Inventory management of repairable service parts for personal computers:A case study

Recent years have seen an increase of interest in the field of service parts inventory - particularly in computer industry. The computer industry is a highly competitive industry; products have to be repaired as quickly as possible, since slow repair can lead to loss of future business to competitors with better service reputations. A good reputation is therefore closely linked to the availability of spare parts on the market. Given this fact and using a real-life case study, this paper first elaborates on the management and control of service-parts inventory and presents a brief overview of the contemporary literature on the subject. Next the paper presents the solution approach adopted and the results of study, which indicate that significant savings can be realized through good management of service-parts inventory.

A multi-echelon inventory model for a low demand repairable item

Bibliography: p. 24.Stephen C. Graves

Application of METEOR to the evaluation of multi-echelon inventory models.

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Reliability applied to maintenance

The thesis covers studies conducted during 1976-79 under a Science Research Council contract to examine the uses of reliability information in decision-making in maintenance in the process industries. After a discussion of the ideal data system, four practical studies of process plants are described involving both Pareto and distribution analysis. In two of these studies the maintenance policy was changed and the effect on failure modes and frequency observed. Hyper-exponentially distributed failure intervals were found to be common and were explained after observation of maintenance work practices and development of theory as being due to poor workmanship and parts. The fallacy that constant failure rate necessarily implies the optimality of maintenance only at failure is discussed. Two models for the optimisation of inspection intervals are developed; both assume items give detectable warning of impending failure. The first is based upon constant risk of failure between successive inspections 'and Weibull base failure distribution~ Results show that an inspection/on-condition maintenance regime can be cost effective even when the failure rate is falling and may be better than periodiC renewals for an increasing failure situation. The second model is first-order Markov. Transition rate matrices are developed and solved to compare continuous monitoring with inspections/on-condition maintenance an a cost basis. The models incorporate planning delay in starting maintenance after impending failure is detected. The relationships between plant output and maintenance policy as affected by the presence of redundancy and/or storage between stages are examined, mainly through the literature but with some original theoretical proposals. It is concluded that reliability techniques have many applications in the improvement of plant maintenance policy. Techniques abound, but few firms are willing to take the step of faith to set up, even temporarily, the data-collection facilities required to apply them. There are over 350 references, many of which are reviewed in the text, divided into chapter-related sectionso Appendices include a review of Reliability Engineering Theory, based on the author's draft for BS 5760(2) a discussion of the 'bath-tub curves' applicability to maintained systems and the theory connecting hyper-exponentially distributed failures with poor maintenance practices

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The U.S. military presently manages about 88 billion dollars in spare and repair parts, consumables, and other support items. Department of Defense (DOD) inventory models which help wholesale item managers make inventory decisions concerning these items are based on the assumption that mean demand remains constant over time. In DOD this assumption is rarely met. During periods of declining demand, such as that associated with force reduction or equipment retirement, the inventory models usually keep stock levels too high, generating excess material. Recently, the amount of excess in DOD was estimated to be as high as 40 billion dollars. On the other extreme, during periods of increasing demand, the models generally provide too little stock, resulting in poor weapons system support. The purpose of this research was to develop an inventory model which does not rely on the assumption that mean demand is stationary. Use of the model would be appropriate when a known or predictable increase or decrease in mean demand is forecasted. Through simulation the model's performance was evaluated and compared with that of the Navy's Uniform Inventory Control Program (UICP) model. The results indicate that the proposed model significantly outperforms the existing model when mean demand is non- stationary. Additionally, the results indicate that the proposed model's performance is equal to or better than the existing Navy model under many stationary mean demand scenarios.http://archive.org/details/awholesalelevelc1094530557NANAU.S. Navy (U.S.N.) author

Advances in Inventory Management: Dynamic Models

In this study, we develop and analyze models incorporating some of the dynamic aspects of inventory systems. In particular, we focus on two major themes to be analyzed separately: nonstationarity in demand rate and unfixed purchasing prices. In the first part of the study, we consider an inventory system with a nonstationary demand rate. In particular, we consider critical service parts subject to obsolescence. Inventory management of such items is notoriously difficult due to their slow moving character and the high risks involved when they are not available or no more needed. In practice, there is a need for policies tailored for service parts taking these aspects into account and easy to implement. We propose an obsolescence based control policy and investigate its performance and impact on costs. We find that ignoring obsolescence in the control policy increases costs significantly and early adaptation of base stock levels can lead to important savings. In the second part of the study, we consider an inventory system where the supplier offers price discounts at random points in time. We extend the literature by assuming a more general backordering structure. That is, when the system is out of stock, an arriving customer either decides to be backlogged with a certain probability or leaves the system and becomes a lost sale. We derive equations to calculate optimal policy parameters and demonstrate that allowing backorders in face of random deal offerings can result in considerable savings

Discrete Event Simulations

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES