|Title:||Industrial Application of a MDM-Based Approach for Generation and Impact Analysis of Adaptation Options-a Case Study||Authors:||Hoang, Xuan-Luu
|Language:||eng||Keywords:||Adaptation Options;Change Impact Analysis;Flexibility;Manufacturing Machines;Modernization||Subject (DDC):||620 Ingenieurwissenschaften||Issue Date:||22-Oct-2018||Publisher:||IEEE||Document Type:||Conference Proceedings||Page Start:||1244||Page End:||1247||Published in (Book):||2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)||Publisher Place:||Piscataway||Conference:||IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), 04-07 September 2018, Turin, Italy||Abstract:||
Global trends in manufacturing urge existing machines to become more flexible, as the production environment becomes increasingly dynamic. In order to attain this 'flexibilization', existing machines have to be adapted during their operational phase, i.e. mechanical changes, changes of sensors and actuators, software changes, or a combination thereof have to be performed. The adaptation of existing machines is a complicated and time-consuming process, as various interdependencies have to be considered. Therefore, a systematic approach for generating adaptation options is crucial for a successful adaptation of machines. State-of-the-art approaches primarily focus on the adaptation of products and, thus, are not appropriate for manufacturing machines. Accordingly, this paper presents an approach for the generation of adaptation options to support the adaptation of manufacturing machines. Furthermore, a use case study is presented and discussed, where the approach is applied to an industrial manufacturing machine. Here, the results demonstrated that the approach is applicable for an industrial manufacturing machine and can automatically generate valid adaptation options.
|Organization Units (connected with the publication):||Automatisierungstechnik||ISBN:||9781538671085||ISSN:||19460740||Publisher DOI:||10.1109/ETFA.2018.8502460|
|Appears in Collections:||3 - Reported Publications|
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