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

Model Development for Auto Spare Parts Inventory Control and Management

The immense dynamics and criticality of spare parts and the large revenues accrued, as essential motivating factors for providing control in manufacturing companies has never showed any sign of decrease. In fact, in the vast technological environment of today the complexities of Spare Parts Inventory Control enjoys more insights from analysts (in the Management Science, Information Technology and Industrial/Mechanical Engineering fields) as inventory policies get modeled to ensure customer satisfaction. In other words manual ways of handling inventory has failed to cope with factors like stochastic demands, better service levels, and shorter lead times and providing perfect heuristics for Inventory-related decision making. To this end, significant results for forecasting spare parts requirements can be achieved through the use of novel decision models. Besides the selling of vehicles, the spare parts of various models of heavy duty vehicles are stored and managed by the company. The management of these models which is complex was further complicated by the vast number of parts required in each model. In fact, more than 20,000 active parts needed to be controlled. The management of these parts can only be done with the aid of a computer; hence the spare parts complex has a computerized spare parts inventory database. Each of the parts that is supplied or replenished is continuously keyed into the computer and the inventory stock parameters are updated automatically. The company uses a software package for its inventory control. This is used to identify the part number of the spare parts. From the part number, the location of the spare parts in the stock room is identified. Key Words: Spare parts inventory, Information Technolog

Enabling customer satisfaction and stock reduction through service differentiation with response time guarantees

In response to customer specific service time guarantee requirements, service providers can offer differentiated services. However, conventional customer differentiation models based on fill rate constraints do not take full advantage of the stock reduction that can be achieved by differentiating customers based on agreed response times. In this paper we focus on the (S − 1, S, K) model with two customer classes, in which low priority customers are served only if the inventory level is above K. We employ lattice paths combinatorics to derive the exact distribution of the response time (within leadtime) for the lower priority class and provide a simple and accurate approximation for the response time of the high priority class. We show that the stock levels chosen based on agreed response times can be significantly lower than the ones chosen based on fillrates. This indicates that response time guarantees are an efficient tool in negotiating after-sale contracts, as they improve customer satisfaction and reduce investment costs

Computation of order and volume fill rates for a base stock inventory control system with heterogeneous demand to investigate which customer class gets the best service

We consider a base stock inventory control system serving two customer classes whose demands are generated by two independent compound renewal processes. We show how to derive order and volume fill rates of each class. Based on assumptions about first order stochastic dominance we prove when one customer class will get the best service. That theoretical result is validated through a series of numerical experiments which also reveal that it is quite robust.Base stock policy; service measures; two customer classes; compound renewal processes