Optimization models for the tool change scheduling problem

Traditional machine scheduling literature generally assumes that a machine is available at all times. Yet this assumption may not be accurate in real manufacturing systems. In many cases, a machine's tool must be changed after it has continuously worked for a period of time. This paper deals wi...

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Bibliographic Details
Published in:Omega (Oxford) Vol. 36; no. 5; pp. 888 - 894
Main Author: Chen, Jen-Shiang
Format: Journal Article
Language:English
Published: Exeter Elsevier Ltd 01.10.2008
Elsevier
Elsevier Science Publishers
Pergamon Press Inc
Series:Omega
Subjects:
Analysis
Applied sciences
Availability constraints
Exact sciences and technology
Integer programming
Job shops
Mathematical optimization
Mathematical programming
Methods
Operational research and scientific management
Operational research. Management science
Optimization
Production management
Production scheduling
Scheduling
Scheduling Tool change Integer programming Tardiness Availability constraints
Scheduling, sequencing
Studies
Tardiness
Tool change
United States
Integer programming
Scheduling
Availability constraints
Tool change
Tardiness
Availability
Production system
Work period
Replacement problem
Machining
Mixed integer programming
Continuous time
Modeling
Optimization
Delay
Tool life
Machine tool
Tool wear
Single machine
ISSN:0305-0483, 1873-5274
Online Access:Get full text
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Summary:Traditional machine scheduling literature generally assumes that a machine is available at all times. Yet this assumption may not be accurate in real manufacturing systems. In many cases, a machine's tool must be changed after it has continuously worked for a period of time. This paper deals with a single machine scheduling problem subject to tool wear, given the allowed maximum continuous working time of the machine is T L (tool life) and the tool change time is T C . Job processing and tool changes are scheduled simultaneously. In this paper, we examine this problem to minimize the total tardiness of jobs. Two mixed binary integer programming models are developed to optimally solve this problem. Computational experiments are performed to evaluate the models’ efficiency.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:0305-0483
1873-5274
DOI:10.1016/j.omega.2006.04.006