Manufacturing services scheduling with supply-demand dual dynamic uncertainties toward industrial internet platforms

Ying Cheng, Yifan Xie, Dongxu Wang, Fei Tao, Ping Ji

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

As a series of industrial Internet platforms have been launched, manufacturing facilities in physical world, although distributed in different enterprises, are interconnected as the form of manufacturing services (MSs) in cyber space. In this context, it makes possible for on-demand sharing of MSs as well as corresponding cross-enterprise collaboration. However, many dynamic uncertainties of both MSs and the submitted demands occur unpredictably, which seriously hinders the application of the platforms. To cope with the problem of MSs scheduling with supply-demand dual dynamic uncertainties, a three-stage approach based on an evolutionary hypernetwork model is proposed. In which, six of nine kinds of dynamic events and eighteen specific conditions are considered, and an event-condition-act mechanism is designed to guide local/global re-scheduling if needed. Experimental results show the effectiveness of the proposed approach, as well as the potential of a platform employing the approach in response to different dynamic events in its application.
Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Industrial Informatics
DOIs
Publication statusPublished - 22 Jun 2020

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