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.spare parts;end-of-life inventory management;phase-out returns

Customer Differentiated End-of-Life Inventory Problem

This paper deals with the service parts end-of-life inventory problem in a circumstance that demands for service parts are differentiated. Customer differentiation might be due to criticality of the demand or based on various service contracts. In both cases, we model the problem as a finite horizon stochastic dynamic program and characterize the structure of the optimal policy. We show that when customers are differentiated based on the demand criticality then the optimal structure consists of time and state dependent threshold levels for inventory rationing. In case of differentiation based on service contracts, we show that in addition to rationing thresholds we also need contract extension thresholds by which the system decides whether to offer an extension to an expiring contract or not. By numerical experiments in both cases, we identify the value of incorporating such decisions in service parts end-of-life inventory management with customer differentiation. Moreover, we show that these decisions not only result in cost efficiency but also decrease the risk of part obsolescence drastically

End-of-Life Inventory Decisions of Service Parts

With the spurt of technology and innovation the life cycles of parts and products have become shorter and service parts enter their final phases earlier. Final phase of a typical service part starts once the part production is ceased and ends when the last service or warranty contract expires. One popular tactic, in practice, to sustain service operations is placing a final order. The prime challenge of a firm while deciding a final order quantity is to minimize inventory-carrying costs together with the risk of obsolescence at the end of the planning period. In this study, end-of-life inventory decisions for an array of products including both consumer electronics and capital-intensive products are investigated. For consumer electronics we show that considering an alternative service policy, such as swapping the defective product with a new one, besides a regular repair policy improves cost efficiency. Moreover, for capital-intensive products we study systems with phase-out returns and systems with customer differentiation in the end-of-life phase. Our analysis reveals that taming the uncertainty associated with phase-out arrivals engenders a remarkable efficiency improvement. Moreover, including rationing decisions in the end-of-life phase enhances the performance of the system by a significant reduction in cost and risk of obsolescence

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

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

Design and implementation of high power, high linearity stacked RF FET switches in a 250 nm silicon on sapphire process

peer reviewedThe RF circuitry in new generation mobile handsets is continuously becoming smaller while containing more functionality. Silicon-on-sapphire (SOS) technology is an advanced active device process that eases the fabrication of advanced wireless components on very high resistivity substrates. This paper presents the basic theory and resulting trade-offs regarding RF FET switches in order to achieve a high power handling capability, low insertion loss and high linearity of the latter. A combined RF switch consisting of eight stacked FETs, used in a high power switched capacitor banks, is designed with an insertion loss of 1 dB at 2 GHz for a transmitter power of 39.5 dBm. The presented configuration has a high linearity featuring P 1dB and IIP3 of 49.2 dBm and 54.3 dBm, respectively. © 2011 Engineers Australia

End-of-life inventory decisions for consumer electronics service parts

We consider a consumer electronics (CE) manufacturer problem of controlling the inventory of spare parts in the final phase of the service life cycle. The final phase starts upon termination of the production of the part and goes on till the last service contract or warranty period expires. Final orders are considered as one tactic to satisfy demand during this period and mitigate the effect of part obsolescence at the end of the service life cycle. Previous works on final order quantity consider just repair of defective products during this phase. However, since there is a remarkable price erosion particularly for consumer electronic products it is much more cost effective to meet consumer demand for service parts by means of an alternative policy such as replacement of the defective product by a new one. Hence, we develop an exact formulation for the expected total cost function and based on that we propose policies trying to find simultaneously the optimal final order quantity and time to switch from 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

Mathematical modeling of floating stock policy in FMCG supply chains

The floating stock distribution concept exploits inter-modal transport to deploy inventories in a supply chain in advance of retailer demand. It is appropriate in case of batch production and containerized transport of standard product mixes. In this way response times are reduced and storage costs can be reduced as well by having products in the transport-pipeline. This concept was earlier analysed using a simulation approach and showed to be efficient under simplifying assumptions for the demand distribution. In this paper we present two mathematical models to analyse this policy while backlogging is allowed. The first one tries to optimize the advanced shipping time of containers to inter-modal terminal, and the second one optimizes the total number of containers in pipeline and terminal. In fact, in both policies containers are shipped to a terminal before the demand is realized in order to benefit from less storage cost at the terminal by utilizing the shipping time and also free storage cost period at inter-modal terminals. A comparison is made with the simulation outcomes of applying previously developed strategies which shows that this concept has advantages in inventories over other strategies