|M.Sc Student||Avital Naama|
|Subject||Joint Stocking and Repair Decisions in Supply Chains of|
Repairable Items with Multiple Repair Locations -
An Operational Model
|Department||Department of Industrial Engineering and Management||Supervisors||Dr. Izack Cohen|
|Professor Yale Herer|
|Full Thesis text|
Supply chain management typically includes three planning levels: strategic, tactical and operational. While the first two deal with high level, long- and intermediate-term planning and use future assessments and estimates, operational level planning handles the day-to-day operating issues of the supply chain.
We consider a two-echelon supply chain of repairable spare parts, which consists of bases from which a fleet of systems operates and a central depot. The depot and each base include a repair facility. In addition, the central depot has a warehouse that can store good parts for delivery to bases as needed. The systems are subject to random failures of their parts. Failed parts can be repaired locally at the bases or centrally at the depot. Locally repaired parts are returned to the base as good inventory and centrally repaired parts can be stored at the depot or allocated to any of the bases.
The objective of this work is to develop an operational model for minimizing supply chain expected costs, using operational level information that are known for the near future. The model will help determine repair and allocation policies in supply chains with multiple repair locations .
We formulate the problem of minimizing the expected costs as a mathematical program, using integer linear programming, based on the Newsvendor problem. The model is a myopic model and is intended to be applied in a rolling horizon matter. We find upper and lower bounds for the optimal solution which result in reformulation of the problem, leading to reasonable solution times compared to the original formulation .
A numerical study was performed to simulate various configurations of the model, focusing on differences between repair cycle times and repair costs. Other parameters considered included different initial stock levels, arrival rates of failed parts, shortage to holding cost ratio and repair capacities .
The numerical study showed, among other findings, that when a repair facility is faster and cheaper there is a preference to send parts for that repair facility. However, when traffic intensity is high, it is better to send some proportion of parts to be repaired at the slower and more expensive facility. Differences in repair cycle times become more significant for repair decisions when the bases are is faster but depot is cheaper, and their impact is even stronger when repair costs are identical. The analysis showed that initial inventory levels, arrival rates and shortage costs, also had an impact on decision making, especially in cases where there was a trade-off between repairing in the faster facility and repairing at the cheaper facility .
The study conducted in this work focuses supply chains with one part type, but the model can be easily expanded to include several part types, while maintaining its assumptions. Other future work can focus either on further development of the model such as joint repair capacity or transshipment of inventory, on expanding the numerical study, or on developing other approaches for finding solutions, such as algorithms based on the bounds found in this work.