Analyzing the Impact of Workload Norms and Order Fill Rate on Job Shop Performance

Abstract

The Garment manufacturing industry is facing several challenges in meeting its customer requirements due to uncertainties associated with production. Varieties of products that include many components to be produced on different machines having variations in terms of due dates and labour productivity which would make the job shop complicated for scheduling. Hence, an investigation is necessary to evaluate the influence of above underlying factors on the shop’s performance. The conceptual model was initially developed, that represents the problem entity followed by the development of a simulation model on a discrete event simulation platform. The resource capacity, process timings and other related data required for feeding the model were collected through process observation techniques. The model was then validated by conducting sensitivity analysis for evaluating the model structure, logic, and causal relationships. Artificial scenarios were generated to experiment with the model performance that mimics real time situations in terms of varying the fill rate and workload norms at distinct levels. Effectiveness of order release policies and priority dispatching rules were monitored by conducting 90 experiments determined through design of experiments. Influence of the workload control methods were evaluated through Analysis of Variance techniques to understand the percentage contribution of each variable on performance. The influence of these variables on different output measures was evaluated through Tukey tests. The experimentation revealed that flowtime is influenced to the extent of 59.72 percent by workload norms and order release methods have 59.2 percent influence on throughput.