied.
Uncontrolled movements of laparoscopic instruments can lead to inadvertent injury of adjacent structures. The risk becomes evident when the dissecting instrument is located outside the field of view of the laparoscopic camera. Technical solutions to ensure patient safety are appreciated. The present work evaluated the feasibility of an automated binary classification of laparoscopic image data using Convolutional Neural Networks (CNN) to determine whether the dissecting instrument is located within the laparoscopic image section. A unique record of images was generated from six laparoscopic cholecystectomies in a surgical training environment to configure and train The CNN. By using a temporary version of the neural network, the annotation of the training image files could be automated and accelerated. A combination of oversampling and selective data augmentation was used to enlarge the fully labelled image data set and prevent loss of accuracy due to imbalanced class volumes. Subsequently the same approach was applied to the comprehensive, fully annotated Cholec80 database. The described process led to the generation of extensive and balanced training image data sets. The performance of the CNN-based binary classifiers was evaluated on separate test records from both databases. On our recorded data, an accuracy of 0.88 with regard to the safety-relevant classification was achieved. The subsequent evaluation on the Cholec80 data set yielded an accuracy of 0.84. The presented results demonstrate the feasibility of a binary classification of laparoscopic image data for the detection of adverse events in a surgical training environment using a specifically configured CNN architecture.
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.
We present an approach for segmenting individual cells and lamellipodia in epithelial cell clusters using fully convolutional neural networks. The method will set the basis for measuring cell cluster dynamics and expansion to improve the investigation of collective cell migration phenomena. The fully learning-based front-end avoids classical feature engineering, yet the network architecture needs to be designed carefully. Our network predicts how likely each pixel belongs to one of the classes and, thus, is able to segment the image. Besides characterizing segmentation performance, we discuss how the network will be further employed.
Some widely used optical measurement systems require a scan in wavelength or in one spatial dimension to measure the topography in all three dimensions. Novel hyperspectral sensors based on an extended Bayer pattern have a high potential to solve this issue as they can measure three dimensions in a single shot. This paper presents a detailed examination of a hyperspectral sensor including a description of the measurement setup. The evaluated sensor (Ximea MQ022HG-IM-SM5X5-NIR) offers 25 channels based on Fabry–Pérot filters. The setup illuminates the sensor with discrete wavelengths under a specified angle of incidence. This allows characterization of the spatial and angular response of every channel of each macropixel of the tested sensor on the illumination. The results of the characterization form the basis for a spectral reconstruction of the signal, which is essential to obtain an accurate spectral image. It turned out that irregularities of the signal response for the individual filters are present across the whole sensor.
Hyperspectral imaging opens a wide field of applications. It is a well established technique in agriculture, medicine, mineralogy and many other fields. Most commercial hyperspectral sensors are able to record spectral information along one spatial dimension in a single acquisition. For the second spatial dimension a scan is required. Beside those systems there is a novel technique allowing to sense a two dimensional scene and its spectral information within one shot. This increases the speed of hyperspectral imaging, which is interesting for metrology tasks under rough environmental conditions. In this article we present a detailed characterization of such a snapshot sensor for later use in a snapshot full field chromatic confocal system. The sensor (Ximea MQ022HG-IM-SM5X5-NIR) is based on the so called snapshot mosaic technique, which offers 25 bands mapped to one so called macro pixel. The different bands are realized by a spatially repeating pattern of Fabry-Pèrot flters. Those filters are monolithically fabricated on the camera chip.
The intelligent recycling of plastics waste is a major concern. Because of the widespread use of polyethylene terephtalate, considerable amounts of PET waste are generated that are ideally re-introduced into the material cycle by generating second generation products without loss of materials performance. Chemical recycling methods are often expensive and entail environmentally hazardous by-products. Established mechanical methods generally provide materials of reduced quality, leading to products of lower quality. These drawbacks can be avoided by the development of new recycling methods that provide materials of high quality in every step of the production cycle. In the present work, oligomeric ethylene terephthalate with defined degrees of polymerization and defined molecular weight is produced by melt-mixing PET with different quantities of adipic acid as an alternative pathway of recycling PET with respect to conventional methods, offering ecofriendly and economical aspects. Additionally, block-copolyesters of defined block length are designed from the oligomeric products.
The proliferation of convergence of digital technologies SMACIT (social, mobile, analytics, cloud, and Internet of Things) has created significant threats and opportunities to established companies. Business leaders must rethink their business strategies and develop what we refer to as a digital strategy. Our research shows four keys to successfully defining and executing a digital strategy:
1. zeroing in on a customer engagement or digitized solutions strategy to guide the transformation, 2. building operational excellence, 3. creating a powerful digital services backbone to facilitate rapid innovation and responsiveness, and 4. ensuring ongoing organizational redesign. A list of publications from the research is provided at the end of this document.
The digital economy poses existential threats to — and game-changing opportunities for — companies that were successful in the pre-digital economy. What will distinguish those companies that successfully transform from those that become historical footnotes? This is the question a group of six researchers and consultants from Boston Consulting Group set out to examine. The team conducted in-depth interviews with senior executives at twenty-seven companies in different industries to explore the strategies and organizational initiatives they relied on to seize the opportunities associated with new, readily accessible digital technologies. This paper summarizes findings from this research and offers recommendations to business leaders responsible for digital business success.
