Refine
Year of publication
Document Type
- Article (144)
- Monograph/Edited Volume (26)
- Part of a Book (21)
- Conference Proceeding (20)
- Postprint (15)
- Other (7)
- Contribution to a Periodical (5)
- Doctoral Thesis (1)
- Review (1)
Is part of the Bibliography
- yes (240) (remove)
Keywords
- knowledge management (7)
- Industrie 4.0 (5)
- Industry 4.0 (5)
- deep reinforcement learning (5)
- production control (5)
- ERP (4)
- Enterprise-Resource-Planning (4)
- digital learning (4)
- machine learning (4)
- systematic literature review (4)
- COVID-19 (3)
- CPPS (3)
- CPS (3)
- Digitale Plattformen (3)
- JSP (3)
- KMU (3)
- Marktübersicht (3)
- adaptability (3)
- business processes (3)
- change management (3)
- evaluation (3)
- industry 4.0 (3)
- intentional forgetting (3)
- knowledge transfer (3)
- learning factories (3)
- learning factory (3)
- modular production (3)
- multi-agent system (3)
- neural networks (3)
- situational strength (3)
- vocational training (3)
- Digitalisierung (2)
- ERP system (2)
- ERP-/PPS-Systeme (2)
- ERP-System (2)
- Enterprise Resource Planning (2)
- Geschäftsmodell (2)
- Hinweisreize (2)
- Internet of Things (2)
- Internet of things (2)
- Lernfabrik (2)
- Marktuntersuchung (2)
- Maschinen- und Anlagenbau (2)
- PPS (2)
- Refabrikation (2)
- Regionale Ansätze (2)
- Remanufacturing (2)
- Simulation (2)
- Strategie (2)
- TAM (2)
- Wandlungsfähigkeit (2)
- action problems (2)
- assessment (2)
- augmented reality (2)
- deep learning (2)
- discipline differences (2)
- e-learning (2)
- job shop scheduling (2)
- knowledge transfers (2)
- market research (2)
- method comparision (2)
- multi-actor routines (2)
- multi-objective optimisation (2)
- organizational memory (2)
- process modelling (2)
- product generation engineering (2)
- production planning (2)
- production planning and control (2)
- serious game (2)
- social network analysis (2)
- tacit knowledge (2)
- taxonomy (2)
- technology acceptance (2)
- technology-mediated teaching (2)
- university teaching (2)
- unlearning (2)
- 4th industrial revolution (1)
- AI and business informatics (1)
- AI-based decision support system (1)
- Adaptation (1)
- Adaptivität (1)
- Altsyteme (1)
- Analytics (1)
- Anpassung (1)
- Anpassungsfähigkeit (1)
- Anwendungssystem (1)
- Anwendungssystemarchitekturen (1)
- Anwendungszentrum Industrie 4.0 (1)
- Architecture concepts (1)
- Assistenzsysteme (1)
- Audit (1)
- Auftragsabwicklung (1)
- Auftragsabwicklungssysteme (1)
- Augmented reality (1)
- Auswahlvorgehen (1)
- Automatisierung (1)
- Automobilzulieferer (1)
- Behavior (1)
- Bewertung (1)
- Blockchain (1)
- CO₂-Fußabdruck (1)
- Case Study (1)
- Change (1)
- Community (1)
- Coring (1)
- Cross-System (1)
- Crowdsourcing (1)
- Customer Relationship Management (1)
- Customization (1)
- Cyber-phyiscal system (1)
- Cyber-physical systems (1)
- Decentral Decision Making (1)
- Decentralized production control (1)
- Degree of autonomy (1)
- Digital Learning Factory (1)
- Digital Marketplaces (1)
- Digital Platforms (1)
- Digitalisierung von Produktionsprozessen (1)
- Digitization (1)
- Diskussion (1)
- ERP-/PPS-systems (1)
- ERP-/PPSsystems (1)
- ERP-Auswahl (1)
- ERP-Systeme (1)
- Enterprise Resource Planning (ERP) System (1)
- Enterprise System (1)
- Fabriksoftware (1)
- Factory operating system (1)
- Functions (1)
- Funktionsumfang (1)
- GHG Protocol (1)
- Generalized knowledge constructin axiom (1)
- Geschäftsmodelle (1)
- ISO 14067 (1)
- IT assessment (1)
- IT-Assessment (1)
- Industrial Analytics (1)
- Industrial IoT Competences (1)
- Industrieunternehmen (1)
- Informationssystemarchitektur (1)
- Intentional forgetting (1)
- Invidiuallösungen (1)
- KI (1)
- KI-ERP-Indikator (1)
- KVP (1)
- Kaizen (1)
- Klassifikationsschema (1)
- Kompetenzentwicklung (1)
- Konfigurator <Softwaresystem> (1)
- Konsens-Algorithmen (1)
- Kundenmanagement (1)
- Künstliche Intelligenz (1)
- Learning Factory (1)
- Lehr-Lernsituationen (1)
- Lernszenario (1)
- Literature Review (1)
- MES (1)
- Market Research (1)
- Marktanalyse (1)
- Meta-model (1)
- Mobile IIoT-Technologie (1)
- Mobile Software Ecosystems (1)
- Modellfabrik (1)
- Modification (1)
- Nachhaltigkeit (1)
- Open innovation (1)
- PAS 2050 (1)
- Portal (1)
- Problems (1)
- Process Mining (1)
- Process modeling (1)
- Production (1)
- Production system (1)
- Produktions-Routine (1)
- Produktkonfiguratoren (1)
- Professional Services Unternehmen (1)
- Projektmanagement (1)
- Prozessintegration (1)
