Modelling, analysis and improvement of an integrated chance-constrained model for level of repair analysis and spare parts supply control

2019 ◽  
Vol 58 (10) ◽  
pp. 3090-3109 ◽  
Author(s):  
Weimiao Liu ◽  
Kanglin Liu ◽  
Tianhu Deng
2014 ◽  
Vol 668-669 ◽  
pp. 1633-1636
Author(s):  
Li Xu ◽  
Qing Min Li ◽  
Hua Li

According to the real background of repair and supply of spare parts, aims to reasonably plan that how to and where to repair the failure parts, where to deploy the repair resources and develop the initial spares configuration program such that the availability target of equipment is achieved with the lowest investment cost, the joint optimization model for level of repair analysis (LORA) and spare parts stocks is established consisting of variable cost and fixed cost that produced in maintenance as well as the equipment availability, and a new joint optimization method for the model is proposed combined Invasive Weed optimization (IWO) and margin analysis, then the optimization is realized. In a given example, the optimization result is gotten, through which the validity of the model and method is proved.


2012 ◽  
Vol 224 (1) ◽  
pp. 121-145 ◽  
Author(s):  
R. J. I. Basten ◽  
M. C. van der Heijden ◽  
J. M. J. Schutten ◽  
E. Kutanoglu

2012 ◽  
Vol 222 (3) ◽  
pp. 474-483 ◽  
Author(s):  
R.J.I. Basten ◽  
M.C. van der Heijden ◽  
J.M.J. Schutten

2021 ◽  
Vol 11 (16) ◽  
pp. 7254
Author(s):  
Ruiqi Wang ◽  
Guangyu Chen ◽  
Jie Wu ◽  
Wei Zhou ◽  
Zheng Huang

For the repair level and spare parts stocking problems, generally METRIC type methods and Level of repair analysis (LORA) are used separately. Since LORA does not consider the availability of capital goods, solving LORA and spare parts stocking problems sequentially may lead to suboptimal solutions. On these considerations, this study presents a joint optimization method to minimize the service logistics cost under the constraints of system availability. Maintenance capability factor and maintenance decisions are introduced into the joint optimization model to express the influence of multiple failure modes on repair level and spare parts stocking. Thus, we establish the bridge relationship between LORA and METRIC models. The joint optimization model is solved by an improved iterative algorithm, and a typical fleet system is taken as an example to verify the correctness and effectiveness of the model and the algorithm. Compared with the optimization of spare parts inventory and maintenance level independently, the joint optimization method could effectively reduce the service logistic system cost.


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