Cost performance of simple priority rule combinations

Abstract

PurposeSeveral prior studies have investigated the strategy of concurrently deploying different priority rules at different processing stages of a manufacturing system. The purpose of this paper is to investigate the advantage of using such a strategy over that of using priority rules in their pure forms.Design/methodology/approachThree priority rules were combined in all possible ways in a simulated, three‐stage, flow‐dominated manufacturing system. The performances of these combinations, along with three other simple priority rules in their pure forms, were compared using both mean and variability in waiting, earliness, tardiness, and total costs under two shop load levels and several tardiness to earliness cost ratios.FindingsThe results indicate that the combinations between SIX and shortest processing time (SPT) rules perform well in reducing both mean and variability of waiting cost but do poorly on tardiness cost. On the other hand, the due date rule in its pure form or in conjunction with SIX or SPT is effective in reducing both mean and variability of both earliness and tardiness costs. While tardiness cost appears to dominate the total cost data, the shop load level registered little impact on the performance of the combination schemes.Research limitations/implicationsThe results of the paper have useful practical implications for textile and ceramic industries. However, the conclusions are limited to the cost structure used, although a wide range of cost ratios is included.Originality/valueThe paper offers insights into whether throughput and due date‐related costs can be reduced by using a job sequencing strategy that simultaneously deploys different priority rules at different processing stages of a manufacturing environment.