Stability of trade-off balancing in one-stage production scheduling

Wei Li; Barrie R. Nault; Syed I. Mohsin; Youlin Huang

doi:10.1016/j.mfglet.2022.07.014

Stability of trade-off balancing in one-stage production scheduling

Wei Li, Barrie R. Nault, Syed I. Mohsin, Youlin Huang

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Production scheduling faces three challenges, which are inconsistent key performance indicators (KPIs), processing time uncertainties, and production schemes. Applying modern portfolio theory (MPT), Li et al. (2021) proposed a ToB(α) heuristic to balance trade-offs in one-stage production. However, production schemes for optimizing average performance of individual KPIs, trade-off values, or worst-case scenarios affect the stability of a process differently, especially with processing time uncertainties. We propose an innovative approach using transfer functions for stability (TF4S) in balancing trade-offs in production scheduling. Our TF4S approach provides a systematic way to analyze the stability of one-stage production and can be extended to production scheduling for classic m-machine flow lines.

Original language	English
Pages (from-to)	48-55
Number of pages	8
Journal	Manufacturing Letters
Volume	33
DOIs	https://doi.org/10.1016/j.mfglet.2022.07.014
State	Published - Sep 2022

Bibliographical note

Publisher Copyright:
© 2022

Keywords

Production scheduling
Stability
Trade-off balancing
Transfer function

ASJC Scopus subject areas

Mechanics of Materials
Industrial and Manufacturing Engineering

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10.1016/j.mfglet.2022.07.014

Cite this

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abstract = "Production scheduling faces three challenges, which are inconsistent key performance indicators (KPIs), processing time uncertainties, and production schemes. Applying modern portfolio theory (MPT), Li et al. (2021) proposed a ToB(α) heuristic to balance trade-offs in one-stage production. However, production schemes for optimizing average performance of individual KPIs, trade-off values, or worst-case scenarios affect the stability of a process differently, especially with processing time uncertainties. We propose an innovative approach using transfer functions for stability (TF4S) in balancing trade-offs in production scheduling. Our TF4S approach provides a systematic way to analyze the stability of one-stage production and can be extended to production scheduling for classic m-machine flow lines.",

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AB - Production scheduling faces three challenges, which are inconsistent key performance indicators (KPIs), processing time uncertainties, and production schemes. Applying modern portfolio theory (MPT), Li et al. (2021) proposed a ToB(α) heuristic to balance trade-offs in one-stage production. However, production schemes for optimizing average performance of individual KPIs, trade-off values, or worst-case scenarios affect the stability of a process differently, especially with processing time uncertainties. We propose an innovative approach using transfer functions for stability (TF4S) in balancing trade-offs in production scheduling. Our TF4S approach provides a systematic way to analyze the stability of one-stage production and can be extended to production scheduling for classic m-machine flow lines.

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KW - Stability

KW - Trade-off balancing

KW - Transfer function

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Stability of trade-off balancing in one-stage production scheduling

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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