- Prozessmanagement (1)
- Prozesswissen (1)
- Qualität (1)
- RFID (1)
- RPA (1)
- Regelkreismechanismus (1)
- Research Agenda (1)
- Retrieval cues (1)
- Roadmap (1)
- Robotic Process Automation (1)
- SECI-model (1)
- SMEs (1)
- Simulation process building (1)
- Spielifizierung (1)
- Student Training (1)
- Subject-oriented learning (1)
- Suchmaschine (1)
- Systematisches Vorgehen (1)
- Systemauswahl (1)
- Tailoring (1)
- Task realization strategies (1)
- Three-tier Architecture (1)
- Turbulenz (1)
- Unternehmen (1)
- Unternehmensberatung (1)
- Use cases Morphologic box (1)
- Variantenmanagement (1)
- Verbesserungen (1)
- Verbesserungsprozess (1)
- Verhalten (1)
- Veränderung (1)
- Vocational Training (1)
- Weiterbildung (1)
- Willentliches Vergessen (1)
- Wirtschaftsinformatik (1)
- Wissensmanagement (1)
- Zentrum Industrie 4.0 (1)
- adaptable software systems (1)
- adaptive performance (1)
- advances in teaching and learning technologies (1)
- age-appropriate competence development (1)
- age-appropriate vocational training (1)
- application center Industrie 4.0 (1)
- application system architectures (1)
- artificial intelligence (1)
- assistance systems (1)
- automation (1)
- behavioral patterns (1)
- benefits (1)
- betriebliche Lernprozesse (1)
- betriebliche Weiterbildung (1)
- betriebliche Weiterbildungspraxis (1)
- big data analytics (1)
- business application (1)
- business model (1)
- business models (1)
- business process improvement (1)
- business process management (1)
- business process modeling (1)
- business process optimization (1)
- case-based reasoning (1)
- change (1)
- classification scheme (1)
- community (1)
- competence development (1)
- components suppliers (1)
- context-aware computing (1)
- control loop mechanism (1)
- conversion (1)
- conversion sequences (1)
- cooperative AI (human-in-the-loop) (1)
- copyright (1)
- coring (1)
- corona-sensitive data collection (1)
- creativity training (1)
- cross self-confrontation (1)
- cross-plant business processes (1)
- cyber-physical production systems (1)
- cyber-physical systems (1)
- data mining (1)
- data-driven artifacts (1)
- database (1)
- databases (1)
- decision-making (1)
- delegated proof of stake (1)
- demographic change (1)
- design science (1)
- design-science research (1)
- development of AI-based systems (1)
- didactic concept (1)
- didactic framework (1)
- digital learning factory (1)
- digital marketplaces (1)
- digital platform openness (1)
- digital platforms (1)
- digital teaching (1)
- digitization of production processes (1)
- discrete event simulation (1)
- discussion (1)
- distributed knowledge base (1)
- domain-specific language (1)
- eference Architecture Model (1)
- effectiveness (1)
- empirical evaluation (1)
- empirical examination (1)
- empirical studies (1)
- enhancement (1)
- enteprise-level (1)
- enterprise resource planning systems (1)
- enterprise system (1)
- enterprise systems (1)
- environmental footprint (1)
- errors in modeling (1)
- experience; (1)
- experiment (1)
- experimental design (1)
- experimentation (1)
- explainability (1)
- factory software (1)
- federated industrial platform ecosystems (1)
- future (1)
- game-based learning (1)
- gamification (1)
- geographical distribution (1)
- gewerkschaftlich unterstützte Weiterbildungspraxis (1)
- higher education (1)
- human-machine-interaction (1)
- humans-in-the-loop (1)
- hybrid simulation (1)
- improvement (1)
- industrial innovation (1)
- industrielle Innovationen (1)
- information system architecture (1)
- information systems research (1)
- intentionales Vergessen (1)
- intermediaries (1)
- internet of things and services (1)
- intervention (1)
- interventions (1)
- job-shop scheduling (1)
- knowledge (1)
- knowledge engineering (1)
- knowledge transfer velocity (1)
- kognitive Assistenzsysteme (1)
- labour union education (1)
- learning (1)
- learning environment (1)
- learning scenario (1)
- learning scenario for manufacturing (1)
- learning scenario implementation (1)
- manipulation (1)
- manufacturing (1)
- manufacturing systems (1)
- market survey (1)
- metadata (1)
- mobile IIoT-technologies (1)
- mobile software ecosystems (1)
- modeling language (1)
- morphologic box (1)
- morphological analysis (1)
- multi-actor routine (1)
- music industry (1)
- new product development (1)
- notation (1)
- person-related factors (1)
- personalised learning (1)
- portal (1)
- problems (1)
- process design (1)
- process improvement (1)
- process integration (1)
