Probability Evaluation Models of Product Disassembly Cost Subject to Random Removal Time and Different Removal Labor Cost

Disassembly is a systematic method to separate an end-of-life product into its constituent parts and components. However, the disassembly process of products can experience great uncertainty due to a variety of unpredictable factors. To deal with such uncertainty, this work proposes a novel probabil...

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Bibliographic Details
Published in:IEEE transactions on automation science and engineering Vol. 9; no. 2; pp. 288 - 295
Main Authors: Tian, Guangdong, Zhou, MengChu, Chu, Jiangwei, Liu, Yumei
Format: Journal Article
Language:English
Published: Piscataway, NJ IEEE 01.04.2012
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm
Algorithms
Analytical models
Applied sciences
Computational modeling
disassembly
disassembly planning
Exact sciences and technology
Mechanical engineering. Machine design
modeling and simulation
Planning
Probabilistic logic
Probability
Production costs
Simulation
Stochastic processes
Time factors
Uncertainty
Engineering design
modeling and simulation
Life cycle
Costs
Uncertain system
Probabilistic approach
disassembly
disassembly planning
Planning
Desassembly
Modeling
Algorithm
ISSN:1545-5955, 1558-3783
Online Access:Get full text
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Summary:Disassembly is a systematic method to separate an end-of-life product into its constituent parts and components. However, the disassembly process of products can experience great uncertainty due to a variety of unpredictable factors. To deal with such uncertainty, this work proposes a novel probability analysis method of disassembly cost with random removal time and different removal labor cost. According to different constraints and actual execution of disassembly, it presents typical probability evaluation models of disassembly cost. Moreover, a solution algorithm based on stochastic simulation is used to solve the proposed probability models. Some numerical examples are given to illustrate the proposed concepts and the effectiveness of the proposed algorithm.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:1545-5955
1558-3783
DOI:10.1109/TASE.2011.2176489