Abstract

This paper addresses the problem of computing the optimal parameters
for production control policies in the glass manufacturing industry,
providing a framework of analysis  related with the structure of the
production policies. We  consider a multi-product,  multi-stage, and
capacitated  discrete-time  production-inventory  system with random
yield. The optimal parameters for  a given production control policy
are determined in  order to  minimize  the expected costs or reach a
given  service  level. Three  different  production  strategies  are
discussed:  Make-to-Order (MTO),  Make-to-Stock (MTS),  and Delayed-
Differentiation (DD).  We use real data  from a glass  manufacturing
company, providing the evaluation of the relative performance of the
different strategies. The approach used to analyze this problem will
be simulation based optimization and gradient estimates are obtained
through Infinitesimal  Perturbation Analysis  (IPA). The simulation-
optimization package (SimulGLASS for Windows) was developed in order
to provide a tool for production decision support. Given the demand,
yield  and cost  structures, the  machines capacity,  the processing
times (and other issues inherent to the glass manufacturing process)
the   application   returns,   for  a  fixed  policy,  not only  the
recommended  inventory levels in order  to minimize total  cost, but
also the corresponding service level.