Taguchi Method to Analyze the Impacts of Commonalities in Multistage Production under Bottleneck and Uncertainty: An Overview

This chapter aims to measure the individual and combined impacts of common components and
machines in manufacturing, under bottleneck and uncertain conditions. Simulation models have
developed for multiple products, multi-period and multistage dependent demand system based on a
live case from a Malaysian company. Machine breakdown and quality variation have incorporated in
the models to create uncertainty. The delivery performances like (i) throughput of the finished
products, (ii) average production time and (iii) work-in-progress (WIP) in the system for different
experimental scenarios have examined. Taguchi approaches for orthogonal array were employed in
designing experiments and these were executed in WITNESS, a simulation modeling software. The
models corroborated historical data from the company by face validity. It was determined that batch
size of 12 in bottleneck, 2 common components and 4 common machines ensure the best outcomes
of the system under the storm of uncertainties. The focus of this chapter is determination of the best
batch size in bottleneck point under uncertainties, commonalities (components and machines) and
capacity constraint.