The modern industrial corporation encompasses a myriad of different software applications, each of which must work in concert to deliver functionality to end-users. However, the increasingly complex and dynamic nature of competition in today’s product-markets dictates that this software portfolio be continually evolved and adapted, in order to meet new business challenges. This ability – to rapidly update, improve, remove, replace, and reimagine the software applications that underpin a firm’s competitive position – is at the heart of what has been called IT agility. Unfortunately, little work has examined the antecedents of IT agility, with respect to the choices a firm makes when designing its “Software Portfolio Architecture.”
We address this gap in the literature by exploring the relationship between software portfolio architecture and IT agility at the level of the individual applications in the architecture. In particular, we draw from modular systems theory to develop a series of hypotheses about how different types of coupling impact the ability to update, remove or replace the software applications in a firm’s portfolio. We test our hypotheses using longitudinal data from a large financial services firm, comprising over 1,000 applications and over 3,000 dependencies between them. Our methods allow us to disentangle the effects of different types and levels of coupling.
Our analysis reveals that applications with higher levels of coupling cost more to update, are harder to remove, and are harder to replace, than those with lower coupling. The measures of coupling that best explain differences in IT agility include all indirect dependencies between software applications (i.e., they include coupling and dependency relationships that are not easily visible to the system architect). Our results reveal the critical importance of software portfolio design decisions, in developing a portfolio of applications that can evolve and adapt over time.
Sleep is essential to existence, much like air, water, and food, as we spend nearly one-third of our time sleeping. Poor sleep quality or disturbed sleep causes daytime solemnity, which worsens daytime activities' mental and physical qualities and raises the risk of accidents. With advancements in sensor and communication technology, sleep monitoring is moving out of specialized clinics and into our everyday homes. It is possible to extract data from traditional overnight polysomnographic recordings using more basic tools and straightforward techniques. Ballistocardiogram is an unobtrusive, non-invasive, simple, and low-cost technique for measuring cardiorespiratory parameters. In this work, we present a sensor board interface to facilitate the communication between force sensitive resistor sensor and an embedded system to provide a high-performing prototype with an efficient signal-to-noise ratio. We have utilized a multi-physical-layer approach to locate each layer on top of another, yet supporting a low-cost, compact design with easy deployment under the bed frame.
"Designed for digital" offers practical advice on digital transformation, with examples that include Amazon, BNY Mellon, DBS Bank, LEGO, Philips, Schneider Electric, USAA, and many other global organizations. Drawing on five years of research and in-depth case studies, the book is an essential guide for companies that want to disrupt rather than be disrupted in the new digital landscape.
Clinical reading centers provide expertise for consistent, centralized analysis of medical data gathered in a distributed context. Accordingly, appropriate software solutions are required for the involved communication and data management processes. In this work, an analysis of general requirements and essential architectural and software design considerations for reading center information systems is provided. The identified patterns have been applied to the implementation of the reading center platform which is currently operated at the Center of Ophthalmology of the University Hospital of Tübingen.
Durch Design Thinking lassen sich radikale Innovationen schaffen. Es findet jedoch immer in einer bestimmten Unternehmenskultur statt, die wiederum in eine nationale Kultur eingebettet ist. Das hat Auswirkungen auf die Implementierung, da dieses Umfeld förderlich oder hinderlich sein kann. Umgekehrt kann die Unternehmenskultur vom Design Thinking beeinflusst werden.
Design thinking
(2019)
Design Thinking als eigenständige Disziplin gibt es bereits seit den sechziger Jahren, aber erst 2005 wurde die Managementlehre darauf aufmerksam. Seitdem wird das Konzept in der Wirtschaft und an den Hochschulen immer populärer, da sich "thinking like a designer" als erfolgreiche Methode erwiesen hat, um Innovationen anzustoßen und Probleme zu beseitigen. Zu den zahlreichen Anwendungsmöglichkeiten von Design Thinking zählt das Design neuer Produkte und Dienstleistungen, die Prozessentwicklung und -implementierung sowie die Organisationsgestaltung.
Nowadays robust, energy-efficient multisensor microsystems often come with heavily restricted power budgets and the characteristic of remaining in certain states for a longer period of time. During this time frame there is no continuous clock signal required which gives the opportunity to suspend the clock until a new transition is requested. In this paper, we present a new topology for on-demand locally clocked finite state machines. The architecture combines a local adaptive clocking approach with synchronous and asynchronous components forming a quasi synchronous system. Using adaptive and local clocking comes with the advantages of reducing the power consumption while saving design effort when no global clock tree is needed. Combining synchronous and asynchronous components is beneficial compared to previous fully asynchronous approaches concerning the design restrictions. The developed topology is verified by the implementation and simulation of a temperature-ADC sensor system realized in a 180 nm process.
