A comparative analysis of sequencing procedures for mixed-model assembly lines in a just-in-time production system
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
In this paper several procedures for sequencing products on a mixed-model assembly line in a just-in-time production system are statistically compared using simulation analysis. The procedures include two 'goal chasing' heuristics developed at Toyota that focus on constant component usage, an algorithm developed by Miltenberg designed to achieve uniform production rates for each model, a time spread method developed by the authors that smooths the work load at each assembly line station, and the familiar batch sequencing procedure frequently used in practice. These five sequencing procedures are evaluated according to four measures of assembly line inefficiency, work not completed, worker idleness, worker station time and a measure of variability in uniform component usage. The results provide assembly line managers with guidelines for selecting the most effective sequencing procedure for achieving their operational objectives.
