Please use this identifier to cite or link to this item: https://doi.org/10.1080/002075400411420
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dc.titleA simulated annealing-based optimization algorithm for process planning
dc.contributor.authorMa, G.H.
dc.contributor.authorZhang, Y.F.
dc.contributor.authorNee, A.Y.C.
dc.date.accessioned2014-06-17T05:07:52Z
dc.date.available2014-06-17T05:07:52Z
dc.date.issued2000-08-15
dc.identifier.citationMa, G.H., Zhang, Y.F., Nee, A.Y.C. (2000-08-15). A simulated annealing-based optimization algorithm for process planning. International Journal of Production Research 38 (12) : 2671-2687. ScholarBank@NUS Repository. https://doi.org/10.1080/002075400411420
dc.identifier.issn00207543
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/57833
dc.description.abstractComputer-aided process planning (CAPP) in the past typically employed knowledge-based approaches, which are only capable of generating a feasible plan for a given part based on invariable machining resources. In the field of concurrent engineering, there is a great need for process planning optimization. This paper describes an approach that models the constraints of process planning problems in a concurrent manner. It is able to generate the entire solution space by considering multiple planning tasks, i.e. operations (machine, tool and tool approach direction), selection and operations sequencing simultaneously. Precedence relationships among all the operations required for a given part are used as the constraints for the solution space. The relationship between an actual sequence and the feasibility of applying an operation is also considered. An algorithm based on simulated annealing (SA) has been developed to search for the optimal solution. Several cost factors including machine cost, tool cost, machine change cost, tool change cost and set-up change cost can be used flexibly as the objective function. The case study shows that the algorithm can generate highly satisfying results.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/002075400411420
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentMECHANICAL & PRODUCTION ENGINEERING
dc.description.doi10.1080/002075400411420
dc.description.sourcetitleInternational Journal of Production Research
dc.description.volume38
dc.description.issue12
dc.description.page2671-2687
dc.description.codenIJPRB
dc.identifier.isiut000088569200007
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