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Agent-Based Distributed Manufacturing Process Planning and Scheduling: A State-of-the-Art Survey
Integrated Manufacturing Technologies Institute, National Research Council of Canada .ORCID iD: 0000-0001-8679-8049
2006 (English)In: IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews, ISSN 1094-6977, E-ISSN 1558-2442, Vol. 36, no 4, p. 563-577Article in journal (Refereed) Published
Abstract [en]

Manufacturing process planning is the process of selecting and sequencing manufacturing processes such that they achieve one or more goals and satisfy a set of domain constraints. Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan. It is, in fact, an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. Manufacturing process planning and scheduling are usually considered to be two separate and distinct phases. Traditional optimization approaches to these problems do not consider the constraints of both domains simultaneously and result in suboptimal solutions. Without considering real-time machine workloads and shop floor dynamics, process plans may become suboptimal or even invalid at the time of execution. Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans. After describing the complexity of the manufacturing process-planning and scheduling problems, this paper reviews the research literature on manufacturing process planning, scheduling as well as their integration, particularly on agent-based approaches to these difficult problems. Major issues in these research areas are discussed, and research opportunities and challenges are identified

Place, publisher, year, edition, pages
IEEE, 2006. Vol. 36, no 4, p. 563-577
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-206407DOI: 10.1109/TSMCC.2006.874022ISI: 000238711200014Scopus ID: 2-s2.0-80052993037OAI: oai:DiVA.org:kth-206407DiVA, id: diva2:1092436
Note

QCR 2070508

QC 20170523

Available from: 2017-05-02 Created: 2017-05-02 Last updated: 2017-11-29Bibliographically approved

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Wang, Lihui

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