@article{ReinhardtMahdaviaslPrelletal.2024, author = {Reinhardt, Heiner and Mahdaviasl, Mahtab and Prell, Bastian and Mauersberger, Anton and Klimant, Philipp and Reiff-Stephan, J{\"o}rg and Ihlenfeldt, Steffen}, title = {Efficient data acquisition for traceability and analytics}, series = {Procedia CIRP}, volume = {122}, journal = {Procedia CIRP}, publisher = {Elsevier}, issn = {2212-8271}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-19232}, pages = {73 -- 78}, year = {2024}, abstract = {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.}, language = {en} } @article{ReinhardtMuennichPrelletal.2021, author = {Reinhardt, Heiner and M{\"u}nnich, Marc and Prell, Bastian and Arnold, Roman and Krippner, Fabian and Weber, Marek and Seifert, Frank and Putz, Matthias}, title = {Retrieving properties of manufacturing systems from traceability data for performance evaluation and material flow simulation}, series = {Procedia CIRP}, volume = {104}, journal = {Procedia CIRP}, publisher = {Elsevier}, issn = {2212-8271}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-15600}, pages = {20 -- 25}, year = {2021}, abstract = {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.}, language = {en} } @article{ReinhardtBogdanowArnoldetal.2025, author = {Reinhardt, Heiner and Bogdanow, Boran and Arnold, Roman and Prell, Bastian and Klimant, Philipp and Seifert, Frank and Mahdaviasl, Mahtab and Ihlenfeldt, Steffen}, title = {Objective validation for short-term material flow simulation}, series = {Procedia CIRP}, volume = {134}, journal = {Procedia CIRP}, publisher = {Elsevier}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20554}, pages = {526 -- 531}, year = {2025}, abstract = {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.}, language = {en} } @article{ReinhardtBogdanowArnoldetal.2025, author = {Reinhardt, Heiner and Bogdanow, Boran and Arnold, Roman and Prell, Bastian and Klimant, Philipp and Seifert, Frank and Mahdaviasl, Mahtab and Ihlenfeldt, Steffen}, title = {Subjective validation for short-term material flow simulation}, series = {Procedia CIRP}, volume = {134}, journal = {Procedia CIRP}, publisher = {Elsevier}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20576}, pages = {562 -- 566}, year = {2025}, abstract = {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.}, language = {en} }