期刊
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
卷 23, 期 6, 页码 1431-1448出版社
INFORMS
DOI: 10.1287/msom.2020.0888
关键词
inventory; spare parts; multi-item; repair; expediting; multi-echelon; column generation
资金
- National Research Fund of Luxembourg [AFR] [12451704]
- Netherlands Organization for Scientific Research [451-16-025]
The study explores dual sourcing in a distribution network and proposes optimization solutions using queuing theory and a greedy heuristic method, achieving effective inventory management and reduced stock investments. With dynamic repair policies, expedited repairs can significantly improve the utilization of repairable spare parts and reduce stock investments.
Problem definition: We consider dual sourcing in a distribution network for spare parts consisting of one central warehouse and multiple local warehouses. Each warehouse keeps multiple types of repairable parts to maintain several types of capital goods. The repair shop at the central warehouse has two repair options for each repairable part: a regular repair option and an expedited repair option. Irrespective of the repair option, each repairable part uses a certain resource for its repair. In the design of these inventory systems, companies need to decide on stocking levels and expedite thresholds such that total stock investments are minimized while satisfying asset availability and expediting constraints. Academic/practical relevance: Although most companies have the possibility to expedite the repair of parts in short supply, no contributions have been made that incorporate such dynamic expediting policies in repairable investment decisions. Anticipating expediting decisions that will be made later leads to substantial reductions in repairable investments. Methodology: We use queueing theory to determine the performance of the central warehouse and subsequently find the performance of all local warehouses using binomial disaggregation. For the optimization problem, we develop a greedy heuristic and a decomposition and column generation based algorithm. Results: Both solution approaches perform very well with average optimality gaps of 2.38 and 0.27%, respectively, across a large test bed of industrial size. The possibility to expedite the repair of failed parts is effective in reducing stock investments with average reductions of 7.94% and even reductions up to 19.61% relative to the state of the art. Managerial implications: Based on a case study at Netherlands Railways, we show how managers can significantly reduce the investment in repairable spare parts when dynamic repair policies are leveraged to prioritize repair of parts whose inventory is critically low.
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