TY - GEN
T1 - Decision Support System for Joint Product Design and Reconfiguration of Production Systems
AU - Hashemi-Petroodi, S. Ehsan
AU - Gonnermann, Clemens
AU - Paul, Magdalena
AU - Thevenin, Simon
AU - Dolgui, Alexandre
AU - Reinhart, Gunther
N1 - Publisher Copyright:
© IFIP International Federation for Information Processing 2019.
PY - 2019
Y1 - 2019
N2 - Reconfigurable manufacturing systems (RMS) are designed to be able to be reconfigured to produce new items. Nevertheless, reconfigurations of a RMS may be time consuming and costly if they are not considered since early steps of new item design. This work describes a decision support system to automatically generate and test configurations for such RMSs based on a computer-aided design (CAD) model of a new product. The proposed methodology consists of two main steps. First, a matrix of possible assembly plans (taking into account resource/tool compatibility, geometric constraints, ...) is generated with a skill-based comparison between the new item and the production resources. Second, the assembly plan with minimum reconfiguration cost is found through mathematical optimization. The solution is analyzed by a simulation model in the end. Experiments performed on small use case validate the proposed methodology.
AB - Reconfigurable manufacturing systems (RMS) are designed to be able to be reconfigured to produce new items. Nevertheless, reconfigurations of a RMS may be time consuming and costly if they are not considered since early steps of new item design. This work describes a decision support system to automatically generate and test configurations for such RMSs based on a computer-aided design (CAD) model of a new product. The proposed methodology consists of two main steps. First, a matrix of possible assembly plans (taking into account resource/tool compatibility, geometric constraints, ...) is generated with a skill-based comparison between the new item and the production resources. Second, the assembly plan with minimum reconfiguration cost is found through mathematical optimization. The solution is analyzed by a simulation model in the end. Experiments performed on small use case validate the proposed methodology.
KW - CAD model
KW - Decision support system
KW - Optimization
KW - Production graph
KW - Reconfigurable manufacturing system
KW - Skill-based approach
UR - http://www.scopus.com/inward/record.url?scp=85072966462&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-30000-5_30
DO - 10.1007/978-3-030-30000-5_30
M3 - Conference contribution
AN - SCOPUS:85072966462
SN - 9783030299996
T3 - IFIP Advances in Information and Communication Technology
SP - 231
EP - 238
BT - Advances in Production Management Systems. Production Management for the Factory of the Future - IFIP WG 5.7 International Conference, APMS 2019, Proceedings
A2 - Ameri, Farhad
A2 - Stecke, Kathryn E.
A2 - von Cieminski, Gregor
A2 - Kiritsis, Dimitris
PB - Springer New York LLC
T2 - IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2019
Y2 - 1 September 2019 through 5 September 2019
ER -