Polynomial metamodelling and Taguchi designs in simulation with application to the maintenance float system

Abstract This paper presents a new approach to modeling maintenance float systems via simulation. A regression metamodel is developed and applied in a decision framework. In order to derive the metamodel, Taguchi's design technique is used to identify the appropriate design for the controllable factors. Each factor is studied at three levels in order to consider both its linear and quadratic effects on the dependent variable, the average equipment utilization (EU). A polynomial regression method is used to determine the significant factors. The procedure offers an expedient method for solving complex production problems.

[1]  Linda Weiser Friedman,et al.  The Metamodel in Simulation Analysis: Can It Be Trusted? , 1988 .

[2]  Christian N. Madu,et al.  Coefficient of variation: A critical factor in maintenance float policy , 1990, Comput. Oper. Res..

[3]  Christian N. Madu.  Simulation in manufacturing: A regression metamodel approach , 1990 .

[4]  Jack P. C. Kleijnen,et al.  Experimental design and regression analysis in simulation : An FMS case study , 1988 .

[5]  Henry P. Wynn,et al.  Quality through design : experimental design, off-line quality control and Taguchi's contributions , 1991 .

[6]  Christian N. Madu.  An economic design for optimum maintenance float policy , 1990 .

[7]  Christian N. Madu,et al.  Maintenance float policy estimation with imperfect information , 1989 .

[8]  W. Lewis,et al.  Reliability analysis based on the Weibull distribution: an application to maintenance float factors , 1983 .

[9]  T. R. Bement,et al.  Taguchi techniques for quality engineering , 1995 .

[10]  Richard M. Soland,et al.  A Closed Queueing Network Model for Multi-Echelon Repairable Item Provisioning. , 1983 .

[11]  C. Ireland.  Fundamental concepts in the design of experiments , 1964 .

[12]  Christian N. Madu.  A Closed Queueing Maintenance Network with Two Repair Centres , 1988 .

[13]  J. Kleijnen.  Screening Designs for Poly-Factor Experimentation , 1975 .

[14]  Christian N. Madu,et al.  Waiting Line Effects in Analytical Maintenance Float Policy , 1988 .

[15]  Christian N. Madu.  The study of a maintenance float model with gamma failure distribution , 1987 .

[16]  Christian N. Madu.  Determination of maintenance floats using Buzen's algorithm , 1988 .

[17]  J. Kleijnen.  Statistical tools for simulation practitioners , 1986 .