In this study, a novel strategy has been developed for the assembly of polyelectrolyte multilayer (PEM) on CaCO3 templates in acidic pH solutions, where consecutive polyelectrolyte layers (heparin/poly(allylamine hydrochloride) or heparin/chitosan) were deposited on PEM hollow microcapsules established previously on CaCO3 templates. The PEM build-up, hollow capsule characterization and successful encapsulation of fluorescein 5(6)-isothiocyanate (FITC)-Dextran by coprecipitation with CaCO3 are demonstrated. Improvement by the removal of CaCO3 core was achieved while the depositions. In the course of the release profile, high retardation for encapsulated FITC-Dextran was observed. The combined shell capsules system is a significant trait that has potential use in tailoring functional layer-by-layer capsules as intelligent drug delivery vehicles where the preliminary in vitro tests showed the responsiveness on the enzymes.
Heat pumps in combination with a photovoltaic system are a very promising option for the transformation of the energy system. By using such a system for coupling the electricity and heat sectors, buildings can be heated sustainably and with low greenhouse gas emissions. This paper reveals a method for dimensioning a suitable system of heat pump and photovoltaics (PV) for residential buildings in order to achieve a high level of (photovoltaic) PV self-consumption. This is accomplished by utilizing a thermal energy storage (TES) for shifting the operation of the heat pump to times of high PV power production by an intelligent control algorithm, which yields a high portion of PV power directly utilized by the heat pump. In order to cover the existing set of building infrastructure, 4 reference buildings with different years of construction are introduced for both single- and multi-family residential buildings. By this means, older buildings with radiator heating as well as new buildings with floor heating systems are included. The simulations for evaluating the performance of a heat pump/PV system controlled by the novel algorithm for each type of building were carried out in MATLAB-Simulink® 2017a. The results show that 25.3% up to 41.0% of the buildings’ electricity consumption including the heat pump can be covered directly from the PV installation per year. Evidently, the characteristics of the heating system significantly influence the results: new buildings with floor heating and low supply temperatures yield a higher level of PV self-consumption due to a higher efficiency of the heat pump compared to buildings with radiator heating and higher supply temperatures. In addition, the effect of adding a battery to the system was studied for two building types. It will be shown that the degree of PV self-consumption increases in case a battery is present. However, due to the high investment costs of batteries, they do not pay off within a reasonable period.
In this paper we describe the design and development process of an electromagnetic picker for rivets. These rivets are used in a production process of leather or textile design objects like riveted waist belts or purses. The picker is designed such that it replaces conventional mechanical pickers thus avoiding mechanical wear problems and increasing the process quality. The paper illustrates the challenges in the design process of this mechatronic system. The design process was based on both simulation and experiments leading to a prototype that satisfies the requirements.
Additive Manufacturing is increasingly used in the industrial sector as a result of continuous development. In the Production Planning and Control (PPC) system, AM enables an agile response in the area of detailed and process planning, especially for a large number of plants. For this purpose, a concept for a PPC system for AM is presented, which takes into account the requirements for integration into the operational enterprise software system. The technical applicability will be demonstrated by individual implemented sections. The presented solution approach promises a more efficient utilization of the plants and a more elastic use.
The world is becoming increasingly digital. People have become used to learning and interacting with the world around them through technology, accelerated even further by the Covid-19 pandemic. This is especially relevant to the generation currently entering education systems and the workforce. Considering digital aids and methods of learning are important for future learning. The increasing online learning needs open the case for integrating digital learning aspects such as serious gaming within education and training systems. Learning factories fall amongst the education and training systems that can benefit from integration with digital learning extensions. Digital capabilities such as digital twins and models further enable the exploration of integrating digital serious games as an extension of learning factories. Since learning factories are meant for a range of different learning, training, and research purposes, such serious games need to be adaptable across stakeholder perspectives to maximize the value gained from the time and cost invested into such design and development. Research into the development of adaptive serious games for multiple stakeholder perspectives must first determine whether such development can be developed that reaches the objectives set for different included stakeholder perspectives. The purpose of this research is to investigate this at the hand of the practical development of a digital adaptive serious game for stakeholder perspectives.
The design process for a single phase, smart, universal charger for light electric vehicles, is presented. With a step up, power factor correction circuit, followed by a phase shifted, full bridge converter, with synchronous rectification on the secondary side. Due to the resistor-capacitor-diode snubber on the secondary side, the current peak at the start of power transfer, leads to false triggering during light load control with peak current mode control. The solution developed for light loads, is to change from peak current control to voltage control. This is achieved by limiting the maximum phase shift, instead of changing the reference value. For the power factor correction stage, measured and calculated efficiencies are compared as a function of the output power. The voltage and current waveforms are shown for the power factor correction circuit, and for the phase shifted bridge, the measured current waveform is compared with simulation.
Normal breathing during sleep is essential for people’s health and well-being. Therefore, it is crucial to diagnose apnoea events at an early stage and apply appropriate therapy. Detection of sleep apnoea is a central goal of the system design described in this article. To develop a correctly functioning system, it is first necessary to define the requirements outlined in this manuscript clearly. Furthermore, the selection of appropriate technology for the measurement of respiration is of great importance. Therefore, after performing initial literature research, we have analysed in detail three different methods and made a selection of a proper one according to determined requirements. After considering all the advantages and disadvantages of the three approaches, we decided to use the impedance measurement-based one. As a next step, an initial conceptual design of the algorithm for detecting apnoea events was created. As a result, we developed an activity diagram on which the main system components and data flows are visually represented.
Usually battery chargers have two stages and DC charging current is considered to by necessary for a proper charging. To decrease the charger volume, a single stage LLC battery charger is investigated in this paper. PFC stage is eliminated, therefore no bulky capacitor is necessary any more, and battery is charged with a sinusoidal-like charging current. However, previous studies show that such a pulsating charging current has only minimal impact on battery life and efficiency. Design considerations of the resonant tank and optimal transformer design are presented. A 360W single stage LLC converter prototype for e-bike charger achieves a power factor of 0.98, efficiency of 0.93 and power density of 1,8kW/dm³.
In this work design rules for a novel brushless excitation system for externally excited synchronous machines are discussed. The concept replaces slip rings with a fullbridge active rectifier and a controller mounted on the rotor. An AC signal induced from the stator is used to charge the rotor DC link. The DC current for the rotor excitation is provided from this DC link source. Finite element analysis of an existing machine is used to analyze the practicability of the excitation system.
This paper presents the design and simulation processes of an Equiangular Spiral Antenna for the extremely high frequencies between 65 GHz and 170 GHz. A new approach for the analysis of the antenna’s electrical parameters is described. This approach is based on formalism proposed by Rumsey to determine the EM field produced by an equiangular spiral antenna. Analytical expressions of the electrical parameters such as the gain or the directivity are then calculated using well sustained mathematical approximations. The comparison of obtained results with those from numerical integration methods shows a good agreement.
An operation room is a stressful work environment. Nevertheless, all involved persons have to work safely as there is no space for making mistakes. To ensure a high level of concentration and seamless interaction, all involved persons have to know their own tasks and tasks of their colleagues. The entire team must work synchronously at all times. However, the operation room (OR) is a noisy environment and the actors have to set their focus on their work. To optimize the overall workflow, a task manager supporting the team was developed. Each actor is equipped with a client terminal showing a summary of their own tasks. Moreover, a big screen displays all tasks of all actors. The architecture is a distributed system based on a communication framework that supports the interaction of all clients with the task manager. A prototype of the task manager and several clients have been developed and implemented. The system represents a proof-of-concept for further development. This paper describes the concept of the task manager.
An operating room is a stressful work environment. Nevertheless, all involved persons have to work safely as there is no space for mistakes. To ensure a high level of concentration and seamless interaction, all involved persons have to know their own tasks and the tasks of their colleagues. The entire team must work synchronously at all times. To optimize the overall workflow, a task manager supporting the team was developed. In parallel, a common conceptual design of a business process visualization was developed, which makes all relevant information accessible in real-time during a surgery. In this context an overview of all processes in the operating room was created and different concepts for the graphical representation of these user-dependent processes were developed. This paper describes the concept of the task manager as well as the general concept in the field of surgery.
This paper presents a permanent magnet tubular linear generator system for powering passive sensors using vertical vibration harvesting energy. The system consists of a permanent magnet tubular linear vibration generator and electric circuits. By using the design of mechanical resonant movers, the generator is capable of converting low frequencies small amplitude vertical vibration energy into more regular sinusoidal electrical energy. The distribution of the magnetic field and electromotive force are calculated by Finite Element Analysis. The characteristics of the linear vibration generator system are observed. The experimental results show the generator can produce about 0.4W~1.6W electrical power when the vibration source's amplitude is fixed on 2mm and the frequencies are between 13Hz and 22Hz.
This paper presents a description model for smart, connected devices used in a manufacturing context. Similar to the wide spread adoption of smart products for personal and private usage, recent developments lead to a plethora of devices offering a variety of features and capabilities. Manufacturing companies undergoing digital transformation demand guidance with respect to the systematic introduction of smart, connected devices. The introduction of smart connected devices constitutes a strategic decision cost due to the high future committed cost after introduction and maintaining a smart device fleet by a vendor. This paper aims to support the introduction efforts by classifying the devices and thus helping companies identify their specific requirements for smart, connected devices before initiating widespread procurement. By mapping the features of these devices based on various attributes, allows the clustering of smart, connected devices including a requirement list for their implementation on the shopfloor. Four individual commercially available smart connected devices were analyzed using the description model.
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 aim of this work was to investigate the mean fill weight control of a continuous capsule-filling process, whether it is possible to derive controller settings from an appendant process model. To that end, a system composed out of fully automated capsule filler and an online gravimetric scale was used to control the filled weight. This setup allows to examine challenges associated with continuous manufacturing processes, such as variations in the amount of active pharmaceutical ingredient (API) in the mixture due to fluctuations of the feeders or due to altered excipient batch qualities. Two types of controllers were investigated: a feedback control and a combination of feedback and feedforward control. Although both of those are common in the industry, determining the optimal parameter settings remains an issue. In this study, we developed a method to derive the control parameters based on process models in order to obtain optimal control for each filled product. Determined via rapid automated process development (RAPD), this method is an effective and fast way of determining control parameters. The method allowed us to optimize the weight control for three pharmaceutical excipients. By conducting experiments, we verified the feasibility of the proposed method and studied the dynamics of the controlled system. Our work provides important basic data on how capsule filler can be implemented into continuous manufacturing systems.
