A queueing-based optimization model for planning inventory of repaired components in a service center

- We study after-sales service contracts that guarantee a quick turnaround time for repair.
- Queueing-based optimization models were used to obtain the optimal repair capacity and inventory levels.
- Algorithms were developed based on the properties derived for the total cost function.
- Repair cost and server operating cost play a significant role in determining the optimal solution.
- Demand arrival rate and fraction of irreparable faulty components are other significant factors.

We address the problem of managing repair capacity and repaired component inventory in a service center. With modular products, the repair essentially involves identifying the faulty component in the product and replacing it with a repaired component or a new component, if repaired components are not available in stock. The faulty component is then repaired and used to service a future faulty product that arrives for repair. The problem is modeled as a queueing system with a limit on the queue length. The total cost function involves the steady-state probabilities and queue length of the queueing system. Using the properties of the cost function that we derive, we identify bounds on the decision variables, and use them in developing an algorithm to determine the optimal repair capacity and repaired component inventory. A computational study is carried out to investigate the impact of the various cost parameters on the optimal solution.