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

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

Multiobjective Coordination Models For Maintenance And Service Parts Inventory Planning And Control

In many equipment-intensive organizations in the manufacturing, service and particularly the defense sectors, service parts inventories constitute a significant source of tactical and operational costs and consume a significant portion of capital investment. For instance, the Defense Logistics Agency manages about 4 million consumable service parts and provides about 93% of all consumable service parts used by the military services. These items required about US$1.9 billion over the fiscal years 1999-2002. During the same time, the US General Accountability Office discovered that, in the United States Navy, there were about 3.7 billion ship and submarine parts that were not needed. The Federal Aviation Administration says that 26 million aircraft parts are changed each year. In 2002, the holding cost of service parts for the aviation industry was estimated to be US$50 billion. The US Army Institute of Land Warfare reports that, at the beginning of the 2003 fiscal year, prior to Operation Iraqi Freedom the aviation service parts alone was in excess of US$1 billion. This situation makes the management of these items a very critical tactical and strategic issue that is worthy of further study. The key challenge is to maintain high equipment availability with low service cost (e.g., holding, warehousing, transportation, technicians, overhead, etc.). For instance, despite reporting US$10.5 billion in appropriations spent on purchasing service parts in 2000, the United States Air Force (USAF) continues to report shortages of service parts. The USAF estimates that, if the investment on service parts decreases to about US$5.3 billion, weapons systems availability would range from 73 to 100 percent. Thus, better management of service parts inventories should create opportunities for cost savings caused by the efficient management of these inventories. Unfortunately, service parts belong to a class of inventory that continually makes them difficult to manage. Moreover, it can be said that the general function of service parts inventories is to support maintenance actions; therefore, service parts inventory policies are highly related to the resident maintenance policies. However, the interrelationship between service parts inventory management and maintenance policies is often overlooked, both in practice and in the academic literature, when it comes to optimizing maintenance and service parts inventory policies. Hence, there exists a great divide between maintenance and service parts inventory theory and practice. This research investigation specifically considers the aspect of joint maintenance and service part inventory optimization. We decompose the joint maintenance and service part inventory optimization problem into the supplier s problem and the customer s problem. Long-run expected cost functions for each problem that include the most common maintenance cost parameters and service parts inventory cost parameters are presented. Computational experiments are conducted for a single-supplier two-echelon service parts supply chain configuration varying the number of customers in the network. Lateral transshipments (LTs) of service parts between customers are not allowed. For this configuration, we optimize the cost functions using a traditional, or decoupled, approach, where each supply chain entity optimizes its cost individually, and a joint approach, where the cost objectives of both the supplier and customers are optimized simultaneously. We show that the multiple objective optimization approach outperforms the traditional decoupled optimization approach by generating lower system-wide supply chain network costs. The model formulations are extended by relaxing the assumption of no LTs between customers in the supply chain network. Similar to those for the no LTs configuration, the results for the LTs configuration show that the multiobjective optimization outperforms the decoupled optimization in terms of system-wide cost. Hence, it is economically beneficial to jointly consider all parties within the supply network. Further, we compare the model configurations LTs versus no LTs, and we show that using LTs improves the overall savings of the system. It is observed that the improvement is mostly derived from reduced shortage costs since the equipment downtime is reduced due to the proximity of the supply. The models and results of this research have significant practical implications as they can be used to assist decision-makers to determine when and where to pre-position parts inventories to maximize equipment availability. Furthermore, these models can assist in the preparation of the terms of long-term service agreements and maintenance contracts between original equipment manufacturers and their customers (i.e., equipment owners and/or operators), including determining the equitable allocation of all system-wide cost savings under the agreement

Integrating Closed-loop Supply Chains and Spare Parts Management at IBM

Ever more companies are recognizing the benefits of closed-loop supplychains that integrate product returns into business operations. IBMhas been among the pioneers seeking to unlock the value dormant inthese resources. We report on a project exploiting product returns asa source of spare parts. Key decisions include the choice of recoveryopportunities to use, the channel design, and the coordination ofalternative supply sources. We developed an analytic inventory controlmodel and a simulation model to address these issues. Our results showthat procurement cost savings largely outweigh reverse logistics costsand that information management is key to an efficient solution. Ourrecommendations provide a basis for significantly expanding the usageof the novel parts supply source, which allows for cutting procurementcosts.supply chain management;reverse logistics;product recovery;inventory management;service management

A Heuristic for the Two-Echelon Multi-Period Multi-Product Location–Inventory Problem with Partial Facility Closing and Reopening

In this paper, the two-echelon multi-period multi-product location–inventory problem with partial facility closing and reopening is studied. For each product and period, plants serve warehouses, which serve consolidation hubs, which service customers with independent, normally distributed demands. The schedule of construction, temporary partial closing, and reopening of modular capacities of facilities, the continuous-review inventory control policies at warehouses, the allocation of customer demands to hubs, and the allocation of hubs to warehouses are determined. The service levels for stockout at warehouses during lead time and the violation of warehouse and hub capacities are explicitly considered. The proposed mixed-integer non-linear program minimizes the weighted summation of the number of different facilities and logistical costs, so that the number of different facilities can be controlled. Since the proposed model is np-hard, the multi-start construction and tabu search improvement heuristic (MS-CTSIH) with two improvement strategies and the modified MS-CTSIH incorporating both strategies are proposed. The experiment shows that the two improvement strategies appear non-dominated, and the modified MS-CTSIH yields the best results. The comparison of the modified MS-CTSIH and a commercial solver on a small instance shows the efficiency and effectiveness of the modified MS-CTSIH. The sensitivity analyses of problem parameters are performed on a large instance

An iterative method for the simultaneous optimization of repair decisions and spare parts stocks

In the development process of a capital good, it should be decided how to maintain it once it is in the field. The level of repair analysis (LORA) is used to answer the questions: 1) which components to repair upon failure, and which to discard, 2) at which locations in the repair network to perform the repairs, and 3) at which locations to deploy resources, such as repair equipment. Next, it should be decided what amount of spare parts to store at each location in the network in order to guarantee a certain availability of the product. Usually, the LORA and the spare parts stocking problem are solved sequentially. However, solving the LORA first can lead to high spare parts costs. Therefore, we propose an iterative approach to solve the two problems jointly. We find that the total costs are lowered with 3.2% on average and almost 35% at maximum in our experiments. A cost reduction of a few percent may be worth hundreds of thousands of euros over the life cycle of a capital good

An economic order quantity stochastic dynamic optimization model in a logistic 4.0 environment

This paper proposes a stock dynamic sizing optimization under the Logistic 4.0 environment. The safety stock is conceived to fill up the demand variability, providing continuous stock availability. Logistic 4.0 and the smart factory topics are considered. It focuses on vertical integration to implement flexible and reconfigurable smart production systems using the information system integration in order to optimize material flow in a 4.0 full-service approach. The proposed methodology aims to reduce the occurring stock-out events through a link among the wear-out items rate and the downstream logistic demand. The failure rate items trend is obtained through life-cycle state detection by a curve fitting technique. Therefore, the optimal safety stock size is calculated and then validated by an auto-tuning iterative modified algorithm. In this study, the reorder time has been optimized. The case study refers to the material management of a very high-speed train