The effect of work content imbalance and its interaction with scheduling method on sequential flow line performance

Theodor Freiheit, Wei Li

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Uneven workflow in serial flow lines is common when job work content varies. Unfortunately, work content imbalance between stations or between jobs degrades system performance. The effect of this imbalance can be mitigated by proper job sequencing. In this paper, we uncouple the influence of station-to-station and job-to-job imbalance within a set of jobs, introducing metrics to quantify the degree of imbalance, and determine their impact on line performance. We then examine the sensitivity of several scheduling methods at different problem scales and processing time variance levels, and compare the sensitivity to process time stability radii. Within the case studies explored, we determine that greater station imbalance can degrade solution quality regardless of problem scale and variance level. Greater job imbalance can either improve or diminish solution quality (i.e. relative performance from a given scheduling method), but less than station imbalance. Scheduling methods that sequence jobs based on the sums of processing times, e.g. SPT, can benefit from greater station imbalance. Scheduling methods that sequence jobs based on idle time between stations, e.g. the state-space heuristic, are more sensitive to station imbalance, but can also benefit from job imbalance. Finally, we conclude that job sequence has a greater impact on solution quality than stability radii.

Original languageEnglish
Pages (from-to)2791-2805
Number of pages15
JournalInternational Journal of Production Research
Volume55
Issue number10
DOIs
StatePublished - May 19 2017

Bibliographical note

Publisher Copyright:
© 2016 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • flow shop
  • imbalance
  • performance analysis
  • process time variation
  • scheduling

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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