- process knowledge (1)
- process of modeling (1)
- process perspective (1)
- process simulation (1)
- process-oriented knowledge acquisition (1)
- product carbon footprint (1)
- product configurators (1)
- product development (1)
- production engineering computing (1)
- production networks (1)
- production routine (1)
- programming skills (1)
- proof of stake (1)
- proof of work (1)
- quality (1)
- quantitative (1)
- recording of workplaces (1)
- regional network (1)
- remanufacturing (1)
- requirements (1)
- research challenges (1)
- retentivity (1)
- retrieval cues (1)
- retrofit (1)
- risks (1)
- routines (1)
- rype of change content (1)
- scenario modeling (1)
- search engine (1)
- simulation (1)
- smart automation (1)
- smart grid (1)
- smart production (1)
- software engineering (1)
- standardization (1)
- subject differences (1)
- subject-oriented learning (1)
- sustainability (1)
- task realization strategies (1)
- teaching and learning model (1)
- technologies (1)
- terminology (1)
- time consumption (1)
- training (1)
- triple bottom line (1)
- turbulence (1)
- variant management (1)
- various applications (1)
- virtual learning (1)
- werksübergreifende Geschäftsprozesse (1)
- ökologischer Fußabdruck (1)
Institute
- Wirtschaftswissenschaften (139)
- Fachgruppe Betriebswirtschaftslehre (88)
- Wirtschafts- und Sozialwissenschaftliche Fakultät (4)
- Hasso-Plattner-Institut für Digital Engineering GmbH (3)
- Fachgruppe Politik- & Verwaltungswissenschaft (2)
- Sozialwissenschaften (2)
- Bürgerliches Recht (1)
- Department Psychologie (1)
- Extern (1)
- Forschungsbereich „Politik, Verwaltung und Management“ (1)
Künstliche Intelligenz ist in aller Munde. Immer mehr Anwendungsbereiche werden durch die Auswertung von vorliegenden Daten mit Algorithmen und Frameworks z.B. des Maschinellen Lernens erschlossen. Dieses Buch hat das Ziel, einen Überblick über gegenwärtig vorhandene Lösungen zu geben und darüber hinaus konkrete Hilfestellung bei der Auswahl von Algorithmen oder Tools bei spezifischen Problemstellungen zu bieten. Um diesem Anspruch gerecht zu werden, wurden 90 Lösungen mittels einer systematischen Literaturrecherche und Praxissuche identifiziert sowie anschließend klassifiziert. Mit Hilfe dieses Buches gelingt es, schnell die notwendigen Grundlagen zu verstehen, gängige Anwendungsgebiete zu identifizieren und den Prozess zur Auswahl eines passenden ML-Tools für das eigene Projekt systematisch zu meistern.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
In the copyright industries of the 21st century, metadata is the grease required to make the engine of copyright run smoothly and powerfully for the benefit of creators, copyright industries and users alike. However, metadata is difficult to acquire and even more difficult to keep up to date as the rights in content are mostly multi-layered, fragmented, international and volatile. This article explores the idea of a neutral metadata search and enhancement tool that could constitute a buffer to safeguard the interests of the various proprietary database owners and avoid the shortcomings of centralised databases.
ERP-Systeme
(2021)
The increasing demand for software engineers cannot completely be fulfilled by university education and conventional training approaches due to limited capacities. Accordingly, an alternative approach is necessary where potential software engineers are being educated in software engineering skills using new methods. We suggest micro tasks combined with theoretical lessons to overcome existing skill deficits and acquire fast trainable capabilities. This paper addresses the gap between demand and supply of software engineers by introducing an actionoriented and scenario-based didactical approach, which enables non-computer scientists to code. Therein, the learning content is provided in small tasks and embedded in learning factory scenarios. Therefore, different requirements for software engineers from the market side and from an academic viewpoint are analyzed and synthesized into an integrated, yet condensed skills catalogue. This enables the development of training and education units that focus on the most important skills demanded on the market. To achieve this objective, individual learning scenarios are developed. Of course, proper basic skills in coding cannot be learned over night but software programming is also no sorcery.
As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization.
