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

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

2 Scopus citations

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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title = "Stability of trade-off balancing in one-stage production scheduling",

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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AU - Li, Wei

AU - Nault, Barrie R.

AU - Mohsin, Syed I.

AU - Huang, Youlin

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Y1 - 2022/9

N2 - 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.

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.

KW - Production scheduling

KW - Stability

KW - Trade-off balancing

KW - Transfer function

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EP - 55

JO - Manufacturing Letters

JF - Manufacturing Letters

ER -

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

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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