Joint Group Maintenance Scheduling and Team Collaboration Sharing Strategy for Multi-Center Leasehold Manufacturing Network

doi:10.16183/j.cnki.jsjtu.2022.074

Abstract

Abstract:

With the wide application of the service-oriented manufacturing mode, the scale of leasing manufacturing enterprises continues to expand, which leads to the global multi-regional development of maintenance outsourcing services. To address the multi-location maintenance scheduling problem of multi-center leasehold networks in the provision of “products+services”, this paper proposes a multi-center collaboration maintenance scheduling (MCMS) strategy with the dynamic interaction between the system level and the network level. At the system level, it considers the impact of the maintenance downtime, cumulative failure, and system combination selection on maintenance decisions, then optimizes the maintenance grouping of machines in the same manufacturing system. Based on the proposed optimization model, the group maintenance set and the corresponding maintenance start time can be obtained by minimizing the total maintenance cost. At the network level, it further considers the impact of service routing optimization, team dispatch selection, and maintenance response speed on scheduling decision, and then outputs the optimal service route for each team by minimizing the total scheduling cost. It also verifies the feasibility and cost-effectiveness of the MCMS strategy in the field of multi-location maintenance scheduling problems by analyzing the case study.

Key words: group maintenance, multi-center leasehold network, collaboration sharing, maintenance team routing

CLC Number:

TH17

SI Guojin, LIN Zeyu, ZHENG Yu, XIA Tangbin, XI Lifeng. Joint Group Maintenance Scheduling and Team Collaboration Sharing Strategy for Multi-Center Leasehold Manufacturing Network[J]. Journal of Shanghai Jiao Tong University, 2023, 57(3): 273-284.

Figures/Tables 14

Fig.1

Tab.1

Symbol and meaning of group maintenance decision-making optimization model

符号类别	符号	含义
集合与索引	M_i	租赁系统i中的设备集合(索引k∈M_i= $1, ? 2, ? …, M i$ )
	N_l	租赁系统集合(索引i, j∈N_l= $1, ? 2, ? …, ? I$ )
	G	成组维护集合(索引g∈G= $1, ? 2, ? …, ? G$ )
模型参数	λ_hk(t)	设备k在第h个维护周期的故障率函数
	c_hk(T_hk)	设备k在第h个维护周期内的成本率函数
	$T P h k$	设备k在第h个维护周期的预知维护作业时长
	P_i	租赁系统i单位时间的维护停机损失
	R	设备运维成本的系数项
	LP_i	租赁系统i的租赁服务期时长
	F_g	各成组维护集合的固定成本
	w_g	维护时间窗的窗宽
	$t E h g, t L h g$	各成组维护集合对应的维护时间窗
	n_hg	各成组维护集合中所需维护的设备数目
	$T h g m a x$	执行各成组维护集合所需的维护时长
决策变量	α_ik_,_g	租赁系统i的设备k在成组维护集g中时为1,否则为0
	τ_ik	租赁系统i的设备k的预知维护作业开始时间
	γ_g	成组维护集g中有待维护的设备时为1,否则为0

Tab.1

Tab.2

Symbol and meaning of collaborative team scheduling optimization model

符号类别	符号	含义
模型参数	C^rv	维护团队v∈V_r的单位时间路由成本
	t_ij	租赁系统i到租赁系统j的路由时间
	D^rv	维护团队v∈V_r的固定派遣成本
	W^rv	维护团队v∈V_r的单位时间的等待成本
	L_i	维护团队v∈V_r的单位时间的延时惩罚成本
	q^rv	维护团队v∈V_r一次派遣的最大可维护的设备数目
决策变量	$x i j r v$	维护团队v∈V_r由租赁系统i前往租赁系统j时为1,否则为0
	$y g r v$	维护团队v∈V_r被派遣以执行成组维护集合g时为1,否则为0
	z_i_,_g	成组维护集合g由系统i中的设备组成时为1,否则为0
	$? g r v$	维护团队v∈V_r执行成组维护集合g的实际开始时点

Tab.2

Fig.2

Fig.3

Tab.3

Reliability and maintenance parameters of each leased machine

k	i	β_k	η_k	b_hk	a_hk	$C P h k$ /美元	$C C h k$ /美元	$T P h k$ /h	$T C h k$ /h
1	1	3.15	5 600	1.05	0.025	6 500	18 000	20	66
2		1.70	4 900	1.036	0.016	9 000	30 000	25	74
3		2.51	5 500	1.02	0.018	6 000	17 000	14	48
4	2	1.94	4 200	1.015	0.023	3 900	8 800	10	38
5		1.85	6 400	1.03	0.038	4 600	21 000	12	68
6		2.95	5 300	1.025	0.048	3 200	6 800	8	18
7	3	2.57	6 100	1.03	0.038	6 700	28 000	12	68
8		1.83	6 000	1.04	0.036	4 600	22 000	10	22
9		2.97	4 300	1.025	0.048	3 900	7 000	8	19
10	4	1.84	4 200	1.015	0.023	4 300	8 200	10	39
11		1.72	5 500	1.03	0.038	7 600	26 000	12	68
12		1.83	3 800	1.04	0.036	9 800	16 000	10	22
13	5	1.74	4 300	1.036	0.016	9 000	20 000	25	72
14		2.51	5 500	1.02	0.018	6 000	17 000	14	48
15		3.13	4 600	1.018	0.036	7 000	13 000	16	40
16	6	2.93	4 700	1.025	0.048	4 000	6 800	8	18
17		1.83	3 500	1.04	0.036	9 800	16 000	10	22
18		1.84	4 500	1.04	0.018	8 200	21 000	25	74
19	7	2.62	5 000	1.05	0.025	6 000	15 000	20	66
20		2.34	5 300	1.027	0.046	7 000	22 000	22	60
21		2.89	4 200	1.04	0.036	9 800	16 000	10	24
22	8	2.25	5 500	1.03	0.038	9 600	28 000	12	68
23		1.78	3 600	1.04	0.036	9 800	16 000	10	22
24		1.76	5 600	1.036	0.016	8 000	30 000	25	74
25	9	3.29	4 400	1.018	0.036	7 000	13 000	16	40
26		2.51	5 200	1.02	0.018	6 000	17 000	14	48
27		1.84	4 200	1.015	0.023	3 600	8 800	10	38

