Joint Optimization of Replacement and Spare Parts Ordering with Dual Sourcing

doi:10.16183/j.cnki.jsjtu.2021.151

Abstract

Abstract:

To optimize the joint decisions of equipment maintenance and spare parts ordering with dual sourcing, a joint policy is proposed for a multi-unit parallel manufacturing system. The degradation trajectories of components are described by the Poisson process. The joint decisions are modeled according to the Markov decision process. Based on components and inventory status, the transition probability of a system is formulated. The value iteration algorithm is applied to obtain the optimal maintenance and spare parts ordering policy to minimize the average total cost of the system. Furthermore, to shorten the computation time, a heuristic strategy is developed according to the principle of sequential optimization. Numerical experiments with a two-component system are conducted to analyze the decision difference between the heuristic strategy and the optimal strategy. The sensitivity analysis shows that compared with the optimal strategy, the heuristic strategy can reduce the computation time when the total cost increases by no more than 5%.

Key words: preventive maintenance, spare parts ordering, dual sourcing, joint optimization, heuristic strategy

CLC Number:

TH17

YE Hongqing, SU Huade, ZHENG Meimei, XIA Tangbin. Joint Optimization of Replacement and Spare Parts Ordering with Dual Sourcing[J]. Journal of Shanghai Jiao Tong University, 2022, 56(10): 1359-1367.

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参数	取值	参数	取值
c₁	120	c_p	36
c₂	240	c_s	30
c_c	54	l₁	2
c_d	200	L	9
c_F	15	T	1
c_h	0.48	α	0.5
H	N+2	ε	0.0005

N	最优策略		阈值策略			启发式策略
N	f	g/s	f	g/s	q/%	f	g/s	q/%
2	27.8	38	30.0	15	7.9	27.9	9	0.4
4	51.2	5 214	56.5	485	10.4	51.9	255	1.4

c_h	最优策略		启发式策略		q/%
c_h	f	g/s	f	g/s	q/%
0.5	51.3	5 013	52.0	262	1.4
1	52.1	4 608	52.9	215	1.5
2	53.3	4 583	54.1	214	1.5
3	54.2	4 645	55.1	226	1.7

c_p	最优策略		启发式策略		q/%
c_p	f	g/s	f	g/s	q/%
12	45.2	4 714	46.0	264	1.8
24	48.2	5 042	49.0	259	1.7
36	51.2	5 214	51.9	255	1.4
48	54.1	5 293	54.9	252	1.5

c₁	最优策略		启发式策略		q/%
c₁	f	g/s	f	g/s	q/%
50	32.5	5 236	33.7	293	3.7
100	45.9	4 961	46.7	270	1.7
150	58.9	5 222	59.7	249	1.4
200	71.5	5 203	72.7	246	1.7