Computational Experiment Research on the Equalization-Oriented Service Strategy in Collaborative Manufacturing

• Published in: IEEE transactions on services computing Vol. 11; no. 2; pp. 369 - 383
• Main Authors: Xue, Xiao, Kou, Yan-Min, Wang, Shu-Fang, Liu, Zhi-Zhong
• Format: Journal Article
• Language: English
• Published: IEEE 01.03.2018
• Subjects: Collaboration; collaborative manufacturing; computational experiment; equalization-oriented services strategy; Genetic algorithms; Heuristic algorithms; Industry 4.0; Manufacturing; Quality of service; Supply chains; Web services
• ISSN: 1939-1374; 1939-1374; 2372-0204
• DOI: 10.1109/TSC.2016.2569082

In the framework of Industry 4.0, collaborative manufacturing across different supply chains is one of the most important business models. In order to avoid the uneven distribution of service requirements among service providers (i.e., non-equalization phenomenon), a lot of service strategies with different characteristics can be taken as candidate solutions to adjust the matching between service providers and service consumers. Based on the background, how to identify the application conditions of various service strategies in complex environment has become a serious challenge in the field. To solve this problem, the computational experiment-based evaluation method is proposed in this paper, including customization of service strategy, construction of experiment system, and experiment analysis of service strategy. In this paper, three possible service strategies are built to deal with the non-equalization phenomenon, i.e., non-equalization strategy, equalization strategy, collaborative equalization strategy. Experiment results show that: collaborative equalization strategy can effectively enhance the service utilization rate and reduce the completion time in short supply environment; equalization strategy is the optimal one in oversupply market environment. This case study can show that the proposed method is feasible and the result is satisfactory.