@article{TeichmannUllrichWenzetal.2020, author = {Teichmann, Malte and Ullrich, Andr{\´e} and Wenz, Julian and Gronau, Norbert}, title = {Herausforderungen und Handlungsempfehlungen betrieblicher Weiterbildungspraxis in Zeiten der Digitalisierung}, series = {HMD Praxis der Wirtschaftsinformatik}, volume = {57}, journal = {HMD Praxis der Wirtschaftsinformatik}, publisher = {Springer Vieweg}, address = {Wiesbaden}, issn = {1436-3011}, doi = {10.1365/s40702-020-00614-x}, pages = {512 -- 527}, year = {2020}, abstract = {Die Digitalisierung von Produktionsprozessen schreitet mit einer hohen Intensit{\"a}t voran. Weiterbildung hat eine hohe Relevanz f{\"u}r betriebliche Transformationsprozesse. Die betriebliche Weiterbildungspraxis ist den aktuellen Herausforderungen der Digitalisierung jedoch nicht gewachsen. Herausforderungen sind Kompetenzl{\"u}cken der Mitarbeiter, ungewisse Anforderungsprofile und T{\"a}tigkeitstypen, demographischer Wandel sowie veraltete didaktische Ans{\"a}tze. Zudem wird bestehender inhaltlicher und p{\"a}dagogischer Freiraum bei der Gestaltung von Weiterbildung oftmals nur unzureichend ausgenutzt. Die skizzierte Situation f{\"u}hrt dazu, dass der Mehrwert gegenw{\"a}rtiger Qualifizierungsangebote sowohl f{\"u}r Unternehmen als auch Besch{\"a}ftigte nicht ausgesch{\"o}pft wird. Ausgehend von Ver{\"a}nderungen durch Digitalisierung in der Produktion und deren Auswirkungen auf die Kompetenzentwicklung diskutiert dieser Beitrag Herausforderungen gegenw{\"a}rtiger betrieblicher Weiterbildung. Er leitet Handlungsempfehlungen ab, die mithilfe von Beispielen gewerkschaftlich unterst{\"u}tzter Weiterbildungspraxis illustriert werden. Im Ergebnis erhalten Interessierte einen {\"U}berblick {\"u}ber gegenw{\"a}rtige Herausforderungen und Handlungsempfehlungen f{\"u}r die Gestaltung und Durchf{\"u}hrung von Weiterbildung in Zeiten der Digitalisierung.}, language = {de} } @article{RojahnWeberGronau2023, author = {Rojahn, Marcel and Weber, Edzard and Gronau, Norbert}, title = {Towards a standardization in scheduling models}, series = {International journal of industrial and systems engineering}, volume = {17}, journal = {International journal of industrial and systems engineering}, number = {6}, publisher = {Inderscience Enterprises}, address = {Gen{\`e}ve}, issn = {1748-5037}, pages = {401 -- 408}, year = {2023}, abstract = {Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in)consistence for the research field of job-shop scheduling by a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability and combinability of scheduling methods is unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods.}, language = {en} } @incollection{RojahnAmbrosBiruetal.2023, author = {Rojahn, Marcel and Ambros, Maximilian and Biru, Tibebu and Krallmann, Hermann and Gronau, Norbert and Grum, Marcus}, title = {Adequate basis for the data-driven and machine-learning-based identification}, series = {Artificial intelligence and soft computing}, booktitle = {Artificial intelligence and soft computing}, editor = {Rutkowski, Leszek and Scherer, Rafał and Korytkowski, Marcin and Pedrycz, Witold and Tadeusiewicz, Ryszard and Zurada, Jacek M.}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-42504-2}, doi = {10.1007/978-3-031-42505-9_48}, pages = {570 -- 588}, year = {2023}, abstract = {Process mining (PM) has established itself in recent years as a main method for visualizing and analyzing processes. However, the identification of knowledge has not been addressed adequately because PM aims solely at data-driven discovering, monitoring, and improving real-world processes from event logs available in various information systems. The following paper, therefore, outlines a novel systematic analysis view on tools for data-driven and machine learning (ML)-based identification of knowledge-intensive target processes. To support the effectiveness of the identification process, the main contributions of this study are (1) to design a procedure for a systematic review and analysis for the selection of relevant dimensions, (2) to identify different categories of dimensions as evaluation metrics to select source systems, algorithms, and tools for PM and ML as well as include them in a multi-dimensional grid box model, (3) to select and assess the most relevant dimensions of the model, (4) to identify and assess source systems, algorithms, and tools in order to find evidence for the selected dimensions, and (5) to assess the relevance and applicability of the conceptualization and design procedure for tool selection in data-driven and ML-based process mining research.