Since more and more production tasks are enabled by Industry 4.0 techniques, the number of knowledge-intensive production tasks increases as trivial tasks can be automated and only non-trivial tasks demand human-machine interactions. With this, challenges regarding the competence of production workers, the complexity of tasks and stickiness of required knowledge occur [1]. Furthermore, workers experience time pressure which can lead to a decrease in output quality. Cyber-Physical Systems (CPS) have the potential to assist workers in knowledge-intensive work grounded on quantitative insights about knowledge transfer activities [2]. By providing contextual and situational awareness as well as complex classification and selection algorithms, CPS are able to ease knowledge transfer in a way that production time and quality is improved significantly. CPS have only been used for direct production and process optimization, knowledge transfers have only been regarded in assistance systems with little contextual awareness. Embedding production and knowledge transfer optimization thus show potential for further improvements. This contribution outlines the requirements and a framework to design these systems. It accounts for the relevant factors.
Already successfully used products or designs, past projects or our own experiences can be the basis for the development of new products. As reference products or existing knowledge, it is reused in the development process and across generations of products. Since further, products are developed in cooperation, the development of new product generations is characterized by knowledge-intensive processes in which information and knowledge are exchanged between different kinds of knowledge carriers. The particular knowledge transfer here describes the identification of knowledge, its transmission from the knowledge carrier to the knowledge receiver, and its application by the knowledge receiver, which includes embodied knowledge of physical products. Initial empirical findings of the quantitative effects regarding the speed of knowledge transfers already have been examined. However, the factors influencing the quality of knowledge transfer to increase the efficiency and effectiveness of knowledge transfer in product development have not yet been examined empirically. Therefore, this paper prepares an experimental setting for the empirical investigation of the quality of knowledge transfers.
Yes, we can (?)
(2021)
The COVID-19 crisis has caused an extreme situation for higher education institutions around the world, where exclusively virtual teaching and learning has become obligatory rather than an additional supporting feature. This has created opportunities to explore the potential and limitations of virtual learning formats. This paper presents four theses on virtual classroom teaching and learning that are discussed critically. We use existing theoretical insights extended by empirical evidence from a survey of more than 850 students on acceptance, expectations, and attitudes regarding the positive and negative aspects of virtual teaching. The survey responses were gathered from students at different universities during the first completely digital semester (Spring-Summer 2020) in Germany. We discuss similarities and differences between the subjects being studied and highlight the advantages and disadvantages of virtual teaching and learning. Against the background of existing theory and the gathered data, we emphasize the importance of social interaction, the combination of different learning formats, and thus context-sensitive hybrid learning as the learning form of the future.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep reinforcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensorand process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
Digitization and demographic change are enormous challenges for companies. Learning factories as innovative learning places can help prepare older employees for the digital change but must be designed and configured based on their specific learning requirements. To date, however, there are no particular recommendations to ensure effective age-appropriate training of bluecollar workers in learning factories. Therefore, based on a literature review, design characteristics and attributes of learning factories and learning requirements of older employees are presented. Furthermore, didactical recommendations for realizing age-appropriate learning designs in learning factories and a conceptualized scenario are outlined by synthesizing the findings.
As the complexity of learning task requirements, computer infrastruc- tures and knowledge acquisition for artificial neuronal networks (ANN) is in- creasing, it is challenging to talk about ANN without creating misunderstandings. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information and knowledge on the base of an integration with knowledge- intensive business process models and a process-oriented knowledge manage- ment are attractive. With the aim of making the design of learning tasks express- ible by models, this paper proposes a graphical modeling language called Neu- ronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaptation exemplifies its use as a first demonstration.
Die Digitalisierung von Produktionsprozessen schreitet mit einer hohen Intensität voran. Weiterbildung hat eine hohe Relevanz für betriebliche Transformationsprozesse. Die betriebliche Weiterbildungspraxis ist den aktuellen Herausforderungen der Digitalisierung jedoch nicht gewachsen. Herausforderungen sind Kompetenzlücken der Mitarbeiter, ungewisse Anforderungsprofile und Tätigkeitstypen, demographischer Wandel sowie veraltete didaktische Ansätze. Zudem wird bestehender inhaltlicher und pädagogischer Freiraum bei der Gestaltung von Weiterbildung oftmals nur unzureichend ausgenutzt. Die skizzierte Situation führt dazu, dass der Mehrwert gegenwärtiger Qualifizierungsangebote sowohl für Unternehmen als auch Beschäftigte nicht ausgeschöpft wird. Ausgehend von Veränderungen durch Digitalisierung in der Produktion und deren Auswirkungen auf die Kompetenzentwicklung diskutiert dieser Beitrag Herausforderungen gegenwärtiger betrieblicher Weiterbildung. Er leitet Handlungsempfehlungen ab, die mithilfe von Beispielen gewerkschaftlich unterstützter Weiterbildungspraxis illustriert werden. Im Ergebnis erhalten Interessierte einen Überblick über gegenwärtige Herausforderungen und Handlungsempfehlungen für die Gestaltung und Durchführung von Weiterbildung in Zeiten der Digitalisierung.
