An investigation of the effects of variance components on the performance of job shop dispatching policies

Abstract

The objectives of this research are twofold. First, to investigate the impact of unequal processing time variances on overall shop performance. Second, to implement strategies for improving job shop performance by designing priority dispatching policies that include measures of system statistical variability. The approach is through a statistical- experiment in which processing time variances, at specified machines, are systematically increased while holding processing means constant. The job shops modeled herein deviate from mainstream research which traditionally assumes that processing times are known prior to the implementation of the priority rules. Instead, this study examines a stochastic environment in which operation processing times are random variables from mutually independent probability distributions. It is assumed that the only information available for jobs waiting for service, are their operation processing time distribution. Hence, the priority dispatching policies examined herein are based solely on means and variances instead of exact information. A capstone of this research is the development of four new priority dispatching policies that include components of system variability. In simulated cases these four rules are compared against five commonly studied dispatching rules. The results indicate that that the four variance inclusive rules perform as well or better than the five traditional dispatching rules, in every criterion measured.