Selecting a flexible manufacturing system using multiple criteria analysis

A visual interactive decision support framework designed to aid the decision-maker, typically top management, in selecting the most appropriate technology and design when planning a flexible manufacturing system (FMS) is described. The framework can be used in the preinvestment stage of the planning process, after the decision in principle has been made to build an FMS. First, both qualitative and quantitative criteria are used to narrow the set of alternative system configurations under consideration down to a small number of most attractive candidates. After this prescreening phase, a multiobjective programming model is formulated for each remaining configuration, allowing the manager to explore and evaluate the costs and benefits of various different scenarios for each configuration separately by experimenting with different levels of batch sizes and production volumes. The system uses visual interaction with the decision-maker, graphically displaying the relevant trade-offs between such relevant perfo...

[1]  Abraham Seidmann,et al.  Performance evaluation of flexible manufacturing systems , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  M. Ollus,et al.  Flexible production automation and computer integrated manufacturing: recent trends in Finland , 1988 .

[3]  R. S. Laundy,et al.  Multiple Criteria Optimisation: Theory, Computation and Application , 1989 .

[4]  K. Toikka,et al.  FMS-DESIGN FROM THE POINT OF VIEW OF IMPLEMENTATION — RESULTS OF A CASE STUDY , 1988 .

[5]  Cynthia K. Whitney.  Control Principles in Flexible Manufacturing , 1984, 1984 American Control Conference.

[6]  Pekka Korhonen,et al.  A Visual Interactive Method for Solving the Multiple-Criteria Problem , 1986 .

[7]  Andrzej P. Wierzbicki,et al.  Theory, Software and Testing Examples for Decision Support Systems , 1987 .

[8]  Pekka Korhonen,et al.  A pareto race , 1988 .

[9]  J. Granat,et al.  IAC-DIDAS-N A Dynamic Interactive Decision Analysis and Support System for Multicriteria Analysis of Nonlinear Models , 1988 .

[10]  Jack R. Meredith,et al.  Managing factory automation projects , 1987 .

[11]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[12]  Andrzej P. Wierzbicki,et al.  Aspiration Based Decision Support Systems , 1989 .

[13]  R. Kuivanen,et al.  Disturbances in Flexible Manufacturing , 1988 .

[14]  Roger N. Wabalickis.  Justification of FMS with the analytic hierarchy process , 1988 .

[15]  J. A. Buzacott,et al.  Flexible manufacturing systems: a review of analytical models , 1986 .

[16]  Thomas L. Saaty,et al.  Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World , 1982 .

[17]  J. Ranta,et al.  Interactive Analysis of FMS Productivity and Flexibility , 1988 .

[18]  Jukka Ranta,et al.  A Non-linear Multi-criteria Model for Strategic FMS Selection Decisions , 1992 .

[19]  Stanley Gershwin,et al.  A control theorist's perspective on recent trends in manufacturing systems , 1984, The 23rd IEEE Conference on Decision and Control.

[20]  A. Wierzbicki.  A Mathematical Basis for Satisficing Decision Making , 1982 .

[21]  Janusz Majchrzak.  DISCRET An Interactive Decision Support System for Discrete Alternatives Multicriteria Problems , 1989 .

[22]  P. Korhonen,et al.  A multiple criteria model for pricing alcoholic beverages , 1988 .

[23]  R. Jaikumar.  Postindustrial manufacturing , 1986 .

[24]  Jack R. Meredith,et al.  Implementing the automated factory , 1987 .