Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 1998. / Includes bibliographical references.

Thesis PlanB (M.S.)--University of Wisconsin--Stout, 2009. / Includes bibliographical references.

Shrinking profit margins in the high technology industry has led companies to attempt to increase profits through an increased focus on after-market services. As part of that effort, service parts logistics, which manages the post-sales distribution of spare parts needed to maintain and repair products in use, has gained importance. In an effort to improve Service Parts Logistics (SPL) operations, we integrate facility location and inventory stocking decisions while classifying facilities based on their assignment; dedicated facilities that are assigned solely to individual customers (located on-site of the customer, serving only that customer), and shared facilities that are assigned to a subset of customers. The introduction of dedicated facilities simplifies the overall problem formulation in certain special cases. In one such special case where there is only one facility and none of the customers are within its service time window, the overall problem reduces to a binary knapsack formulation. This can be solved in pseudo-polynomial time through the dynamic programming algorithm for such problems. Nonetheless, even in the general case, we identify conditions under which a dedicated facility will always be opened. Computational results show that this observation is used by solvers as a preprocessing step, thus loosening some hard constraints. As a result, some of these problems are solved in less time than the corresponding problems without the dedicated facilities. However, dedicated facilities become advantageous mainly in sparse networks as opposed to dense networks. Apart from low network density, low holding cost and relatively high demand are two other system parameters that encourage the opening of dedicated facilities. SPL can be further improved by sharing inventory across shared facilities, which is already a common practice in real SPL systems. In this case, Markov chains can be used to estimate fill rates, but the process is iterative. However, under the low demand assumption of parts in SPL, we derive analytical formulae of estimating fill rates and thus incorporate inventory sharing within the network design and inventory optimization model. Special cases of this problem can be solved by an alternative binary knapsack formulation. Computational results show that large instances can be solved instantaneously, and we also identify a greedy heuristic that provides bounds on average within 0.12% of the optimal solution. We observe maximum benefit from inventory sharing when there exists large demand in the area overlapping the time window of both shared facilities and when inventory replenishment rates are high. However, we also identify conditions on the system parameters where inventory sharing could increase cost and/or decrease service in comparison with not-sharing. The combined problem of inventory sharing with customer dedicated facilities is formulated based on a binary knapsack structure. However, the problem size increases exponentially with solution time. Therefore, we construct another greedy heuristic by combining the inventory sharing heuristic and a special case algorithm for a single dedicated facility. A large size problem that takes almost a minute to be solved by conventional branch and bound is solved in less than a second using the greedy heuristic. We also show that for a given demand network, the combined problem achieves 40-60% reduction in total cost within 1% of the time taken by the problem without inventory sharing and without dedicated facilities. Another interesting result is that in some cases, adding new customers to a given inventory sharing system helps to reduce the cost and/or increase service. / text

Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Effective management of spare parts inventory is essential to companies because it influences inventory costs and asset utilization. The vast and diverse portfolio of spare parts, intermittent demand patterns and contradicting objectives between departments are examples of some of the factors that complicate Spare Parts Management (SPM). Managers of spare parts are faced with trade-off decisions between risk and cost on a daily basis. These decisions include, amongst many, determining appropriate stock levels and order frequencies. Despite the importance of SPM, decisions are however often made intuitively in practice with little factual support, and the decision-making process is commonly constrained within departmental silos. Even though there is a large body of academic knowledge on this topic, practical applications of spare parts inventory solutions lag behind theoretical studies. The majority of studies in literature focus on single components of SPM, such as demand forecasting and parts classification, whereas fewer studies consider the decision-making process itself. This study proposes a decision-making framework for spare parts inventory management. The framework is based on a wide-ranging literature review that focuses on capturing the essence of Spare Parts Management (SPM), but also acknowledges the interconnectedness of the problem. Therefore, core inventory management principles, as well as closely related topics such as Supply Chain Management (SCM) and Physical Asset Management (PAM), are studied in the context of spare parts. The broad scope of the literature study leads to a holistic approach to the problem and prevents sub-optimization. The proposed framework condenses principles from various fields of study (SCM, PAM, Classification and Inventory Management) into a stepwise methodology presented as a decision-making framework. The objective of the framework is to provide managers with a structured process, based on factual information, to enable better decision-making in the field. Furthermore, the framework aims to capture the fundamentals of SPM in a simplistic manner to ease the adoption of the framework in practice. A case study is conducted in the South African mining industry to validate the framework. The case study demonstrates that the framework is practical, provides structured guidance, and assists managers to make trade-off decisions in managing spare parts inventory. / AFRIKAANSE OPSOMMING: Effektiewe voorraadbestuur van onderdele is belangrik vir maatskappye omdat dit voorraadkoste en die benutting van bates beïnvloed. Die bestuur van onderdele is ’n komplekse probleem. Ondermeer is die portefeulje van onderdele items breed en divers, die vraagpatrone sporadies en word die voorraadvlakke geaffekteer deur kontrasterende doelwitte tussen verskillende departemente. Bestuurders van onderdele word daagliks gekonfronteer met besluite rakende risiko’s en kostes, soos om toepaslike voorraadvlakke te bepaal en om te besluit wanneer om bestellings te plaas. Hierdie besluite word dikwels intuïtief geneem met min feitelike ondersteuning en insette in die besluitnemingsproses word gereeld beperk tot sekere departemente. Ten spyte van die geweldige akademiese belang in die onderwerp, is daar min suksesvolle praktiese toepassings. Die meerderheid van studies in die literatuur fokus op spesifieke elemente van onderdele bestuur, soos vooruitskatting en klassifisering van parte, terwyl minder op die besluitnemingsproses konsentreer. Hierdie studie stel ’n besluitnemingsraamwerk vir die bestuur van onderdele voorraad voor. Die raamwerk is gegrond op ’n deeglike literatuurstudie wat die essensie van onderdele bestuur ondersoek, maar ook die interverbondenheid van die probleem in ag neem. Voorraadbestuurbeginsels en verwante onderwerpe soos Voorsieningskettingbestuur en Fisiese Batebestuur word dus bespreek. Die breë omvang van die literatuurstudie lei tot ’n holistiese benadering wat sub-optimering van die probleem voorkom. Die voorgestelde raamwerk som beginsels uit verskillende relevante studievelde op in ’n stapsgewyse metode wat voorgestel word as ’n besluitnemingsraamwerk. Die doel van die raamwerk is om bestuurders te voorsien met ’n gestruktureerde proses, gebaseer op feitelike inligting, om besluitneming in die veld te verbeter. Verder poog die raamwerk om die fundamentele konsepte in voorraadbestuur vas te vang in ’n eenvoudige manier sodat die raamwerk maklik geïmplementeer kan word in die praktyk. Die voorgestelde raamwerk is gevalideer deur middel van ’n gevallestudie in die Suid-Afrikaanse mynbedryf. Die gevallestudie toon dat die voorgestelde raamwerk prakties is, die besluitnemingsproses op ’n gestruktureerde wyse lei, en bestuurders help om beter, ingeligte besluite te neem.

by Cheung Chi-leung Stanley, Ha Wai-Hung Michael. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 78-79). / ABSTRACT --- p.iii / TABLE OF CONTENTS --- p.iv / LIST OF ILLUSTRATIONS --- p.vi / ACKNOWLEDGMENTS --- p.vii / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Company Background --- p.3 / Objective and Methodology --- p.9 / Chapter II. --- WHAT IS MRP II --- p.12 / Chapter III. --- MRP II SYSTEM IN XYZ COMPANY --- p.15 / Chapter IV. --- THE INVENTORY PROBLEMS --- p.22 / High Level of Excess and No Current Use Inventory --- p.23 / Engineering Changes --- p.23 / Forecast Fluctuation --- p.26 / Customer Order Cancellation --- p.28 / Management Reluctant to Write Off --- p.29 / Long Lead-Time of Components --- p.30 / Active Inventory Level Higher Than Management Expectation --- p.31 / Incorrect Purchase Order Time Bucket --- p.33 / Inefficient Re-scheduling Activities --- p.35 / Inefficient Time Fencing --- p.38 / Ineffective Control --- p.38 / Vendor Early Deliveries --- p.39 / Ineffective Priority of Purchasing Activities --- p.40 / Ineffective Follow-Up of Discrepancies --- p.40 / Unable to Project Inventory Within Tolerance --- p.41 / Alternative Parts --- p.42 / Goods in Transit --- p.48 / Consumption of Active Inventory and Reconciliation of Supply and Demand --- p.49 / Inaccurate Inventory Record --- p.52 / Space Limitation --- p.53 / Staff Training --- p.55 / Policies and Procedures --- p.57 / Cycle Counting --- p.57 / Chapter V. --- SUMMARY OF OBSERVATION --- p.60 / BIBLIOGRAPHY --- p.78