Supply Chain Recovery Strategies for High Demand Products Based on the Impact of Capacity and Transportation Disruptions
Abstract
:1. Introduction
2. Literature Review
3. System Dynamics Framework
3.1. System Dynamics Model Boundaries
3.2. System Dynamics Model Hypothesis
- (1)
- Only after the production capacity is interrupted can the manufacturer proceed.
- (2)
- The size of the expediting rate represents the extent of production. The higher the pilot rate, the higher the complexity cost.
- (3)
- The advanced stage of the support chain is known and fixed.
- (4)
- The capacity interruption rate being 1 represents complete interrupt, and the capacity interruption rate being 0.5 represents partial interrupt.
- (5)
- Transport interrupts are expressed through the interruption of the transport interrupt; the transport interruption time of 30 generations means a partial interrupt, and the transport interruption time of 50 represents complete interrupt.
- (6)
- Due to the severity of the capacity interruption, the manufacturer operates in a specific capacity and costs when the production capacity is interrupted.
- (7)
- The transport truck cost and load weight of the manufacturer and distribution center are the same.
- (8)
- The production capacity interruption and transportation interruption start at the same time.
- (9)
- Government subsidies start from the supply chain interruption time.
- (10)
- The order implements the “advanced first-out” principle.
- (11)
- The manufacturer’s demand is derived from orders in the distribution center.
- (12)
- Government subsidies and capacity are positive linear relationships, and there is a government subsidy to the capacity of capacity and the increased production capacity after subsidies.
- (13)
- The government needs a certain amount of time to develop new production capacity, and there is a subsidy of production capacity to take effect.
- (14)
- The production capacity interruption only occurs for the manufacturer, and the transport interruption only occurs at the distribution center.
- (15)
- The demand is subject to a uniform distribution.
- (16)
- Limitations on the warehouse capacity of manufacturers and distribution centers are not taken into account.
- (17)
- Government subsidies can only subsidize one of the objects and distribution centers of the manufacturer and distribution center, representing the choice of subsidy strategy. The government subsidy is set to 0 or 1.
3.3. System Structure Analysis
3.4. System Stock Traffic Diagram
3.5. Model Equations and Parameters
4. Numerical Study and Results
4.1. Parameter Setting
4.2. System Dynamics Model Checking
Reality Check
4.3. Analysis of Simulation Results
4.3.1. Analysis of Simulation Results of Transportation Partial Interruption and Capacity Interruption
4.3.2. Analysis of Simulation Results of Complete Transportation Interruption and Capacity Interruption
5. Conclusions
- (1)
- In the case of transportation interruption and capacity interruption, whether the transportation is partially or completely interrupted, the government subsidizes the manufacturer and the recovery effect is better than subsidizing the distribution center. Most of the labor used by manufacturers is near the factory. During the epidemic, the transmission speed can be controlled in a small area. Most of the labor in the distribution center passes through multiple locations during the distribution process. During the epidemic, the risk level of various places may change at any time. Delivery workers are more likely to be out of work, so government subsidies to manufacturers can restore productivity faster, boosting the recovery of cumulative profits for supply chain members.
- (2)
- The government subsidy strategy does not have an immediate recovery effect in the complete interruption of transportation and production capacity. When production capacity and transportation are completely interrupted, it means that the production and manufacturers’ and distribution centers’ transportation facilities have been completely paralyzed, and government subsidies need to re-integrate resources. In addition, there are material and information delays in the supply chain, so government subsidies cannot work right away.
- (3)
- When the government chooses the subsidy strategy, the different production capacity levels and transportation interruption will lead to different effects of government subsidies on supply chain recovery. The severity of capacity disruptions can cause companies to operate at different efficiencies and costs. The more severe the capacity disruption, the less productive the manufacturer will be and the corresponding increase in operating costs. In the partial interruption scenario, government subsidies can allow manufacturers and distribution centers to obtain capital and labor resources to quickly resume production. In the complete interruption scenario, due to the rapid spread of the epidemic and the different isolation measures in various parts of China, it is difficult to resume production in a short period quickly. Integrate resources and restore production capacity, so the recovery effect is not as good as the partially interrupted scene.
