Effect of forecast errors on rolling horizon master production schedule cost performance for various replanning intervals

Ray Venkataraman, Jay Nathan

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Master production schedules are usually updated by the use of a rolling schedule. Previous studies on rolling schedules seem to form the consensus that frequent replanning of a master production schedule (MPS) can increase costs and schedule instability. Building on previous research on rolling schedules, this study addresses the impact of overestimation or underestimation of demand on the rolling horizon MPS cost performance for various replanning frequencies. The MPS model developed in this paper is based on actual data collected from a paint company. Results indicate that under both the forecast errors conditions investigated in this study, a two- replanning interval provided the best MPS cost performance for this company environment. However, results from the sensitivity analysis performed on the MPS model indicate that when the setup and inventory carrying costs are high, a 1- month replanning frequency (frequent replanning) seems more appropriate for both of the above forecast error scenarios.

Original languageEnglish (US)
Pages (from-to)682-689
Number of pages8
JournalProduction Planning and Control
Volume10
Issue number7
DOIs
StatePublished - Jan 1999

Fingerprint

Costs
Paint
Sensitivity analysis
Rolling horizon
Schedule
Forecast error
Industry

All Science Journal Classification (ASJC) codes

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

Cite this

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abstract = "Master production schedules are usually updated by the use of a rolling schedule. Previous studies on rolling schedules seem to form the consensus that frequent replanning of a master production schedule (MPS) can increase costs and schedule instability. Building on previous research on rolling schedules, this study addresses the impact of overestimation or underestimation of demand on the rolling horizon MPS cost performance for various replanning frequencies. The MPS model developed in this paper is based on actual data collected from a paint company. Results indicate that under both the forecast errors conditions investigated in this study, a two- replanning interval provided the best MPS cost performance for this company environment. However, results from the sensitivity analysis performed on the MPS model indicate that when the setup and inventory carrying costs are high, a 1- month replanning frequency (frequent replanning) seems more appropriate for both of the above forecast error scenarios.",
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