TY - CHAP A1 - Grum, Marcus A1 - Bender, Benedict A1 - Alfa, Attahiru S. T1 - The construction of a common objective function for analytical infrastructures T2 - 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC) N2 - The paper deals with the increasing growth of embedded systems and their role within structures similar to the Internet (Internet of Things) as those that provide calculating power and are more or less appropriate for analytical tasks. Faced with the example of a cyber-physical manufacturing system, a common objective function is developed with the intention to measure efficient task processing within analytical infrastructures. A first validation is realized on base of an expert panel. KW - Analytic Infrastructures KW - Cyber-Physical Manufacturing Systems KW - Measuring Efficient Task Processing Y1 - 2018 U6 - https://doi.org/10.1109/ICE.2017.8279892 SP - 219 EP - 225 PB - IEEE CY - New York ER - TY - CHAP A1 - Grum, Marcus A1 - Blunk, Oliver A1 - Rojahn, Marcel A1 - Fettke, Peter A1 - Gronau, Norbert T1 - Research challenges of knowledge modelling and the outline of a research agenda T2 - Knowledge in digital age : IFKAD 2020 KW - knowledge management KW - process modelling KW - research challenges Y1 - 2020 SN - 978-88-96687-13-0 SN - 2280-787X PB - The Arts of Business Institute CY - Matera, Italy ER - TY - CHAP A1 - Grum, Marcus ED - Rutkowski, Leszek ED - Scherer, Rafał ED - Korytkowski, Marcin ED - Pedrycz, Witold ED - Tadeusiewicz, Ryszard ED - Zurada, Jacek M. T1 - Learning representations by crystallized back-propagating errors T2 - Artificial intelligence and soft computing N2 - With larger artificial neural networks (ANN) and deeper neural architectures, common methods for training ANN, such as backpropagation, are key to learning success. Their role becomes particularly important when interpreting and controlling structures that evolve through machine learning. This work aims to extend previous research on backpropagation-based methods by presenting a modified, full-gradient version of the backpropagation learning algorithm that preserves (or rather crystallizes) selected neural weights while leaving other weights adaptable (or rather fluid). In a design-science-oriented manner, a prototype of a feedforward ANN is demonstrated and refined using the new learning method. The results show that the so-called crystallizing backpropagation increases the control possibilities of neural structures and interpretation chances, while learning can be carried out as usual. Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practitioners will benefit from this interactive process because they can restrict neural learning to specific architectural components of ANN and can focus further development on specific areas of higher cognitive levels without the risk of destroying valuable ANN structures. KW - artificial neural networks KW - backpropagation KW - knowledge crystallization KW - second-order conditioning KW - cognitive levels KW - NMDL Y1 - 2023 SN - 978-3-031-42504-2 SN - 978-3-031-42505-9 U6 - https://doi.org/10.1007/978-3-031-42505-9_8 SP - 78 EP - 100 PB - Springer CY - Cham ER - TY - CHAP A1 - Bender, Benedict A1 - Grum, Marcus T1 - Gamification and dynamisation of the continous improvement processes BT - design and realization of a gamification platform for continous improvement T2 - International Conference on Electrical, Computer and Energy Technologies N2 - The idea of the continuous improvement process (CIP) helps companies to continuously improve their operation and thereby contributes to their competitiveness. Through digi tization, new potentials emerge to solve known CIP issues. This contribution specifically addresses the individual motivation of employees to contribute to the CIP. Typically, related initiatives lack contributions over time. The use of gamification is a promising way to achieve continuous participation by addressing the individual needs of participants. While the use of extrinsic motivation elements is common in practice, the idea of this approach is to specifically address intrinsic motivations which serve as a long-term motivator. This article contributes to a gam-ification concept for the continuous improvement process. The main results include an adapted CIP, a gamification concept, and a market mechanism. Furthermore, the concept is implemented and demonstrated as a prototype in an online platform. Y1 - 2021 U6 - https://doi.org/10.1109/ICECET52533.2021.9698530 SP - 1 EP - 7 PB - IEEE CY - New York 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 - Grum, Marcus A1 - Bender, Benedict A1 - Gronau, Norbert A1 - Alfa, Attahiru S. T1 - Efficient task realizations in networked production infrastructures T2 - Proceedings of the Conference on Production Systems and Logistics N2 - 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. KW - Industry 4.0 KW - CPS KW - Decentral Decision Making KW - Industrial Analytics KW - Case Study Y1 - 2020 U6 - https://doi.org/10.15488/9682 SP - 397 EP - 407 PB - publish-Ing. CY - Hannover ER - TY - CHAP A1 - Gronau, Norbert A1 - Grum, Marcus A1 - Bender, Benedict T1 - Determining the optimal level of autonomy in cyber-physical production systems T2 - IEEE 14th International Conference on Industrial Informatics (INDIN) N2 - Traditional production systems are enhanced by cyber-physical systems (CPS) and Internet of Things. A kind of next generation systems, those cyber-physical production systems (CPPS) are able to raise the level of autonomy of its production components. To find the optimal degree of autonomy in a given context, a research approach is formulated using a simulation concept. Based on requirements and assumptions, a cyber-physical market is modeled and qualitative hypotheses are formulated, which will be verified with the help of the CPPS of a hybrid simulation environment. KW - cyber-physical systems KW - hybrid simulation KW - Internet of Things KW - manufacturing systems KW - production engineering computing KW - cyber-physical production systems Y1 - 2017 U6 - https://doi.org/10.1109/INDIN.2016.7819367 SP - 1293 EP - 1299 PB - IEEE CY - New York ER - TY - CHAP A1 - Grum, Marcus ED - Shishkov, Boris T1 - Context-aware, intelligent musical instruments for improving knowledge-intensive business processes T2 - Business modeling and software design N2 - With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals. KW - business process KW - knowledge transfer KW - CPS KW - prototype Y1 - 2022 SN - 978-3-031-11509-7 SN - 978-3-031-11510-3 U6 - https://doi.org/10.1007/978-3-031-11510-3_5 VL - 453 SP - 69 EP - 88 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 - Rapp, Simon A1 - Gronau, Norbert A1 - Albers, Albert ED - Shishkov, Boris T1 - Accelerating knowledge BT - the speed optimization of knowledge transfers T2 - Business modeling and software design N2 - As knowledge-intensive processes are often carried out in teams and demand for knowledge transfers among various knowledge carriers, any optimization in regard to the acceleration of knowledge transfers obtains a great economic potential. Exemplified with product development projects, knowledge transfers focus on knowledge acquired in former situations and product generations. An adjustment in the manifestation of knowledge transfers in its concrete situation, here called intervention, therefore can directly be connected to the adequate speed optimization of knowledge-intensive process steps. This contribution presents the specification of seven concrete interventions following an intervention template. Further, it describes the design and results of a workshop with experts as a descriptive study. The workshop was used to assess the practical relevance of interventions designed as well as the identification of practical success factors and barriers of their implementation. KW - knowledge transfers KW - business process optimization KW - interventions KW - product development KW - product generation engineering KW - empirical evaluation Y1 - 2019 SN - 978-3-030-24853-6 SN - 978-3-030-24854-3 U6 - https://doi.org/10.1007/978-3-030-24854-3_7 VL - 356 SP - 95 EP - 113 PB - Springer CY - Cham ER -