Die vierte industrielle Revolution stellt neue Anforderungen an Unternehmen und insbesondere an KMU. Das verfügbare Know-how bei der Implementierung von Industrie 4.0-Ansätzen stellt für viele KMU eine Herausforderung dar. Derzeit existieren in der Literatur verschiedene Wege zur Erstellung einer auf das Unternehmen angepassten Industrie 4.0 Roadmap. Eine Ausrichtung auf die Belange von KMU fehlt jedoch gänzlich. Mit dieser Arbeit werden verschiedene Ansätze zur Erstellung einer Industrie 4.0-Roadmap zusammengefasst und anschließend untersucht, worauf KMU mit ihren spezifischen Eigenschaften besonders ihren Fokus legen sollten.
Im März dieses Jahres fand der Steuerprozess gegen Uli Hoeneß statt, der mit einer Verurteilung des damaligen Präsidenten und Aufsichtsratsvorsitzenden des FC Bayern München endete. Vor, während und nach dem mit Spannung erwarteten Prozess stellte das Deutsche Institut für Sportmarketing (DISM) in Kooperation mit dem Felddienstleister Norstat Germany über 7.000 Probanden in Deutschland im Rahmen einer Online-Befragung verschiedene Fragen zum Sportmarketing in Verbindung mit der Steueraffäre. Auf die zentralen Ergebnisse dieser Befragung wird im vorliegenden Forschungsreport eingegangen.
Ein Forscherteam der Pädagogischen Hochschule Freigburg und der Hochschule Reutlingen mit Expertisen in Kommunikationsdesign und einer ästhetisch-kulturellen Fachdidaktik der Grundschulpädagogik erforscht, inwieweit sich der iterative Prozess und Prinzipien des Design Thinking eignen, Kreativität, Problemlösekompetenz und kollaboratives Arbeiten von Grundschulkindern zu födern. Grundlage der Überlegungen sind die prozessorientierten Kompetenzen der Fächer Kunst/Werken und Sachunterricht gemäß dem aktuellen Bildungsplan in Baden-Württemberg. Nach Vortstudien mit Lehrpersonen und Ausbildungslehrkräften wurde eine Unterrichtseinheit konzipiert, in welcher Kinder der dritten Klassenstufe mittels Design Thinking den perfekten Leseort umsetzen sollten.
Der relative Vorteil von Heim- gegenüber Auswärtsteams im Sport - der sogenannte Heimvorteil - ist in mehreren Studien belegt (z.B. Nevill et al., 2002; Jamieson, 2010). Als theoretisch dem Heimvorteil zugrundeliegende Faktoren gelten u.a. folgende: die Zuschauer (durch ihre motivierende Wirkung auf Spieler oder beeinflussende Wirkung auf Schiedsrichter), Reisefaktoren (z.B. die Entfernung bzw. Dauer der Reise und die damit einhergehende Erschöpfung der Spieler) und die Vertrautheit der Heimmannschaft mit der Umgebung (z.B. die Vertrautheit mit dem Stadion und dem Spieluntergrund) (Courneya & Carron, 1992; Nevill et al., 2002). Durch die während der COVID-19-Pandemie stattfindenden Spiele ohne Zuschauer (Geisterspiele) lässt sich erstmals durch ein natürliches Experiment der Einfluss von Zuschauern auf den Heimvorteil betrachten. Ein Überblick über die Studien, die den Heimvorteil in verschiedenen Fußballligen während der pandemiebedingten Geisterspiele untersuchen, findet sich in Leitner et al. (2022).
Der Halo-Effekt im Fußball
(2019)
Der Halo-Effekt ist eine aus der Sozialpsychologie bekannte kognitive Verzerrung. Er tritt dann auf, wenn ein globaler Eindruck oder eine Information über ein hervorstechendes Merkmal die Beurteilung anderer Eigenschaften prägt. Im vorliegenden Beitrag soll der Frage nachgegangen werden: Gibt es einen Halo-Effekt im Fußball? Überstrahlt der sportliche Erfolg bzw. Misserfolg eines Vereins andere sportliche Aspekte? Verzerrt der sportliche Erfolg bzw. Misserfolg die Wahrnehmung der Fans hinsichtlich nicht-sportlicher Aspekte?
Der Halo-Effekt im Fußball
(2019)
Der Halo-Effekt ist eine aus der Sozialpsychologie bekannte kognitive Verzerrung. Ein Halo-Effekt tritt dann auf, wenn ein globaler Eindruck oder eine Information über ein hervorstechendes Merkmal die Beurteilung anderer Eigenschaften prägt. Im vorliegenden Beitrag wird der Frage nachgegangen: Gibt es einen Halo-Effekt im Fußball? Überstrahlt der sportliche Erfolg bzw. Misserfolg die Wahrnehmung der Fans womöglich sogar hinsichtlich nicht-sportlicher Aspekte? Der Beitrag gibt den aktuellen Stand zur Halo-Forschung wider und präsentiert die Ergebnisse einer empirischen Untersuchung, in deren Rahmen Fans von Vereinen aus der deutschen Fußball-Bundesliga befragt werden.
