TY - JOUR A1 - Reinhardt, Heiner A1 - Mahdaviasl, Mahtab A1 - Prell, Bastian A1 - Mauersberger, Anton A1 - Klimant, Philipp A1 - Reiff-Stephan, Jörg A1 - Ihlenfeldt, Steffen T1 - Efficient data acquisition for traceability and analytics JF - Procedia CIRP N2 - Implementing processes for traceability is required in various industries to assure product quality during manufacturing, provide evidence on required processing conditions or facilitate product recalls. Commonly, radio-frequency identification (RFID) or code recognition techniques (e.g. Data Matrix) are applied to track the flow of workpieces through a manufacturing system and link processing data accordingly. Although the analysis of tracking data is well-examined, we still see a gap in the research on the trade-off between data acquisition, data analytics and data quality. Here, we present a framework to increase the value of existing data by enabling data analytics while addressing common pitfalls and reducing the costs of data management. KW - identification KW - knowledge management KW - manufacturing system KW - process control KW - quality assurance KW - sustainable development KW - decision making KW - complexity KW - analysis KW - design Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-19232 SN - 2212-8271 VL - 122 SP - 73 EP - 78 PB - Elsevier ER - TY - JOUR A1 - Prell, Bastian A1 - Reinhardt, Heiner A1 - Mauersberger, Anton A1 - Rauscher, Alexander A1 - Reiff-Stephan, Jörg A1 - Ihlenfeldt, Steffen T1 - A survey on sustainability approaches in manufacturing JF - Procedia CIRP N2 - Awareness about climate change has led to policies and regulations but also customer preferences favoring sustainable production. Thus, producing businesses are confronted by this, as they consume a large share of resources. Therefore, when producing, additional dimensions beyond commercial feasibility ought to be considered. Here, literature on sustainability from the field of engineering science is systematically searched and analyzed for approaches leading to actual recommendations for action. Hence, this bottom-up approach, incorporating the production engineers’ point of view, represents an inside view of how the topic of sustainability has arrived at production companies. The focus on commercial feasibility ensures high relevance to practice, as production needs to become both sustainable and competitive. Even though exemplary collections of different approaches addressing the topic of sustainability in production can be found in literature, novelty is provided by the structured manner literature was collected and the special focus on approaches leading to practice-relevant recommendations for action. Thus, a comprehensive overview of approaches applicable to the manufacturing domain is presented. KW - eco-design methodology KW - economics KW - environment(al) KW - innovation management KW - manufacturing KW - production KW - sustainable development Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-17527 SN - 2212-8271 VL - 116 SP - 101 EP - 106 PB - Elsevier ER - TY - JOUR A1 - Reinhardt, Heiner A1 - Münnich, Marc A1 - Prell, Bastian A1 - Arnold, Roman A1 - Krippner, Fabian A1 - Weber, Marek A1 - Seifert, Frank A1 - Putz, Matthias T1 - Retrieving properties of manufacturing systems from traceability data for performance evaluation and material flow simulation JF - Procedia CIRP N2 - The operation of manufacturing systems is increasingly accompanied by data-driven continuous improvement processes and product traceability is required. Commonly, radio-frequency identification (RFID) technology is applied to track the flow of a uniquely-identifiable workpiece along various stations or waypoints within a factory. Based on an automotive use case, this paper describes how to analyze the resulting traceability data in order to identify several properties of a manufacturing system. The acquired knowledge can support performance evaluation and facilitate model building for material flow simulation as a foundation for digital twins and cyber-physical production systems. KW - knowledge management KW - algorithm KW - analysis KW - condition monitoring KW - manufacturing system KW - complexity KW - man-machine system KW - pattern recognition Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-15600 SN - 2212-8271 VL - 104 SP - 20 EP - 25 PB - Elsevier ER - TY - JOUR A1 - Reinhardt, Heiner A1 - Bogdanow, Boran A1 - Arnold, Roman A1 - Prell, Bastian A1 - Klimant, Philipp A1 - Seifert, Frank A1 - Mahdaviasl, Mahtab A1 - Ihlenfeldt, Steffen T1 - Objective validation for short-term material flow simulation JF - Procedia CIRP N2 - Material flow simulation, by means of discrete event simulation (DES), is utilized in various industries to support production planning and control. This is due to the fact that changes to manufacturing systems and production strategies can be virtually examined before actual implementation. Since the manual development and repeated adjustment of simulation models is time-consuming and error-prone, numerous studies suggest computerized model generation and synchronization. However, validation of such generated or synchronized models is rarely considered. Here, we present an extendible objective validation technique for the repeated short-term simulation of a generated model. To illustrate this, the technique is applied to a high-volume automotive production line and a series of simulation cycles. KW - digital twin KW - simulation KW - quality KW - optimization KW - manufacturing system KW - control KW - analysis Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-20554 VL - 134 SP - 526 EP - 531 PB - Elsevier ER - TY - JOUR A1 - Reinhardt, Heiner A1 - Bogdanow, Boran A1 - Arnold, Roman A1 - Prell, Bastian A1 - Klimant, Philipp A1 - Seifert, Frank A1 - Mahdaviasl, Mahtab A1 - Ihlenfeldt, Steffen T1 - Subjective validation for short-term material flow simulation JF - Procedia CIRP N2 - Material flow simulation, by means of discrete event simulation (DES), is frequently applied to support decision-making in production planning and control. However, manual modeling can be time-consuming and error-prone. Hence, numerous studies propose the automation of model generation and synchronization to overcome these challenges. However, in this context, validation techniques are rarely addressed. Therefore, we introduce a subjective validation technique for short-term material flow simulation based on a coherent methodology for data acquisition and visualization. The methodology is utilized to evaluate the outcome of an approach for computerized model generation and simulation. By means of an industrial use case, we hypothesize the causes for the deviation between the operation of a manufacturing system and the simulation of its generated virtual companion. KW - digital twin KW - simulation KW - quality KW - optimization KW - manufacturing system KW - control KW - analysis Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-20576 VL - 134 SP - 562 EP - 566 PB - Elsevier ER -