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dc.contributor.authorPerera, Terrence
dc.contributor.authorLiyanage, Kapila
dc.date.accessioned2017-01-05T11:56:30Z
dc.date.available2017-01-05T11:56:30Z
dc.date.issued2000-02
dc.identifier.citationPerera, T. and Liyanage, K. (2000) 'Methodology for rapid identification and collection of input data in the simulation of manufacturing systems', Simulation Practice and Theory, 7 (7):645.en
dc.identifier.issn09284869
dc.identifier.doi10.1016/S0928-4869(99)00020-8
dc.identifier.urihttp://hdl.handle.net/10545/621222
dc.description.abstractComputer simulation is a well-established decision support tool in the manufacturing industry. The rapid development and deployment of simulation models however, are inhibited by factors such as inefficient data collection, lengthy model documentation, and poorly planned experimentation. Typically, more than one third of project time is spent on identification, collection, validation, and analysis of input data. Whilst most research work has been focused on statistical techniques for data analysis, less attention has been paid to the development of systematic approaches to input data gathering. This paper presents a methodology for rapid identification and collection of input data in batch manufacturing environments. A functional module library and a reference data model, both developed using the IDEF (Integrated computer aided manufacturing DEFinition) family of constructs, are the core elements of the methodology. The paper also identifies the major causes behind the inefficient collection of data.
dc.description.sponsorshipN/Aen
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0928486999000208en
dc.rightsArchived with thanks to Simulation Practice and Theoryen
dc.subjectSimulationen
dc.subjectInput data modellingen
dc.subjectIntegrated computer aided manufacturing definitionen
dc.titleMethodology for rapid identification and collection of input data in the simulation of manufacturing systemsen
dc.typeArticleen
dc.contributor.departmentSheffield Hallam Universityen
dc.identifier.journalSimulation Practice and Theoryen
html.description.abstractComputer simulation is a well-established decision support tool in the manufacturing industry. The rapid development and deployment of simulation models however, are inhibited by factors such as inefficient data collection, lengthy model documentation, and poorly planned experimentation. Typically, more than one third of project time is spent on identification, collection, validation, and analysis of input data. Whilst most research work has been focused on statistical techniques for data analysis, less attention has been paid to the development of systematic approaches to input data gathering. This paper presents a methodology for rapid identification and collection of input data in batch manufacturing environments. A functional module library and a reference data model, both developed using the IDEF (Integrated computer aided manufacturing DEFinition) family of constructs, are the core elements of the methodology. The paper also identifies the major causes behind the inefficient collection of data.


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