}, language = {en} } @misc{WeberTiefenbacherGronau2019, author = {Weber, Edzard and Tiefenbacher, Anselm and Gronau, Norbert}, title = {Need for standardization and systematization of test data for job-shop scheduling}, series = {Postprints der Universit{\"a}t Potsdam Wirtschafts- und Sozialwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Wirtschafts- und Sozialwissenschaftliche Reihe}, number = {134}, issn = {1867-5808}, doi = {10.25932/publishup-47222}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-472229}, pages = {23}, year = {2019}, abstract = {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}, language = {en} } @article{WeberTiefenbacherGronau2019, author = {Weber, Edzard and Tiefenbacher, Anselm and Gronau, Norbert}, title = {Need for Standardization and Systematization of Test Data for Job-Shop Scheduling}, series = {Data}, volume = {4}, journal = {Data}, number = {1}, publisher = {MDPI}, address = {Basel}, issn = {2306-5729}, doi = {10.3390/data4010032}, pages = {21}, year = {2019}, abstract = {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.}, language = {en} } @inproceedings{RojahnGronau2023, author = {Rojahn, Marcel and Gronau, Norbert}, title = {Digital platform concepts for manufacturing companies}, series = {10th International Conference on Future Internet of Things and Cloud (FiCloud)}, booktitle = {10th International Conference on Future Internet of Things and Cloud (FiCloud)}, publisher = {IEEE}, address = {[Erscheinungsort nicht ermittelbar]}, isbn = {979-8-3503-1635-3}, doi = {10.1109/FiCloud58648.2023.00030}, pages = {149 -- 158}, year = {2023}, abstract = {Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.}, language = {en} } @inproceedings{RojahnGronau2024, author = {Rojahn, Marcel and Gronau, Norbert}, title = {Openness indicators for the evaluation of digital platforms between the launch and maturity phase}, series = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences}, editor = {Bui, Tung X.}, publisher = {Department of IT Management Shidler College of Business University of Hawaii}, address = {Honolulu, HI}, isbn = {978-0-99813-317-1}, pages = {4516 -- 4525}, year = {2024}, abstract = {In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation.}, language = {en} } @article{UllrichTeichmannGronau2021, author = {Ullrich, Andr{\´e} and Teichmann, Malte and Gronau, Norbert}, title = {Fast trainable capabilities in software engineering-skill development in learning factories}, series = {Ji suan ji jiao yu = Computer Education / Qing hua da xue}, journal = {Ji suan ji jiao yu = Computer Education / Qing hua da xue}, number = {12}, publisher = {[Verlag nicht ermittelbar]}, address = {Bei jing shi}, issn = {1672-5913}, doi = {10.16512/j.cnki.jsjjy.2020.12.002}, pages = {2 -- 10}, year = {2021}, abstract = {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.}, language = {en} } @misc{PanzerBenderGronau2022, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {Neural agent-based production planning and control}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, issn = {1867-5808}, doi = {10.25932/publishup-60477}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-604777}, pages = {26}, year = {2022}, abstract = {Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.}, language = {en} } @article{PanzerBenderGronau2022, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {Neural agent-based production planning and control}, series = {Journal of Manufacturing Systems}, volume = {65}, journal = {Journal of Manufacturing Systems}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0278-6125}, doi = {10.1016/j.jmsy.2022.10.019}, pages = {743 -- 766}, year = {2022}, abstract = {Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.}, language = {en} }