Manufacturing Service Composition Method Based on Service Weighted Synergy Network

doi:10.3901/JME.2018.16.070

Abstract

Abstract: In order to solve the problems that resources translation, information handoff and knowledge sharing widely exist in the complex manufacturing business process and ensure the efficient task implementation, a manufacturing service composition method based on weighted synergy network is proposed, where collaboration capacity is a key index for service competence evaluation and selection. Based on big data analysis of service interaction and cooperation in cloud platform, synergy effect can be measured and obtained through the weighted aggregation of social relationship strength, and then service weighted synergy network is naturally constructed. Hence, a muti-objective optimization model of manufacturing service selection for highest overall QoS and synergy effect is put forward. Applying two-way learning, population update and group interaction based speed update mechanism, a improved GSA algorithm is built to solve the model. Through the simulation experiment of intelligent automobile cloud manufacturing, the validity of our model and algorithm is verified, and the optimal service scheme in line with the actual manufacturing situation is obtained finally.

Key words: improved GSA, service composition, service social network, synergy effect

CLC Number:

TP393

REN Lei, REN Minglun. Manufacturing Service Composition Method Based on Service Weighted Synergy Network[J]. Journal of Mechanical Engineering, 2018, 54(16): 70-78.

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