Wodurch zeichnen sich die besten ERP-Systeme aus? Diese Frage wird dem Autor dieses Beitrags immer wieder gestellt. Mit der Vorstellung der Balanced ERP Scorecard (BESC) besteht nun eine Möglichkeit, ein System aus verschiedenen Perspektiven zu bewerten und so individuell zu einer Einschätzung des für eine konkrete Unternehmenssituation besten Systems zu gelangen. Daher beschreibt dieser Beitrag zunächst die Perspektiven der BESC und dann mögliche Kriterien für eine Ausgestaltung dieser Scorecard.
Die Branche der Dienstleistungsunternehmen (Professional Services) hat einige Anforderungen, die sie von den „klassischen“ ERP-Branchen Industrie und Handel unterscheidet. Dieser Beitrag beschreibt einige der aktuellen Herausforderungen dieses immer wichtiger werdenden Wirtschaftszweigs und geht dann am Beispiel eines mittelständischen Ingenieurdienstleisters auf typische Anforderungen dieser Branche, infrage kommende Systeme und das Vorgehen zur Auswahl ein.
Wiederanlauf nach der Krise
(2020)
Jetzt intelligent aus der Krise heraus starten! Der Anlauf von Neuprodukten und der jetzt notwendige Wiederanlauf nach der Corona-Krise haben einige Gemeinsamkeiten: In beiden Fällen muss vorsichtig vorgegangen werden, es muss eine hohe Wandlungsfähigkeit und Anpassungsfähigkeit aufrechterhalten werden, um schnell auf eine Veränderung der Situation reagieren zu können und es werden geeignete Werkzeuge und Prognoseverfahren benötigt, um sich die Auswirkungen von geplanten Schritten vorher verdeutlichen zu können. Das vorliegende Herausgeberwerk wurde zusammengestellt, um Expertenwissen für die Praxis nutzbar zu machen. Die über 30 Aufsätze in diesem Werk dienen dem Ziel, das Thema „Wiederanlauf nach der Krise“ aus allen wichtigen Blickwinkeln zu beleuchten und alle relevanten Branchen zu berücksichtigen. Nach der Darstellung allgemeiner Prinzipien des Wiederanlaufs werden Methoden und Werkzeuge vorgestellt, bevor dann Spezika einzelner Branchen diskutiert werden. Im Vordergrund steht dabei die international vernetzte Automobilindustrie sowie die globalen Lieferketten. Weitere Branchen wie die Elektronikfertigung und die Herstellung von Konsumgütern werden ebenfalls besprochen. Zielgruppe dieses Werkes sind vor allem diejenigen, die jetzt den Wiederanlauf von Produktionssystemen nach der drastischen Reduzierung durch das neuartige Corona-Virus planen, vorbereiten und umsetzen.
The usage of gamification in the contexts of commerce, consumption, innovation or eLearning in schools and universities has been extensively researched. However, the potentials of serious games to transfer and perpetuate knowledge and action patterns in learning factories have not been levered so far. The goal of this paper is to introduce a serious game as an instrument for knowledge transfer and perpetuation. Therefore, reqirements towards serious games in the context of learning factories are pointed out. As a result, that builds on these requirements, a serious learning game for the topic of Industry 4.0 is practically designed and evaluated.
Einsatzorganisationen, wie z. B. Feuerwehr oder Technisches Hilfs-werk, müssen sehr schnell auf teilweise unbekannte Lagen reagieren und angemessene Hilfeleistung erbringen. Können Handlungsweisen und vorbereitende Maßnahmen dieser Organisationen auf die Störungsbeseitigung in Produktionssystemen übertragen werden? Ein Experiment in einem Cyber-Physischen Produktionssystem geht dieser Frage nach. Es zeigt sich, dass durch die Anwendung geeigneter Handlungsmuster sowohl die Dauer von Störungen als auch die Zeit für die Behebung verkürzt werden können.
Die teilweise sehr kurzfristig notwendige Reaktion auf Veränderungen erfordert von Unternehmen ein hohes Maß an Flexibilität und Reaktionsgeschwindigkeit. Anwendungssystemarchitekturen, die im Wesentlichen aus alten und selbst entwickelten Systemen bestehen, erfüllen häufig diese Anforderungen nicht. Investitionsmittel für neue Software sind jedoch begrenzt, daher müssen Prioritäten in der Ablösung von Altsystemen gesetzt werden. Eine effiziente Analysemethode zur Planung der Erneuerung der Anwendungssystemlandschaft stellt die Wandlungsfähigkeitsanalyse dar. Dieser Beitrag beschreibt Vorgehen und Ergebnisse am Beispiel eines international tätigen Automobilzulieferers.
A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the transfer of knowledge between any kind of knowledge carriers in business processes with AR techniques can lead to a huge competitive advantage, for instance in manufacturing. This includes the transfer of person-bound knowledge as well as externalized knowledge of physical and virtual objects. The contribution builds on a time-dependent knowledge transfer model and conceptualizes an adaptable, AR-based application. Having the intention to accelerate the speed of knowledge transfers between a manufacturer and an information system, empirical results of an experimentation show the validity of this approach. For the first time, it will be possible to discover how to improve the transfer among knowledge carriers of an organization with knowledge-driven information systems (KDIS). Within an experiment setting, the paper shows how to improve the quantitative effects regarding the quality and amount of time needed for an example manufacturing process realization by an adaptable KDIS.
Neben dem enormen Kursanstieg des Bitcoins in den Jahren 2017/2018, stieg im gleichen Maß auch die benötigte Rechenleistung und der damit verbundene Elektrizitätsbedarf, um Blöcke innerhalb der Bitcoin-Blockchain zu verifizieren. Aus diesem Problem ableitend beschäftigt sich dieser Beitrag mit der Fragestellung, welchen Beitrag unterschiedliche Konsens-Algorithmen innerhalb einer Blockchain zur Nachhaltigkeit liefern. Im Ergebnis liegt ein Überblick über die meist genutzten Konsens-Algorithmen und deren Beitrag zur Nachhaltigkeit vor.
Technological advancements are giving rise to the fourth industrial revolution - Industry 4.0 -characterized by the mass employment of smart objects in highly reconfigurable and thoroughly connected industrialproduct-service systems. The purpose of this paper is to propose a theory-based knowledgedynamics model in the smart grid scenario that would provide a holistic view on the knowledge-based interactions among smart objects, humans, and other actors as an underlyingmechanism of value co-creation in Industry 4.0. A multi-loop and three-layer - physical, virtual, and interface - model of knowledge dynamics is developedby building on the concept of ba - an enabling space for interactions and theemergence of knowledge. The model depicts how big data analytics are just one component inunlocking the value of big data, whereas the tacit engagement of humans-in-the-loop - theirsense-making and decision-making - is needed for insights to be evoked fromanalytics reports and customer needs to be met.
As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies.
Die Auswahl von Standardsoftware stellt viele Unternehmen vor Herausforderungen. Gerade im deutschen Mittelstand kommen vermehrt eigenentwickelte Individuallösungen zum Einsatz. Ent- sprechende Unternehmen sind daher nicht mit komplexen Soft- wareauswahlprojekten vertraut. Das breite Angebot an ERP-Systemen erschwert die Vergleichbarkeit der Lösungen und die zielgerichtete Auswahl des idealen Systems zusätzlich.
Produkte werden zunehmend internetfähig. Gerade im Kontext der Industrie 4.0 statten beispielsweise Maschinen- und Anlagenbauer sowie Komponentenhersteller ihre Produkte mit Option zur Netzwerk- und Internetanbindung aus. Neben der technischen Realisierung beschäftigt Unternehmen die Frage, wie diese neue Geschäftsmodelle realisieren können. Gerade bei Produkten, die bei Kunden im Einsatz sind, kommt der Nutzung von IoT-Plattformen eine wichtige Bedeutung zu.
Cyber-physical systems (CPS) have shaped the discussion about Industry 4.0 (I4.0) for some time. To ensure the competitiveness of manufacturing enterprises the vision for the future figures out cyber-physical production systems (CPPS) as a core component of a modern factory. Adaptability and coping with complexity are (among others) potentials of this new generation of production management. The successful transformation of this theoretical construct into practical implementation can only take place with regard to the conditions characterizing the context of a factory. The subject of this contribution is a concept that takes up the brownfield character and describes a solution for extending existing (legacy) systems with CPS capabilities.
Fabriksoftware
(2020)
Immer mehr Konzepte versprechen die Digitale Fabrik, die Industrie 4.0-Fabrik, die Smart Factory usw. Allen ist gemeinsam, dass dahinter der erheblich ausgeweitete Einsatz von vernetzter Software steht. Allein der Begriff Fabriksoftware selbst ist noch nicht definiert bzw. gegenüber nahestehenden Begriffen abgegrenzt. Der vorliegende Beitrag stellt dazu einen für Forschung und Praxis tauglichen Ansatz zur Einordnung von Software in Fertigung und Logistik vor.
Time to change
(2020)
Industry 4.0 leads to a radical change that is progressing incrementally. The new information and communication technologies provide many conceivable opportunities for their application in the context of sustainable corporate management. The combination of new digital technologies with the ecological and social goals of companies offers a multitude of unimagined potentials and challenges. Although companies already see the need for action, there was in the past and currently still is a lack of concrete measures that lever the potential of Industry 4.0 for sustainability management. During the course of this position paper we develop six theses (two from each sustainability perspective) against the background of the current situation in research and practice, and policy.
