A multiple-criteria approach to machine selection for flexible manufacturing systems
Identifieur interne : 002D56 ( Main/Exploration ); précédent : 002D55; suivant : 002D57A multiple-criteria approach to machine selection for flexible manufacturing systems
Auteurs : San Myint [Thaïlande] ; Mario T. Tabucanon [Thaïlande]Source :
- International Journal of Production Economics [ 0925-5273 ] ; 1993.
Abstract
This paper describes a visual interactive decision support framework designed to aid decision makers in selecting the most appropriate machines for a flexible manufacturing system (FMS). The framework can be used in the preinvestment stage of the planning process, after a decision has been made, in principle, to build an FMS. The framework mainly consists of two parts. The first part is called the prescreening stage, which narrows down all possible configurations by using the analytic hierarchy process (AHP). The second part uses a goal programming (GP) model to find out the satisfactory candidate from the remaining shortlisted configuration. After applying the GP model, AH P is used again for sensitivity analysis. This approach helps managers explore and evaluate costs and benefits of various scenarios for each configuration separately by experimenting with different types of machines and degrees of flexibility of the system.
Url:
DOI: 10.1016/0925-5273(94)90125-2
Affiliations:
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<front><div type="abstract" xml:lang="en">This paper describes a visual interactive decision support framework designed to aid decision makers in selecting the most appropriate machines for a flexible manufacturing system (FMS). The framework can be used in the preinvestment stage of the planning process, after a decision has been made, in principle, to build an FMS. The framework mainly consists of two parts. The first part is called the prescreening stage, which narrows down all possible configurations by using the analytic hierarchy process (AHP). The second part uses a goal programming (GP) model to find out the satisfactory candidate from the remaining shortlisted configuration. After applying the GP model, AH P is used again for sensitivity analysis. This approach helps managers explore and evaluate costs and benefits of various scenarios for each configuration separately by experimenting with different types of machines and degrees of flexibility of the system.</div>
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