Frontiers of Mechanical Engineering >
Timing decision-making method of engine blades for predecisional remanufacturing based on reliability analysis
Received date: 18 Feb 2019
Accepted date: 13 Jun 2019
Published date: 15 Dec 2019
Copyright
A timing decision-making method for predecisional remanufacturing is presented. The method can effectively solve the uncertainty problem of remanufacturing blanks. From the perspective of reliability, this study analyzes the timing decision-making interval for predecisional remanufacturing of mechanical products during the service period and constructs an optimal timing model based on energy consumption and cost. The mapping relationships between time and energy consumption are predicted by using the characteristic values of performance degradation of products combined with the least squares support vector regression algorithm. Application of game theory reveals that when the energy consumption and cost are comprehensively optimal, this moment is the best time for predecisional remanufacturing. Used engine blades are utilized as an example to demonstrate the validity and effectiveness of the proposed method.
Le CHEN , Xianlin WANG , Hua ZHANG , Xugang ZHANG , Binbin DAN . Timing decision-making method of engine blades for predecisional remanufacturing based on reliability analysis[J]. Frontiers of Mechanical Engineering, 2019 , 14(4) : 412 -421 . DOI: 10.1007/s11465-019-0551-0
1 |
Wang X L, Luo W, Zhang H,
|
2 |
Wang H, Jiang Z G, Zhang H,
|
3 |
Miao Z W, Mao H Q, Fu K,
|
4 |
Wang X L, Chen L, Dan B B,
|
5 |
Macedo P B, Alem D, Santos M,
|
6 |
Matsumoto M, Yang S S, Martinsen K,
|
7 |
Jiang Z G, Jiang Y, Wang Y,
|
8 |
Li X, Li Y J, Cai X Q. Remanufacturing and pricing decisions with random yield and random demand. Computers & Operations Research, 2015, 54: 195–203
|
9 |
Jiang Z G, Wang H, Zhang H,
|
10 |
Wang L L, Zhang Z M, Chen C. Evaluation model for product green design based on active remanufacturing. Applied Mechanics and Materials, 2012, 215‒216: 583–587
|
11 |
Chiodo J D, Ijomah W L. Use of active disassembly technology to improve remanufacturing productivity: Automotive application. International Journal of Computer Integrated Manufacturing, 2014, 27(4): 361–371
|
12 |
Ke Q D, Wang H, Song S X,
|
13 |
Song S X, Wang W, Ke Q D. Optimization design of predecisional remanufacturing based on structural function derivative coefficient. Journal of Mechanical Engineering, 2017, 53(11): 175–183 (in Chinese) doi:10.3901/JME.2017.11.175
|
14 |
Song S X, Liu M, Liu G F,
|
15 |
Song S X, Liu M, Ke Q D,
|
16 |
Ijomah W L, Chiodo J D. Application of active disassembly to extend profitable remanufacturing in small electrical and electronic products. International Journal of Sustainable Engineering, 2010, 3(4): 246–257
|
17 |
Kharoufeh J P, Cox S M, Oxley M E. Reliability of manufacturing equipment in complex environments. Annals of Operations Research, 2013, 209(1): 231–254
|
18 |
Saghafi A, Mirhabibi A R, Yari G H. Improved linear regression method for estimating Weibull parameters. Theoretical and Applied Fracture Mechanics, 2009, 52(3): 180–182
|
19 |
Liu T, Huang H H, Liu Z F,
|
20 |
Schau M, Traverso M, Lehmann A,
|
21 |
Chalkiadakis G, Elkind E, Wooldridge M. Cooperative game theory: Basic concepts and computational challenges. IEEE Intelligent Systems, 2012, 27(3): 86–90
|
22 |
Zhao Y P, Sun J G. Improved scheme to accelerate sparse least squares support vector regression. Journal of Systems Engineering and Electronics, 2010, 21(2): 312–317
|
23 |
Wang H, Jiang Z G, Zhang X G,
|
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