Der Girlboss Mythos : die gesellschaftlichen und ökonomischen Perspektiven der Gender-Debatte
(2019)
Faktisch sind Frauen heute gleichberechtigt. Sie haben die gleichen Chancen, Rechte und Möglichkeiten wie Männer. Dennoch weisen maßgebliche Studien darauf hin, dass die Anzahl von Frauen auf allen Führungsebenen stagniert oder nur im Schneckentempo wächst. In der medialen Diskussion rund um das Thema Frauen im Management ist die Welt auf den ersten Blick in zwei Lager geteilt. Ein Lager stellt ernüchtert fest, dass Frauen selbst Schuld sind an ihrer Situation. Oft werden hier gerade erfolgreiche Frauen zitiert, die ihren Geschlechtsgenossinnen den nötigen Erfolgswillen oder die Opferbereitschaft absprechen. Das andere Lager scheint die Sachlage genau entgegengesetzt zu beurteilen. Überall gut ausgebildete, hochmotivierte Frauen, die an Glasdecken stoßen oder denen von der Gesellschaft im Allgemeinen und Männern im Besonderen die Türen versperrt werden. Dieses Buch trägt zu einer wissenschaftlich nüchternen Diskussion bei, um die aktuelle gesellschaftspolitische Situation differenzierter und abseits von abgegriffenen Dogmen zu betrachten.
Am 29. Mai 2015 wurde Sepp Blatter trotz immenser öffentlicher Kritik im Vorfeld der Wahl vom Kongress als Präsident der FIFA erneut gewählt. Nur vier Tage nach seiner Wiederwahl ist Blatter am 2. Juni 2015 überraschend zurückgetreten. Ist das eine Reaktion auf die aktuellen Untersuchungen des FBI? Der vorliegende Beitrtag zeigt auf, welche Rolle die FIFA-Sponsoren in dieser Entwicklung einnehmen.
Im März 2014 fand der Steuerprozess gegen Uli Hoeneß statt, der mit einer Verurteilung des damaligen Präsidenten und Aufsichtsratsvorsitzenden des FC Bayern München endete. Im Vorfeld des mit Spannung erwarteten Prozesses stellte das Deutsche Institut für Sportmarketing (DISM) in Kooperation mit Felddienstleister Norstat Germany 1.014 internetrepräsentativen Personen in Deutschland im Rahmen einer Online-Befragung verschiedene Fragen aus Sicht des Sportmarketing. Auf die zentralen Ergebnisse dieser Befragung wird im vorliegenden Beitrag eingegangen.
Mittlerweile ist der Einsatz von technischen Hilfsmitteln zu Analysezwecken im Sport fester Bestandteil im Trainingsalltag von Trainern und Athleten. In nahezu jeder Sportart werden Videoaufzeichnungen genutzt, um die Bewegungsausführung zu dokumentieren und zu analysieren. Allerdings reichen Aufnahmen von einem statischen Standort oftmals nicht mehr aus. An dieser Stelle kann Virtual Reality (VR) eine Lösung dieses Problems bieten. Durch VR kann der aufgezeichneten Szene eine weitere Ebene hinzugefügt und die Bewegungsabläufe neu und detaillierter bewertet werden. Um Bewegungen in einer virtuellen Umgebung abzubilden, müssen diese mittels Motion Capturing (MoCap) aufgezeichnet werden. Ziel dieser Arbeit ist es, herauszufinden, ob das MoCap System Perception Neuron in der Lage ist, Bewegungen in hoher Geschwindigkeit zu erfassen.
Diese Ausarbeitung befasst sich mit der Fragestellung, inwiefern interaktive Systeme innerhalb eines historischen Ausstellungskontextes herangezogen werden können, um die methodische Vermittlung von Informationen zu fördern und zu unterstützen. Als Anwendungsfall wird hierbei auf das Schloss Aulendorf zurückgegriffen.
Das Ziel der vorliegenden Studie war es, den Zusammenhang zwischen der Implementierung von CRM-Prozessen und der Kundenzufriedenheit zu analysieren. Unsere Untersuchung ist einigen grundsätzlichen Beschränkunfen unterworfen. CRM ist immer noch ein relativ junges Forschungsgebiet, dessen Prozesse sich im Zeitablauf mit großer Wahrscheinlichkeit noch weiterentwickeln werden. Manche Praktiken werden als ineffektiv identifiziert und verworfen werden; andere existierende Prozesse werden eine Verbesserung erfahren. Es ist zudem zu erwarten, dass neue Prozesse und Aktivitäten entwickelt und eingeführt werden. Als Folge dieser Entwicklungen ist es möglich, dass die hier berichtete Wirkung auf die Kundenzufriedenheit durch die Implementierung von CRM-Prozessen sich im Laufe der Zeit ebenfalls ändern wird. Ein interessanter Forschungsansatz wäre daher die Beobachtung dieser Evolution im Zeitablauf.
Darüber hinaus muss in dieser Studie beachtet werden, dass die Kundenzufriedenzeit lediglich ein vorökonomisches Ziel des CRM ist. Einzelne Investitionen in eine bestehende Geschäftsbeziehung müssen anhand der Wertigkeit des Kunden für das Unvernehmen vorgenommen werden.Bestehen ferner keine Alternativen zum bisherigen Anbieter, so ist es ökonomisch nicht sinnvoll, Ressourcen zur Steigerung der Kundenzufriedenheit einzusetzen, da ein Wechsel des Anbieters unwahrscheinlich ist.