- (4)
- Under the complete interruption of production capacity, the cumulative total value of the supply chain after increasing government subsidies has rebounded in a spiral. Due to the delay in the arrival of materials in the production process of the manufacturer’s work in progress, the cumulative total profit of the supply chain after the government subsidy will decline, and the overall recovery trend will spiral upward.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Appendix B
Serial Number | Constant | Numerical Value |
---|---|---|
1 | P government subsidy ceiling (yuan) | 200,000 |
2 | Blackout start time (days) | Day 830 |
3 | P effective Time of Subsidized products capacity to take effect (days) | 10 days |
4 | Blackout end time (days) | Day 860 |
5 | P initial product inventory (set) | 800 |
6 | DC initial product inventory (set) | 1200 |
7 | P capacity disruption rate | Simulation settings |
8 | DC duration of transport interruption | Simulation settings |
9 | P minimum delivery time (days) | 3 |
10 | Dc minimum delivery time (days) | 4 |
11 | P backlog adjustment time (days) | 2 |
12 | DC backlog adjustment time (days) | 1 |
13 | P initial backlogged order (sets) | 0 |
14 | DC initial backlogged order (set) | 0 |
15 | P initial work in process (set) | 0 |
16 | DC initially received product (set) | 0 |
17 | P product shipping time (days) | 4 |
18 | P total capacity (units/day) | 1200 |
19 | P normal production time (days) | 6 |
20 | DC normal production time (days) | 6 |
21 | P expediting rate | 0.5 |
22 | P product delivery time (days) | 6 |
23 | DC product delivery time (days) | 6 |
24 | P product safety stock time | 2 |
25 | DC product safety stock time (days) | 2 |
26 | P order time (days) | 1 |
27 | P product price (yuan/unit) | 10,000 |
28 | DC product price (yuan/set) | 30,000 |
29 | DC order time (days) | 1 |
30 | P order adjustment time (days) | 5 |
31 | DC order adjustment time (days) | 10 |
32 | P initial raw material inventory (set) | 200 |
33 | P raw material transportation time (days) | 2 |
34 | P raw material adjustment time (days) | 1 |
35 | P time to order raw materials (days) | 5 |
36 | P raw material delivery time (days) | 6 |
37 | P raw material safety stock time (days) | 4 |
38 | P initial order product (set) | 0 |
39 | DC initial order product (set) | 0 |
40 | P truck capacity (unit/car) | 80 |
41 | DC truck capacity (unit/car) | 80 |
42 | P Transport truck unit cost (yuan/car) | 100 |
43 | DC transport truck unit cost (yuan/car) | 100 |
44 | P raw material price (yuan/set) | 2000 |
45 | P currency rate | 1.5 |
46 | DC currency exchange rate | 1.5 |
47 | P procurement cost growth rate | 0.8 |
48 | DC procurement cost growth rate | 0.2 |
49 | P holding rate | 0.12 |
50 | DC holding rate | 0.15 |
51 | P backlog penalty rate | 0.1 |
52 | DC backlog Penalty Rate | 0.1 |
53 | P raw material holding ratio | 0.1 |
54 | P raw material inventory adjustment time (days) | 10 |
55 | P inventory adjustment time (days) | 10 |
56 | DC inventory adjustment time (days) | 7 |
57 | Expediting time (days) | 20 |
58 | P received raw material (units/day) | 300 |
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Situation | P Capacity Interruption Rate | Length of Transport Interruption | P Government Subsidy Ratio | DC Government Subsidy Ratio |
---|---|---|---|---|
A1 | 0.5 | 30 | 1 | 0 |
A2 | 0.5 | 30 | 0 | 1 |
A3 | 1 | 30 | 1 | 0 |
A4 | 1 | 30 | 0 | 1 |
A5 | 0.5 | 50 | 1 | 0 |
A6 | 0.5 | 50 | 0 | 1 |
A7 | 1 | 50 | 1 | 0 |
A8 | 1 | 50 | 0 | 1 |
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Ju, C.; Zhao, J.; Li, K.; Bao, F.; Xu, C.; Ran, J. Supply Chain Recovery Strategies for High Demand Products Based on the Impact of Capacity and Transportation Disruptions. Systems 2022, 10, 88. https://doi.org/10.3390/systems10040088
Ju C, Zhao J, Li K, Bao F, Xu C, Ran J. Supply Chain Recovery Strategies for High Demand Products Based on the Impact of Capacity and Transportation Disruptions. Systems. 2022; 10(4):88. https://doi.org/10.3390/systems10040088
Chicago/Turabian StyleJu, Chunhua, Jiehao Zhao, Ke Li, Fuguang Bao, Chonghuan Xu, and Jiarui Ran. 2022. "Supply Chain Recovery Strategies for High Demand Products Based on the Impact of Capacity and Transportation Disruptions" Systems 10, no. 4: 88. https://doi.org/10.3390/systems10040088