Tab.3

Tab.4

Tab.5

Tab.6

System-level group maintenance decision-making in the first cycle

序号	i	成组维护集合	n_hg	$T h g m a x$ /h	[ $t E h g$ , $t L h g$ ]
1	1	{1, 3}	2	20	[2 898, 2 922]
2	1	{2}	1	25	[3 167, 3 191]
3	2	{4, 6}	2	10	[3 069, 3 093]
4	2	{5}	1	12	[2 845, 2 869]
5	3	{7}	1	12	[3 261, 3 285]
6	3	{8, 9}	2	10	[2 865, 2 889]
7	4	{10}	1	10	[2 799, 2 823]
8	4	{11, 12}	2	12	[3 253, 3 277]
9	5	{13, 14, 15}	3	25	[3 170, 3 194]
10	6	{16, 17, 18}	3	25	[3 011, 3 035]
11	7	{19, 20, 21}	3	22	[2 912, 2 936]
12	8	{22}	1	12	[2 833, 2 857]
13	8	{23, 24}	2	25	[3 113, 3 137]
14	9	{25}	1	16	[3 069, 3 093]
15	9	{26, 27}	2	14	[2 864, 2 888]
总维护成本 TMC₁=155 017元

Tab.6

Tab.7

Fig.4

Tab.8

Fig.5

Fig.6

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系统层模型参数设置		网络层模型参数设置
参数	取值	参数	取值
P_i/(元·h^-1)	300	C^rv/(元·h^-1)	200
R/元	6 000	D^rv/元	20 000
F_g/元	4 000	W^rv/(元·h^-1)	200
w_g/h	24	L_i/(元·h^-1)	300
LP_i/h	17 520	q^rv/台	7
		∑V_r(r∈N_c)/个	6

团队序号	出发点	出发时点	组合服务顺序	租赁系统服务路线
1	维护中心r₁	3 011	(3, 14, 10)	r₁→2→9→6→r₁
2	维护中心r₁	3 113	(13, 2, 9)	r₁→8→1→5→r₁
3	维护中心r₂	2 865	(6, 11)	r₂→3→7→r₂
4	维护中心r₂	3 253	(8, 5)	r₂→4→3→r₂
5	维护中心r₃	2 799	(7, 12, 15, 1, 4)	r₃→4→8→9→1→2→r₃
总调度成本TSC₁=237 200 元

h	成组维护集合G	最优服务路线	对应的团队出发点
1	{1, 3}{2}{4, 6}{5}{7}{8, 9}{10}{11, 12}{13, 14, 15} {16, 17, 18}{19, 20, 21}{22}{23, 24}{25}{26, 27}	(2→9→6, 8→1→5, 3→7, 4→3, 4→8→9→1→2)	(1, 2, 3, 2, 1)
2	{1, 3}{2}{4, 6}{5}{7}{8, 9}{10}{11, 12}{13, 14, 15} {16, 17, 18}{19, 20, 21}{22}{23, 24}{25}{26, 27}	(8→3→9, 3→4, 8→9, 6→2, 1→5, 4→1→7→2)	(3, 1, 3, 1, 2, 1)
3	{1, 3}{2}{4, 6}{5}{7}{8, 9}{10}{11, 12}{13, 14}{15} {16, 17}{18}{19, 20, 21}{22}{23}{24}{25}{26}{27}	(3→4→5, 6→2→7, 8→9→4, 1→3→9, 6→1, 9→8→2→8→5)	(2, 1, 2, 1, 1, 2)
4	{1, 3}{2}{4}{5}{6}{7}{8}{9}{10}{11}{12}{13, 14}{15} {16, 17}{18}{19}{20, 21}{22}{23}{24}{25}{26}{27}	(5→4, 3→6→1→3→7, 9→5→9, 2→9→8→3→6, 8→4, 7→1→2)	(2, 3, 3, 1, 2, 3)
5	{1, 3}{2}{4}{5}{6}{7}{8}{9}{10}{11}{12}{13}{14}{15} {16, 17}{18}{19}{20}{21}{22}{23}{24}{25}{26}{27}	(9→6→8, 7→8→2→4→6, 4→5, 8→3→5→3→2→7→1, 9, 1→3→2→9→7)	(3, 1, 2, 1, 3, 3)