Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/153988
Title: SPARE PART INVENTORY OPTIMIZATION WITH PERFORMANCE-BASED MAINTENANCE CONTRACTS
Authors: NGUYEN VAN VINH
Keywords: Inventory Optimization
Spare Part
Performance-Based Logistics
Inventory Rationing
Markov Chain
Issue Date: 2010
Citation: NGUYEN VAN VINH (2010). SPARE PART INVENTORY OPTIMIZATION WITH PERFORMANCE-BASED MAINTENANCE CONTRACTS. ScholarBank@NUS Repository.
Abstract: In this work, we consider the inventory optimization problem faced by a maintenance repair and overhaul (MRO) company who provides aircraft maintenance services to different airline operators under performance-based contracts. We introduce a mathematical model for the continuous review, multi-customer, multi-location and multi-item logistics network of service parts. The model takes into account the lateral transshipments between different airports. Demands for spare parts are modeled as Poisson processes. In our model, the MRO company follows the (s-1, s), critical-level policy that allows it to effectively allocate the inventory resource according to different service level requirements of the customers. We model the local warehouse inventory system at a particular location using a continuous time Markov chain model. The Markov state in this Markov chain model is described by the numbers of backorders for different customers and the current physical stock level of the warehouse. We then incorporate this Markov chain model into an iterative algorithm to calculate the performance measures such as the time-based system fill rate and the expected number of outage events. We formulate the MRO™s inventory optimization problem that takes into account the presence of multiple maintenance contracts. The resulting optimization problem is discrete, non-linear and non-convex. In order to solve this problem, we use a two-phase algorithm that combines simulated annealing and cost-biased heuristic enumeration. To analyze the performance of the critical-level policy, we perform sensitivity analysis using a small logistics network with simple settings. The results indicate that critical level policy can considerably reduce the cost when the customers have different target fill rates or different penalty rates. Under the experimental scenario where customers have different target fill rates, the cost is reduced by 4.7% using critical-level policy. Similarly, under the scenario that customers have different penalty rates, the cost reduction percentage is 6%. When operators have the same target fill rates and penalty rates, the critical-level policy is not likely to result in significant cost reduction, even when one operator has much more failed parts than the others.
URI: https://scholarbank.nus.edu.sg/handle/10635/153988
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