TY - GEN
T1 - Modeling and analyzing the material flow of crowdsourcing processes in cloud-based manufacturing systems using stochastic petri nets
AU - Wu, Dazhong
AU - Rosen, David W.
AU - Schaefer, Dirk
N1 - Publisher Copyright:
Copyright © 2014 by ASME.
PY - 2014
Y1 - 2014
N2 - Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, has the potential to allow manufacturing enterprises to be rapidly scaled up and down by crowdsourcing manufacturing tasks or sub-tasks. To improve the efficiency of the crowdsourcing process, the material flow of CBM systems needs to be managed so that several manufacturing processes can be executed simultaneously. Further, the scalability of manufacturing capacity in CBM needs to be designed, analyzed, and planned in response to rapidly changing market demands. The objective of this paper is to introduce a stochastic petri nets (SPNs)-based approach for modeling and analyzing the concurrency and synchronization of the material flow in CBM systems. The proposed approach is validated through a case study of a car suspension module. Our results have shown that the SPN-based approach helps analyze the structural and behavioral properties of a CBM system and verify manufacturing performance.
AB - Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, has the potential to allow manufacturing enterprises to be rapidly scaled up and down by crowdsourcing manufacturing tasks or sub-tasks. To improve the efficiency of the crowdsourcing process, the material flow of CBM systems needs to be managed so that several manufacturing processes can be executed simultaneously. Further, the scalability of manufacturing capacity in CBM needs to be designed, analyzed, and planned in response to rapidly changing market demands. The objective of this paper is to introduce a stochastic petri nets (SPNs)-based approach for modeling and analyzing the concurrency and synchronization of the material flow in CBM systems. The proposed approach is validated through a case study of a car suspension module. Our results have shown that the SPN-based approach helps analyze the structural and behavioral properties of a CBM system and verify manufacturing performance.
UR - http://www.scopus.com/inward/record.url?scp=84908876753&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84908876753&partnerID=8YFLogxK
U2 - 10.1115/MSEC2014-3907
DO - 10.1115/MSEC2014-3907
M3 - Conference contribution
AN - SCOPUS:84908876753
T3 - ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference
BT - ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference
PB - Web Portal ASME (American Society of Mechanical Engineers)
T2 - ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference
Y2 - 9 June 2014 through 13 June 2014
ER -