Schließlich nutzten wir für die vorliegende Studie Skalen zur Einschätzung der Einstellungen der Kunden durch die Unternehmen. Da dieses Vorgehen möglichst genaue Beurteilungen erfordert, kann es sein, dass die Daten gewisse Verzerrungen aufweisen. Zukünftige Forschungsansätze könnten die Studie durch eine ergänzende Einschätzung der Kunden zur Kreuzvalidierung sinnvoll erweitern.
Eine wichtige Informationsgrundlage für strategische Entscheidungen im Sportmarketing bildet das Markenimage, da es die Perspektive der Anspruchsgruppen auf die Marke widerspiegelt. Die Analyse des Markenimages ist jedoch methodisch komplex, weshalb dafür der Einsatz Künstlicher Neuronaler Netze eingehender untersucht wird. Denn dieses Verfahren der Künstlichen Intelligenz ermöglicht die Modellierung vielschichtiger und nichtlinearer Wirkungsbeziehungen. Der konzeptionelle Ansatz wird am empirischen Praxisbeispiel des Sportartikelherstellers adidas veranschaulicht, indem ein mehrschichtiges Künstliches Neuronales Netz zwischen den Bewertungen spezifischer Markenattribute und der Gesamtmarke modelliert wird. Mithilfe einer Analyse der Verbindungsgewichte des Netzes wird der Variableneinfluss verschiedener Markenattribute gemessen, woraus sich konkrete Implikationen für die Sportmarketingpraxis ergeben.
Scroll-activated animations eröffnen Webentwicklern neue Möglichkeiten der Interaktion und Präsentation von Inhalten. Durch die Animation von Bildern, Texten und weiteren Elementen einer Website soll der Nutzer durch die neue Darstellungsart positiv überrascht werden. Ziel ist es, dem Nutzer die Inhalte interessanter und möglichst gezielt zu vermitteln. Es stellt sich jedoch die Frage, ob die dadurch gesteigerte User Experience zulasten der Usability erfolgt. Unter Umständen führen die Animationen beim Nutzer zwar zu einem Aha-Effekt, setzen jedoch die Benutzerfreundlichkeit herab. Aus diesem Grund geht die Arbeit auf den Aspekt der Usability und User Experience dieser Animationen ein und untersucht den tatsächlichen Mehrwert des Einsatzes von Scroll-Animationen mithilfe von Webanalysetools. Durch den Vergleich mit einer inhaltlich identischen Seite sollen die oben genannten Effekte untersucht werden. Zusätzlich sollen die Ergebnisse nach Gerätetypen aufgeschlüsselt werden, um mögliche Unterschiede aufzudecken.
In diesem Beitrag wird der Einfluss von Zuschauern nach den pandemiebedingten Geisterspielen auf den Heimvorteil in der ersten Fußball-Bundesliga analysiert. Für die empirische Untersuchung werden die fünf Spielzeiten 2017/18 bis 2021/22 betrachtet. Während in der Geisterspielphase in der Saison 2019/20 der Heimvorteil vollständig verschwindet, steigt der Heimvorteil in der zweiten Geisterspielphase in der Saison 2020/21 mit der Zeit wieder auf vorpandemisches Niveau an. In der Saison 2021/22 ist nach einer kurzen Phase mit eingeschränkten Zuschauerkapazitäten ein signifikant größerer Heimvorteil als in der Zeit vor der Pandemie zu beobachten. Der überdurchschnittlich positive Effekt der Zuschauer in dieser letzten Phase verschwindet mit der Zeit trotz steigender Zuschauerzahlen. Der Einfluss von Fans auf den Heimvorteil ist insgesamt insbesondere auf psychologische Effekte auf die Spieler der Heimmannschaften zurückzuführen.
Diese Studie untersucht den kurzfristigen Einfluss der Tagespflege auf die kindliche Entwicklung im Vergleich zur Betreuung in der Kita. Internationale Studien deuten darauf hin, dass der Besuch einer Tagespflege im Vergleich zur Kita eher negative Auswirkungen auf Kinder hat. Mithilfe der Neugeborenen-Kohorte des NEPS können wir evaluieren, ob dies auch im deutschen Kontext gilt. Wir nutzen zwei verschiedene methodische Ansätze, um den Effekt der Tagespflege zu schätzen. Unsere Ergebnisse zeigen, dass die Tagespflege für die Mehrzahl der untersuchten Entwicklungsindikatoren keinen statistisch signifikant schlechteren Einfluss auf die kindliche Entwicklung hat, außer im Bereich der Habituation.
Es wird erwartet, dass die neuen Technologien rund um die Digitalisierung von Gesellschaft und Geschäftswelt zu revolutionären Veränderungen führen werden. Im Zusammenhang mit produzierenden Unternehmen ist hier von einer möglichen vierten Revolution unter dem Stichwort "Industrie 4.0" die Rede. Eine Frage, die damit aber unmittelbar einhergeht, ist, ob sich infolge dieser Revolution auch Organisations- und Produktionsstrukturen von Unternehmen nicht ebenfalls revolutionär ändern müssen.