Die Innovationstätigkeit im industriellen Umfeld verlagert sich durch die Digitalisierung hin zu Produkt-Service-Systemen. Kleine und mittlere Unternehmen haben sich in ihrer Entwicklungstätigkeit bisher stark auf die Produktentwicklung bezogen. Der Umstieg auf „smarte“ Produkte und die Kopplung an Dienstleistungen erfordert häufig personelle und finanzielle Ressourcen, welche KMU nicht aufbringen können. Crowdsourcing stellt eine Möglichkeit dar, den Innovationsprozess für externe Akteure zu öffnen und Kosten- sowie Geschwindigkeitsvorteile zu realisieren. Bei der Integration von Crowdsourcing-Elementen ist jedoch einigen Herausforderungen zu begegnen. Dieser Beitrag zeigt sowohl die Potenziale als auch die Barrieren einer Crowdsourcing-Nutzung im industriellen Umfeld auf.
The implementation of learning scenarios is a diversely challenging, frequently purely manual and effortful undertaking. In this contribution a process based view is used in scenario generation to overcome communication, coordination and technical gaps. A framework is provided to identify, define and integrate technological artefacts and learning content as modular, reusable building blocks along a modeled production process. The specific contribution is twofold: 1) the theoretical framework represents a unique basis for modularization of content and technology in order to enhance reusability, 2) the model based scenario definition is a starting point for automated implementation of learning scenarios in industrial learning environments that has not been created before.
Lernen mit Assistenzsystemen
(2020)
Der Beitrag beschreibt die Konzeption und Durchführung und bietet einen Einblick in die ersten Ergebnisse einer Untersuchung mit experimentellem Design in einer simulierten Prozessumgebung im Forschungs- und Anwendungszentrum Industrie 4.0 in Potsdam. Im Mittelpunkt stehen Anlernprozesse im Bereich der Einfacharbeit (Helfertätigkeiten) und ihre Gestaltung durch den Einsatz digitaler Assistenzsysteme. In der Arbeitsforschung finden sich Hinweise darauf, dass mit dem Einsatz dieser Systeme Prozesswissen verloren geht, im Sinne einer guten Kenntnis des gesamten Arbeitsprozesses, in den die einzelnen Tätigkeiten eingebettet sind. Das kann sich als Problem erweisen, vor allem wenn unvorhersehbare Situationen oder Fehler eintreten. Um die Rolle von Prozesswissen beim Einsatz von digitalen Assistenzsystemen zu untersuchen, wird im Experiment eine echte Fabriksituation simuliert. Die Probanden werden über ein Assistenzsystem Schritt für Schritt in ihre Aufgabentätigkeit angelernt, einem Teil der Probanden wird allerdings am Anfang zusätzlich Prozesswissen im Rahmen einer kurzen Schulung vermittelt.
Digitale Plattformen
(2020)
Obwohl digitale Plattformen vornehmlich von Großunternehmen betrieben werden, bieten sie klein- und mittelständischen Unternehmen (KMU) Potenziale zur Verbreitung innovativer Technologien und für den Ausbau ihres Geschäftsmodells. Für die Umsetzung digitaler Plattformen stehen Unternehmen mehrere Strategien zur Verfügung. Der Beitrag vergleicht und bewertet grundlegende Strategien am Beispiel eines Maschinenbauunternehmens. Die Ergebnisse dienen als Grundlage für die Entscheidungsfindung von KMU.
Digitale Plattformen
(2020)
Obwohl digitale Plattformen vornehmlich von Großunternehmen betrieben werden, bieten sie klein- und mittelständischen Unternehmen (KMU) Potenziale zur Verbreitung innovativer Technologien und für den Ausbau ihres Geschäftsmodells. Für die Umsetzung digitaler Plattformen stehen Unternehmen mehrere Strategien zur Verfügung. Der Beitrag vergleicht und bewertet grundlegende Strategien am Beispiel eines Maschinenbauunternehmens. Die Ergebnisse dienen als Grundlage für die Entscheidungsfindung von KMU.
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
Keywords
Für die Wettbewerbsfähigkeit von Unternehmen hat der Kontinuierliche Verbesserungsprozess (KVP) eine hohe Bedeutung. Hinsichtlich der Qualität und Quantität der Beiträge für den KVP durch die Mitarbeitenden stoßen Unternehmen, insbesondere KMU, jedoch auf vielfältige Herausforderungen. Diesen Problemen können Unternehmen durch das KVP-Tool begegnen, welches im Projekt „Adaptive Spielifizierung im KVP“ entwickelt wird. Durch die Digitalisierung und Spielifizierung des Prozes- ses im KVP-Tool wird die kontinuierliche Beteiligung nachhaltig durch intrinsische Anreize gefördert. Die Neuartigkeit des Projektes ergibt sich aus der Adaptivität der Spielifizierung, also die Wechselwirkung zu den Nutzenden. Dabei werden zwei Aspekte fokussiert: unterschiedliche Spielertypen und Marktdynamik.
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example.
