TY - CHAP A1 - Thim, Christof A1 - Grum, Marcus A1 - Schüffler, Arnulf A1 - Roling, Wiebke A1 - Kluge, Annette A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - A concept for a distributed Interchangeable knowledge base in CPPS T2 - Towards sustainable customization: cridging smart products and manufacturing systems N2 - 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. KW - learning KW - distributed knowledge base KW - artificial intelligence KW - CPPS Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90702-0 SN - 978-3-030-90700-6 U6 - https://doi.org/10.1007/978-3-030-90700-6_35 SP - 314 EP - 321 PB - Springer CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Roling, Wiebke A1 - Schüffler, Arnulf A1 - Kluge, Annette A1 - Gronau, Norbert ED - Masrour, Tawfik ED - El Hassani, Ibtissam ED - Barka, Noureddine T1 - AI case-based reasoning for artificial neural networks T2 - Artificial intelligence and industrial applications N2 - Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level. KW - case-based reasoning KW - neural networks KW - industry 4.0 Y1 - 2023 SN - 978-3-031-43523-2 SN - 978-3-031-43524-9 U6 - https://doi.org/10.1007/978-3-031-43524-9_2 VL - 771 SP - 17 EP - 35 PB - Springer CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - Aiming for knowledge-transfer-optimizing intelligent cyber-physical systems T2 - Towards sustainable customization : cridging smart products and manufacturing systems N2 - 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. KW - smart automation KW - smart production KW - human-machine-interaction Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90700-6 SN - 978-3-030-90702-0 U6 - https://doi.org/10.1007/978-3-030-90700-6_16 SP - 149 EP - 157 PB - Springer CY - Cham ER - TY - JOUR A1 - Haase, Jennifer A1 - Thim, Christof T1 - An approach to model forgetting JF - AIS Transactions on Enterprise Systems N2 - This paper aims to investigate the possibility to include aspects of forgetting into business process modeling. To date, there is no possibility to model forgotten or to-be- forgotten elements beyond the mere deletion. On a first attempt, we focus on the individual level and model knowledge transformation within a single person. Using the Knowledge Model Description Language, we propose ways to include different forms of forgetting into the realm of modeling tools. Using data from an experimental setting within an assembly line production environment, the usability of those new modeling tools is tested. So far, the applicability of modeling features for forgetting on the individual level is mostly restricted to a research context. However, clear requirements to transfer the tools onto the team- and organizational level are set out. Y1 - 2020 U6 - https://doi.org/10.30844/aistes.v4i1.17 VL - 4 IS - 1 PB - Gito mbH Verlag für Industrielle Informationstechnik und Organisation CY - Berlin ER - TY - JOUR A1 - Thim, Christof A1 - Ullrich, André A1 - Eigelshoven, Felix A1 - Gronau, Norbert A1 - Ritter, Ann-Carolin T1 - Crowdsourcing bei industriellen Innovationen T1 - Crowdsourcing for industrial innovations BT - Lösungsansätze und Herausforderung für KMU BT - solutions and challenges for SMEs JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - 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. N2 - Innovation activity in the industrial environment is shifting towards product-service systems as a result of digitalisation. Small and medium-sized enterprises have so far focused their development activities strongly on product development. The switch to “smart” products and the coupling to services often requires personnel and financial resources that SMEs cannot provide. Crowdsourcing is one way of opening up the innovation process to external actors and realising cost and speed advantages. However, the integration of crowdsourcing elements faces several challenges. This article shows both the potentials and the barriers of crowdsourcing in the industrial environment. KW - Crowdsourcing KW - industrielle Innovationen KW - KMU KW - industrial innovation KW - SMEs Y1 - 2020 U6 - https://doi.org/10.30844/I40M_20-6_S9-13 SN - 2364-9208 VL - 36 IS - 6 SP - 9 EP - 13 PB - GITO mbH Verlag CY - Berlin ER - TY - CHAP A1 - Bender, Benedict A1 - Thim, Christof ED - Bender, Benedict T1 - Entering complementary markets on software platforms BT - the third-party perspective T2 - Platform coring on digital software platforms N2 - Software platforms regularly introduce new features to remain competitive. While platform innovation is considered to be a critical success factor, adding certain features could hurt the ecosystem. If platform owners provide functionality that was previously provided by a contributor, the owners enter complementary product spaces. Complementary market entry frequently occurs on software platforms and is a major concern for third-party developers. Divergent findings on the impact of complementary market entry call for the consideration of additional factors. As prior research neglected the third-party perspective, this contribution aims to address this gap. We explore the use of measures to prevent complementary market entry using a survey approach on browser platforms. The research model is tested with 655 responses among developer from Mozilla Firefox and Google Chrome. To explain countermeasures employment, developer’s attitude and perceived likelihood are important. The results reveal that developers employ countermeasures if complementary market entry is assessed negatively and perceived as likely for their extension. Differences among browser platforms concerning complementary market entry are identified. Product spaces of extensions being available on multiple platforms are less likely to be entered and more heavily protected. Implications for research and stakeholders, i.e. platform owners and contributors are discussed. KW - complementary market entry KW - third-party developer KW - digital platforms KW - software platforms KW - browser platforms KW - platform innovation Y1 - 2021 SN - 978-3-658-34798-7 SN - 978-3-658-34799-4 U6 - https://doi.org/10.1007/978-3-658-34799-4_7 SP - 149 EP - 199 PB - Springer Gabler CY - Wiesbaden ER - TY - CHAP A1 - Grum, Marcus A1 - Klippert, Monika A1 - Albers, Albert A1 - Gronau, Norbert A1 - Thim, Christof T1 - Examining the quality of knowledge transfers BT - the draft of an empirical research T2 - Proceedings of the Design Society N2 - 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. KW - knowledge management KW - new product development KW - evaluation Y1 - 2021 U6 - https://doi.org/10.1017/pds.2021.404 SN - 2732-527X VL - 1 SP - 1431 EP - 1440 PB - Cambridge University Press CY - Cambridge ER - TY - CHAP A1 - Haase, Jennifer A1 - Thim, Christof A1 - Bender, Benedict T1 - Expanding modeling notations BT - requirements for creative process modeling T2 - Business Process Management Workshops. BPM 2021 / Lecture Notes in Business Information Processing N2 - Creativity is a common aspect of business processes and thus needs a proper representation through process modeling notations. However, creative processes constitute highly flexible process elements, as new and unforeseeable outcome is developed. This presents a challenge for modeling languages. Current methods representing creative-intensive work are rather less able to capture creative specifics which are relevant to successfully run and manage these processes. We outline the concept of creative-intensive processes and present an example from a game design process in order to derive critical process aspects relevant for its modeling. Six aspects are detected, with first and foremost: process flexibility, as well as temporal uncertainty, experience, types of creative problems, phases of the creative process and individual criteria. By first analyzing what aspects of creative work modeling notations already cover, we further discuss which modeling extensions need to be developed to better represent creativity within business processes. We argue that a proper representation of creative work would not just improve the management of those processes, but can further enable process actors to more efficiently run these creative processes and adjust them to better fit to the creative needs. KW - Modeling KW - Requirements KW - Pockets of creativity KW - Creative process Y1 - 2022 SN - 978-3-030-94342-4 SN - 978-3-030-94343-1 U6 - https://doi.org/10.1007/978-3-030-94343-1_15 IS - 436 SP - 193 EP - 196 PB - Springer CY - Cham ER - TY - CHAP A1 - Haase, Jennifer A1 - Thim, Christof A1 - Bender, Benedict ED - Marrella, Andrea ED - Weber, Barbara T1 - Expanding modeling notations BT - requirements for creative process modeling T2 - Business process management workshops N2 - Creativity is a common aspect of business processes and thus needs a proper representation through process modeling notations. However, creative processes constitute highly flexible process elements, as new and unforeseeable outcome is developed. This presents a challenge for modeling languages. Current methods representing creative-intensive work are rather less able to capture creative specifics which are relevant to successfully run and manage these processes. We outline the concept of creative-intensive processes and present an example from a game design process in order to derive critical process aspects relevant for its modeling. Six aspects are detected, with first and foremost: process flexibility, as well as temporal uncertainty, experience, types of creative problems, phases of the creative process and individual criteria. By first analyzing what aspects of creative work modeling notations already cover, we further discuss which modeling extensions need to be developed to better represent creativity within business processes. We argue that a proper representation of creative work would not just improve the management of those processes, but can further enable process actors to more efficiently run these creative processes and adjust them to better fit to the creative needs. KW - modeling KW - requirements KW - pockets of creativity KW - creative process Y1 - 2022 SN - 978-3-030-94342-4 SN - 978-3-030-94344-8 SN - 978-3-030-94343-1 U6 - https://doi.org/10.1007/978-3-030-94343-1_15 VL - 436 SP - 197 EP - 208 PB - Springer CY - Cham ER - TY - JOUR A1 - Schüffler, Arnulf A1 - Thim, Christof A1 - Haase, Jennifer A1 - Gronau, Norbert A1 - Kluge, Annette T1 - Information processing in work environment 4.0 and the beneficial impact of intentional forgetting on change management T1 - Informationsverarbeitung in der Industrie 4.0 und die vorteilhafte Wirkung von intentionalem Vergessen für das Change Management JF - Zeitschrift für Arbeits- und Organisationspsychologie : german journal of work and organizational psychology N2 - 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. N2 - Industrie 4.0 ist basierend auf fortschreitender Digitalisierung eine globale Entwicklung, die in allen Bereichen uns heute bekannter Arbeits- und Lebenswelten Einzug halten wird. Das Internet der Dinge beschleunigt Automatisierung bis hin zu autonomen cyber-physischen Systemen. Dieser Prozess wird begleitet von einer weiteren Zunahme von Daten. Gleichzeitig reduziert sich die Aktualität der Daten und damit die Dauer ihrer Relevanz. Die Herausforderungen im Umfeld von Industrie 4.0 zu meistern bedeutet für Menschen in Organisationen diese wachsenden Datenmengen und Anpassung an fortwährende Veränderung zu bewältigen. Intentionales Vergessen kann hier unterstützen. Intentionales Vergessen fokussiert das Vergessen irrelevanter Informationen und Verhaltensweisen zu Gunsten relevanter. In diesem Artikel stellen wir einen experimentellen Ansatz zur Erforschung von Prozessen des intentionalen Vergessens in Organisationen in einer Laborumgebung (Anwendungszentrum Industrie 4.0) vor. Im Fokus der Untersuchung steht dabei das Vergessen einer ungültig gewordenen Produktions-Routine und das Ausführen der neuen, jetzt gültigen. Wir beschreiben dabei zunächst das innovative experimentelle Design zur Untersuchung von Vergessensprozessen. In einer ersten Untersuchung mit N = 18 Personen, die insgesamt 3046 Handlungen zu t1 (1402) und t2 (1644) ausführen, zeigte sich, dass hoch gelernte (prozeduralisierte) Handlungen schwerer zu vergessen sind als ohnehin nicht prozeduralisierte. Es zeigt sich aber kein Unterschied hinsichtlich der Art der Handlungen und der Hinweisreize, durch die sie aufgerufen werden. KW - intentional forgetting KW - retrieval cues KW - production routine KW - intentionales Vergessen KW - Produktions-Routine KW - Hinweisreize Y1 - 2019 U6 - https://doi.org/10.1026/0932-4089/a000307 SN - 0932-4089 SN - 2190-6270 VL - 64 IS - 1 SP - 17 EP - 29 PB - Hogrefe CY - Göttingen ER -