The final order problem for repairable spare parts under condemnation

We consider a manufacturer of complex machines that offers service contracts to her customers, committing herself to repair failed spare parts throughout a fixed service period. The suppliers of spare parts often discontinue the production of some parts as technology advances and ask the manufacturer to place a final order. We address the problem of determining final orders for such spare parts. The parts that we consider are repairable, but they are subject to the risk of condemnation. We build a transient Markovian model to represent the problem for a repairable spare part with a certain repair probability and repair lead time and we present some approximations that allow for further real life characteristics to be included. Furthermore, an approximate model that can be computed more efficiently is presented, and the sensitivity of the results obtained with respect to the problem parameters for both of the models is discussed

End-of-Life Inventory Problem with Phase-out Returns

We consider the service parts end-of-life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phase-out returns. Phase-out returns happen when a customer replaces an old system platform with a next generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this paper, we study the decision-making complications stemming from phase-out occurrence. We use a finite horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time varying threshold level for item repair. Furthermore, we study the value of phase-out information by extending the results to cases with an uncertain phase-out quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.spare parts;end-of-life inventory management;phase-out returns

End-of-Life Inventory Decisions for Consumer Electronics Service Parts

We consider a consumer electronics (CE) manufacturer’s problem of controlling the inventoryof spare parts in the final phase of the service life cycle. The final phase starts when thepart production is terminated and continues until the last service contract or warranty periodexpires. Placing final orders for service parts is considered to be a popular tactic to satisfy demandduring this period and to mitigate the effect of part obsolescence at the end of the servicelife cycle. To satisfy demand for service in the final phase, previous research focuses on repairingdefective products by replacing the defective parts with properly functioning spare ones.However, for consumer electronic products there is a remarkable price erosion while repaircosts may stay steady over time. As a consequence, this introduces the idea that there mightbe a point in time at which the unit price of the product is lower than repair associated costs.Therefore, it would be more cost effective to adopt an alternative policy to meet demands forservice such as offering customers a replacement of the defective product with a new one orgiving a discount on the next generation of the product. This paper examines the cost trade-offsof implementing alternative policies for the repair policy and develops an exact formulation forthe expected total cost function. Based on this developed cost function we propose policies tosimultaneously find the optimal final order quantity and the time to switch from the repair toan alternative replacement policy. Numerical analysis of a real world case study sheds lightover the effectiveness and advantage of these policies in terms of cost reduction and also yieldsinsights into the quantitative importance of the various cost parameters.consumer electronics;end-of-life inventory control;service parts

End-of-Life Inventory Problem with Phase-out Returns

We consider the service parts end-of-life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phase-out returns. Phase-out returns happen when a customer replaces an old system platform with a next generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this paper, we study the decision-making complications stemming from phase-out occurrence. We use a finite horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time varying threshold level for item repair. Furthermore, we study the value of phase-out information by extending the results to cases with an uncertain phase-out quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies

End-of-Life Inventory Decisions for Consumer Electronics Service Parts

We consider a consumer electronics (CE) manufacturer’s problem of controlling the inventory of spare parts in the final phase of the service life cycle. The final phase starts when the part production is terminated and continues until the last service contract or warranty period expires. Placing final orders for service parts is considered to be a popular tactic to satisfy demand during this period and to mitigate the effect of part obsolescence at the end of the service life cycle. To satisfy demand for service in the final phase, previous research focuses on repairing defective products by replacing the defective parts with properly functioning spare ones. However, for consumer electronic products there is a remarkable price erosion while repair costs may stay steady over time. As a consequence, this introduces the idea that there might be a point in time at which the unit price of the product is lower than repair associated costs. Therefore, it would be more cost effective to adopt an alternative policy to meet demands for service such as offering customers a replacement of the defective product with a new one or giving a discount on the next generation of the product. This paper examines the cost trade-offs of implementing alternative policies for the repair policy and develops an exact formulation for the expected total cost function. Based on this developed cost function we propose policies to simultaneously find the optimal final order quantity and the time to switch from the repair to an alternative replacement policy. Numerical analysis of a real world case study sheds light over the effectiveness and advantage of these policies in terms of cost reduction and also yields insights into the quantitative importance of the various cost parameters

Optimal and heuristic repairable stocking and expediting in a fluctuating demand environment

We consider a single stock point for a repairable item. The repairable item is a critical component that is used in a fleet of technical systems such as trains, planes or manufacturing equipment. A number of spare repairables is purchased at the same time as the technical systems they support. Demand for those items is a Markov modulated Poisson process of which the underlying Markov process can be observed. Backorders occur when demand for a ready-for-use item cannot be fulfilled immediately. Since backorders render a system unavailable for use, there is a penalty per backorder per unit time. Upon failure, defective items are sent to a repair shop that offers the possibility of expediting repair. Expedited repairs have shorter lead times than regular repairs but are also more costly. For this system, two important decisions have to be taken: How many spare repairables to purchase initially and when to expedite repairs. We formulate the decision to use regular or expedited repair as a Markov decision process and characterize the optimal repair expediting policy for the infinite horizon average and discounted cost criteria. We find that the optimal policy may take two forms. The first form is to never expedite repair. The second form is a type of threshold policy. We provide necessary and sufficient closed-form conditions that determine what form is optimal. We also propose a heuristic repair expediting policy which we call the world driven threshold (WDT) policy. This policy is optimal in special cases and shares essential characteristics with the optimal policy otherwise. Because of its simpler structure, the WDT policy is fit for use in practice. We show how to compute optimal repairable stocking decisions in combination with either the optimal or a good WDT expediting policy. In a numerical study, we show that the WDT heuristic performs very close to optimal with an optimality gap below 0.76% for all instances in our test bed. We also compare it to more naive heuristics that do not explicitly use information regarding demand fluctuations and find that the WDT heuristic outperforms these naive heuristics by 11.85% on average and as much as 63.67% in some cases. This shows there is great value in leveraging knowledge about demand fluctuations in making repair expediting decisions

Maintenance spare parts planning and control : a framework for control and agenda for future research

This paper presents a framework for planning and control of the spare parts supply chain in organizations that use and maintain high-value capital assets. Decisions in the framework are decomposed hierarchically and interfaces are described. We provide relevant literature to aid decision making and identify open research topics. The framework can be used to increase the e??ciency, consistency and sustainability of decisions on how to plan and control a spare parts supply chain. Applicability of the framework in di??erent environments is investigated