Existing factories face multiple problems due to their hierarchical structure of decision making and control. Cyber-physical systems principally allow to increase the degree of autonomy to new heights. But which degree of autonomy is really useful and beneficiary? This paper differentiates diverse definitions of autonomy and approaches to determine them. Some experimental findings in a lab environment help to answer the question raised in this paper.
Dieses Buch bietet eine Einführung in die Wirtschaftsinformatik in kommentierter Form. Es richtet sich in erster Linie an Studierende der Betriebswirtschaftslehre und der Wirtschaftsinformatik.
Band 1 beinhaltet eine Betrachtung der nachfolgenden Themenpunkte: Der erste Abschnitt gibt eine Einführung in die Bedeutung der Wirtschaftsinformatik als Wissenschaftsfach und damit verbunden in ihre praktische Anwendungsorientierung. Der folgende Abschnitt liefert einen Überblick über die der Informatik zugrunde liegenden Konzepte und Techniken von Computer-Hardware und -Software sowie Begriffsbestimmungen und Beschreibungsmerkmale der Daten, Datenhaltung und -speicherung. Ein weiterer Abschnitt ist dem Komplex Netzwerke und Internet gewidmet. In kompakter Form werden Grundlagen der Netze und Netzwerkdienste erklärt. Das Thema Datenmodellierung bildet den Schwerpunkt dieses Bandes. Die Vorgehensweise zur Erstellung und Bearbeitung von Modellen wird in sehr ausführlicher Form dargelegt. Den Abschluss bildet die Verbindung zwischen Datenbanken und betrieblichen Anwedungssystemen.
Dieses Buch bietet eine Einführung in die Wirtschaftsinformatik in kommentierter Form. Es richtet sich in erster Linie an Studierende der Betriebswirtschaftslehre und der Wirtschaftsinformatik. Zu Beginn dieses Bandes wird eine Einführung in die Funktionalität einer Oracle-Datenbank am Beispiel der Version Oracle 10g XE als frei verfügbare Version des relationalen Datenbanksystems Oracle 10g gegeben. Der thematische Schwerpunkt im Band 2, die Datenbankabfragesprache SQL, baut auf dem Teil der Datenmodellierung des Bandes 1 auf. Zum besseren Verständnis der Zusammenhänge ist ein durchgehend verwendbares Beispiel gewählt worden. An Hand dieses Beispiels werden sowohl Begriffe als auch Zusammenhänge in der Umsetzung vom relationalen Datenmodell zur Datenbank erläutert. Im Detail werden sowohl Syntax als auch Semantik der Datenbeschreibungssprache SQL erläutert.
Audit - and then what?
(2019)
Current trends such as digital transformation, Internet of Things, or Industry 4.0 are challenging the majority of learning factories. Regardless of whether a conventional learning factory, a model factory, or a digital learning factory, traditional approaches such as the monotonous execution of specific instructions don‘t suffice the learner’s needs, market requirements as well as especially current technological developments. Contemporary teaching environments need a clear strategy, a road to follow for being able to successfully cope with the changes and develop towards digitized learning factories. This demand driven necessity of transformation leads to another obstacle: Assessing the status quo and developing and implementing adequate action plans. Within this paper, details of a maturity-based audit of the hybrid learning factory in the Research and Application Centre Industry 4.0 and a thereof derived roadmap for the digitization of a learning factory are presented.
Subject-oriented learning
(2019)
The transformation to a digitized company changes not only the work but also social context for the employees and requires inter alia new knowledge and skills from them. Additionally, individual action problems arise. This contribution proposes the subject-oriented learning theory, in which the employees´ action problems are the starting point of training activities in learning factories. In this contribution, the subject-oriented learning theory is exemplified and respective advantages for vocational training in learning factories are pointed out both theoretically and practically. Thereby, especially the individual action problems of learners and the infrastructure are emphasized as starting point for learning processes and competence development.
Industry 4.0, based on increasingly progressive digitalization, is a global phenomenon that affects every part of our work. The Internet of Things (IoT) is pushing the process of automation, culminating in the total autonomy of cyber-physical systems. This process is accompanied by a massive amount of data, information, and new dimensions of flexibility. As the amount of available data increases, their specific timeliness decreases. Mastering Industry 4.0 requires humans to master the new dimensions of information and to adapt to relevant ongoing changes. Intentional forgetting can make a difference in this context, as it discards nonprevailing information and actions in favor of prevailing ones. Intentional forgetting is the basis of any adaptation to change, as it ensures that nonprevailing memory items are not retrieved while prevailing ones are retained. This study presents a novel experimental approach that was introduced in a learning factory (the Research and Application Center Industry 4.0) to investigate intentional forgetting as it applies to production routines. In the first experiment (N = 18), in which the participants collectively performed 3046 routine related actions (t1 = 1402, t2 = 1644), the results showed that highly proceduralized actions were more difficult to forget than actions that were less well-learned. Additionally, we found that the quality of cues that trigger the execution of routine actions had no effect on the extent of intentional forgetting.