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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Veröffentlicht in:Omega (Oxford) Jg. 36; H. 5; S. 888 - 894
1. Verfasser: Chen, Jen-Shiang
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Sprache:Englisch
Veröffentlicht: Exeter Elsevier Ltd 01.10.2008
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Abstract 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.
AbstractList 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.sub.L] (tool life) and the tool change time is [T.sub.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. Keywords: Scheduling; Tool change; Integer programming; Tardiness; Availability constraints
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^sub L^ (tool life) and the tool change time is T^sub 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. [PUBLICATION ABSTRACT]
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 TL (tool life) and the tool change time is TC. 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.
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.
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.sub.L] (tool life) and the tool change time is [T.sub.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.
Audience Trade
Academic
Author Chen, Jen-Shiang
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  email: jschen@cc.fec.edu.tw, jschenc@ms25.hinet.net
  organization: Department of Industrial and Business Management, Far East College, 49 Junghua Road, Shinshr Shiang, Tainan 744, Taiwan, ROC
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Cites_doi 10.1007/BF01580393
10.1016/S0305-0548(02)00074-6
10.1016/S0377-2217(03)00232-7
10.1057/palgrave.jors.2600791
10.1002/nav.10045
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Issue 5
Keywords 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
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Snippet Traditional machine scheduling literature generally assumes that a machine is available at all times. Yet this assumption may not be accurate in real...
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SubjectTerms 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
Title Optimization models for the tool change scheduling problem
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