Last time buy and repair decisions for spare parts

Original Equipment Manufacturers (OEM’s) of advanced capital goods often offer service contracts for system support to their customers, for which spare parts are needed. Due to technological changes, suppliers of spare parts may stop production at some point in time. As a reaction to that decision, an OEM may place a so-called Last Time Buy (LTB) order to cover demand for spare parts during the remaining service period, which may last for many years. The fact that there might be other alternative sources of supply in the next periods\ud complicates the decision on the LTB. In this paper, we develop a heuristic method to find the near- optimal LTB quantity in presence of an imperfect repair option of the failed parts that can be returned from the field. Comparison of our method to simulation shows high approximation accuracy. Numerical experiments reveal that repair is an excellent option as\ud alternative sourcing, even if it is more expensive than buying a new part, because of postponement of the repair decisions. In addition, we show the impact of other key parameters on costs and LTB quantity

Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems

This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.spare parts;reverse logistics;phase-out;PUSH-PULL repair;non stationary;Last Time Buy;business case

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

Practical extensions to the level of repair analysis

The level of repair analysis (lora) gives answers to three questions that are posed when deciding on how to maintain capital goods: 1) which components to repair upon failure and which to discard, 2) at which locations in the repair network to perform each type of repairs, and 3) at which locations in the network to deploy resources, such as test equipment. The goal is to achieve the lowest possible life cycle costs. Various models exist for the lora problem. However, these models tend to be restrictive in that specic business situations cannot be incorporated, for example, having repair equipment with a capacity restriction or the occurrence of unsuccessful repairs.We discuss and model various practically relevant extensions to an existing minimum cost \ud ow formulation for the lora problem. We show the added value of these model renements in an extensive numerical experiment

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

Dynamic buy-back for product recovery in end-of-life spare parts procurement

The efficient supply of spare parts is of prime concern for OEMs. Next to the traditional spare parts sources in form of final order and remanufacturing, the option to buy back broken products prevents the OEM from fulfilling his spare parts availability obligation in the end-of-life phase and increases his ability to remanufacture. This contribution seeks to identify optimal buy-back strategies for different settings regarding information availability and buy-back flexibility. A numerical study analyzes circumstances under which buy-back is especially beneficial for the OEM.Inventory Management, Spare Parts Management, Reverse Logistics, Buy-back

An Advanced Heuristic for Multiple-Option Spare Parts Procurement after End-of-Production

After-sales service is a major profit generator for more and more OEMs in industries with durable products. Successful engagement in after-sales service improves customer loyalty and allows for competitive differentiation through superior service like an extended service period after end of production during which customers are guaranteed to be provided with service parts. In order to fulfill the service guarantee in these cases, an effective and efficient spare parts management has to be implemented, which is challenging due to the high uncertainty concerning spare parts demand over such a long time horizon. The traditional way of spare parts acquisition for the service phase is to set up a huge final lot at the end of regular production of the parent product which is sufficient to fulfill demand up to the end of the service time. This strategy results in extremely high inventory levels over a long period and generates major holding costs and a high level of obsolescence risk. With increasing service time more flexible options for spare parts procurement after end of production gain more and more importance. In our paper we focus on the two most relevant ones, namely extra production and remanufacturing. Managing all three options leads to a complicated stochastic dynamic decision problem. For that problem type, however, a quite simple combined decision rule with order-up-to levels for extra production and remanufacturing turns out to be very effective. We propose a heuristic procedure for parameter determination which accounts for the main stochastic and dynamic interactions between the different order-up-to levels, but still consists of quite simple calculations so that it can be applied to problem instances of arbitrary size. In a numerical study we show that this heuristic performs extremely well under a wide range of conditions so that it can be strongly recommended as a decision support tool for the multi-option spare parts procurement problem.Spare Parts, Inventory Management, Reverse Logistics, Final Order

On two-echelon inventory systems with Poisson demand and lost sales

We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u

On how the acquisition of recoverable parts influences the profitability of spare parts management for durables

In the management of spare parts for durables OEMs often face a sharp decline in sales of spare parts when the warranty period of their products ends. One reason for this effect is given by the high profitability of the after sales market which attracts competitors. If the competitors’ main sourcing option consists of repairing used or broken parts, an acquisition of those parts by the OEM might lower competition and increase sales. The purpose of this paper is to provide a case-based framework to offer insights on the opportunity of recovering parts. We consider a two-stage supply chain, where independent repair shops are responsible for handling the repair process. There are two options to meet spare parts demand: repair shops may replace the part with a new one (ordered from the OEM) or they may use a part that they repaired before. While repair shops achieve a larger profit by repairing parts, the OEM would prefer the use of new parts. However, he has no control on demand which might be obtained through buyback of broken parts. Furthermore, the OEM could recover these parts on a higher level, thus reducing production/procurement of new parts. The main contribution of this paper is to elaborate the important effects of recoverable items acquisition on spare parts demand by using a simple deterministic framework thus outlining the impact of different parameters on the profitability of spare parts management.Closed-Loop Supply Chains, Spare Parts, Competition in Product Recovery, Case Study