Dieser Beitrag geht dieser Frage nach, indem er den momentanen Stand der wissenschaftlichen Diskussion zusammenfasst und anschließend bewertet.
Der Digitale Zwilling ist ein Technologie-Trendthema mit großen Potenzialen in einer Vielzahl von Anwendungsbereichen – insbesondere für produzierende Unternehmen. Eine Studie des Reutlinger Zentrums Industrie 4.0 beschäftigt sich mit heutigen und zukünftigen Anwendungsmöglichkeiten von Digitalen Zwillingen und gibt Impulse für eine schrittweise Implementierung im Unternehmen.
Zur Ermittlung des Quo Vadis bewerten die Teilnehmer mit „trifft zu“ bis „trifft nicht zu“, inwieweit sie die neun Trends als Kerntrend der Digitalisierung ansehen. Auf Basis der Antworten werden ein bis vier Punkte vergeben und ein Ranking erstellt. Die Auswertung ergibt, dass Vernetzte Produktion, gefolgt von Big-Data-Analytics und digitale Kommunikation als wichtigste Kerntrends gesehen werden. Cloud Computing, Internet der Dinge und Digitale Geschäftsmodelle werden dagegen weniger als Kerntrends angenommen.
Um sich den neuen Herausforderungen zu stellen und eine wettbewerbsstarke Position im Zeitalter der Digitalisierung zu schaffen, wird vermehr in Digitalisierungsvorhaben investiert und digitale Geschäftsmodelle werden entwickelt. Was brauch ein mittelständisches Unternehemen, um sich erfolgreich in das digitale Zeitalter aufzumachen?
Der Career Booster
(2022)
Das berufsbegleitende International MBA Program der ESB Business School in Reutlingen hat einen sehr guten Ruf. Der Schwerpunkt liegt neben Strategie und Business Development auf Digitalisierung, Marketing, Leadership und Nachhaltigkeit. Es wird immer wieder den Anforderungen der Wirtschaft angepasst, meint Studiendekan Prof. Gerd Nufer.
In diesem Artikel wird ein neu entwickeltes Werkzeug zur Dimensionierung von Bonddrähten im ASIC-Entwurf vorgestellt. Die Berücksichtigung aller Einflussfaktoren erlaubt eine gegenüber Handrechnungen optimierte Auslegung der Bondanordnung. Dies ermöglicht zum einen die Absicherung gegen Degradationseffekte bis hin zum Durchbrennen und garantiert so die Zuverlässigkeit über die gesamte Lebensdauer. Zum anderen wird eine aus Zuverlässigkeitserwägungen resultierende Überdimensionierung vermieden.
Das Werkzeug erlaubt die Kalkulation aller für die Auslegung von Bonddrähten relevanten Parameter. Je nach Kontext der Aufgabenstellung lassen sich die Stromtragfähigkeit für Dauerstrom oder Pulsstrombelastung, kritische Temperaturen oder die maximale Bonddrahtlänge als Ausgabegrößen berechnen. Durch diese Flexibilität und die benutzerfreundliche Integration in eine industrielle Entwicklungsumgebung ist der „Bond-Rechner“ im gesamten Entwurfsverlauf einsetzbar und leistet wertvolle Hilfestellung von ersten Abschätzungen in frühen Entwurfsphasen bis hin zur abschließenden Verifikation.
Plasma polymerization is used for the modification and control of surface properties of a highly transparent, thermoplastic elastomeric silicone copolymer, GENIOMER® 80 (G80). PEG-like diglyme plasma polymer films were deposited with ether retentions varying between 20% and 70% as measured by X-ray photoelectron spectroscopy analysis which did not affect the transparency of the substrate. Films with ether retentions of greater than 70% inhibit protein binding (bovine serum albumin and fibrinogen) and cell proliferation. A short oxygen plasma pretreatment enhances the adhesion and stability of the film as shown by protein binding and cell adhesion experiments. The transparency of the material and the stability of the coating makes this material a versatile bulk material for technical (e.g., lab-on-a-chip) and biomedical (e.g., intraocular lens) applications. The G80/plasma polymer composite is stable against vigorous washing and storage over 5 months and, therefore, offers an attractive alternative to poly(dimethylsiloxane).
Planungsprozesse sind komplex und aufwendig. Damit Unternehmen ihre operative Planung schneller und effizienter erstellen können, sollten sie sich an 14 erfolgskritischen Faktoren orientieren. So stellen sie sicher, dass die Planung die strategischen Ziele widerspiegelt, der Aufwand im Rahmen bleibt und die Datenqualität zieladäquat ist.
There have been substantial research efforts for algorithms to improve continuous and automated assessment of various health-related questions in recent years. This paper addresses the deployment gap between those improving algorithms and their usability in care and mobile health applications. In practice, most algorithms require significant and founded technical knowledge to be deployed at home or support healthcare professionals. Therefore, the digital participation of persons in need of health care professionals lacks a usable interface to use the current technological advances. In this paper, we propose applying algorithms taken from research as web-based microservices following the common approach of a RESTful service to bridge the gap and make algorithms accessible to caregivers and patients without technical knowledge and extended hardware capabilities. We address implementation details, interpretation and realization of guidelines, and privacy concerns using our self-implemented example. Also, we address further usability guidelines and our approach to those.