Output maximization of a CIM system: Simulation and statistical approach

Computer simulation is one of the most popular and frequently used techniques among the various management science problem-solving tools. Simulation has often been used either to describe the behaviour of a manufacturing system or to compare several alternate configurations of the system. In this paper, the authors use simulation and statistical experimental design methods for providing normative solutions. They investigated a computer-integrated manufacturing system of an automated printed circuit board manufacturing plant. Owing to the complexity of the manufacturing system, simulation is employed for analysis. The goal of this study is to determine what impact each individual input variable has on the output rate, what settings of the system factors will yield maximum output, and how to make the simulation practicable when multiple variables and complex manufacturing environment are involved. In solving this problem, the authors adopt the fractional factorial design method to reduce the number of experiments and to reduce the computer run time. The effect of input variables on the system performance was evaluated. Using the response surface methodology, the authors obtain a near optimal solution for maximizing the production output of the computer-integrated manufacturing system.