A dissertation submitted to the Faculty of Engineering, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science in Engineering. Johannesburg, November 1994. / Inventories are produced, used (e.g. for raw materials, supplies, spare parts, and So forth) or distributed by every organisation. Moreover, inventories represent a major investment from the perspectives of both individual firms and entire national economies. In addition, enormous costs are incurred in the planning, scheduling, control and actual carrying out of replenlshment-Iprocuretnentl related activities. Interest in the subject of inventory management is constantly increasing, yet Silver and Petarsonlll (P(eface) found that "although invi ,~ory management ha.l been studied in considerable depth from a theoretical perspective, yet, those of us who, throuah consulting work, come into. clos>!)contact with mananerlal decision procedures in this arer are repeatedly surprised to find how limited, and ad hoc, many of the existing decision systems actually are. The rate at which theory has been developed has far outstripped the rate at which decision practices of firms have been successft,Jlly upgraded. A major g~o has existed between the theoretical solutions, on the one hand, and the real world problems, on the other". Inventory control is the science-based art of ensuring that lust enough inventory (or stockl is held by an organisation to meet both its internal and external demand commitments economically. There can be disadvantages in holding either too much 01 too little inventory. Therefore, inventory control is primarily concerned with obtaining the correct inventory with compromise between these two extremes. The control and maintenance of inventories is a problem common to all enterprises in any sector of a given economy. The primary aim of this study is to identify What the inventory policy of a company shoull;I be to Secure a reduction in inventory-related costs while maintaining a high level of customer service. Lewis(2) defines two bMlt:~ tvpes of inventory policy. Those in which decisions concerning replenishment are based on the lellel of inventory held, are known as "fixed-order quantity models" or "re-order level policies" and those in which such declslons arc made on a time basis are known as "fixed-time period models" or "re-order cycle policies". According to Nadder(3) (7I 11) the basic distinction between fixed-order quantity models and fixed-tlme period models is that the former are "event-triggered" while the latter are "time-triggered". That is, a fixed-order quantity model initiates an order when the "event" of reaching a specified re-order level occurs. This event may take place at any time, depending on the demand for the items considered. In contrast, the fixed-time period model is limited to placing orders at the end of a predetermined time period; hence, the passage of time alone "triggers" the model. In this thesis, we shall discuss both classical inventory models and heuristic models. We shall also conduct an investigation into the factors affecting high levels of inventory ~ mainly lead times (supplier and internal lea' times) in relation to spare 9arts in the heavv-dutv truck and bus industry. The thesis also suggests guidelines for controlling stock or these types of commodities in a practical environment. This will be done by either researching the existing inventory models or developing new inventory models or a combination of both, the intention being not to look for absolute optimisation, but rather to achieve significant improvements over current operations. / GR 2016

by Leung Kwong-chuen. / Bibliography: leaves 193-195 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1982

by Lau Tsz Chuen. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves 58-61). / ABSTRACT --- p.i / TABLE OF CONTENT --- p.ii / LIST OF TABLES --- p.iii / LIST OF FIGURES --- p.iii / Chapter CHAPTER ONE --- INTRODUCTION --- p.1 / Chapter CHAPTER TWO --- LITERATURE REVIEW --- p.6 / JIT AND QUALITY --- p.7 / JIT AND INVENTORY CONTROL --- p.8 / "INSPECTION IMPRECISION, TOLERANCE LIMITS AND PROCESS CAPABILITY" --- p.11 / PHILOSOPHY OF TAGUCHI AND MEASUREMENT IMPRECISION --- p.17 / PROCESSING AND INSPECTION TIME VARIATIONS --- p.19 / RESEARCH OBJECTIVES --- p.19 / SIGNIFICANT OF THE RESEARCH --- p.20 / Chapter CHAPTER THREE --- EXPERIMENTAL DESIGN --- p.23 / HYPOTHESIS STATEMENTS --- p.23 / SIMULATION MODEL --- p.24 / PERFORMANCE MEASURES --- p.26 / SPECIFICATION OF COST PARAMETERS --- p.27 / FACTORIAL DESIGN --- p.27 / Chapter CHAPTER FOUR --- RESULT --- p.30 / TWO-FACTOR INTERACTIONS --- p.35 / THREE-FACTOR INTERACTIONS --- p.41 / Chapter CHAPTER FIVE --- CONCLUSION --- p.46 / RECOMMENDATION FOR FURTHER RESEARCH --- p.47 / APPENDIX --- p.48 / REFERENCES --- p.58

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Thesis (M.B.A.)--Boston University

Xie Lei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 50-53). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Related Literature --- p.2 / Chapter 2 --- Notations and Model Formulation --- p.8 / Chapter 3 --- The Optimal Replenishment Policy --- p.15 / Chapter 3.1 --- Preliminaries --- p.15 / Chapter 3.2 --- The optimal replenishment policy at the second decision point --- p.17 / Chapter 3.3 --- The optimal replenishment policy at the first decision point --- p.19 / Chapter 4 --- Specialized Case: No Delivery Information Delay Model --- p.21 / Chapter 4.1 --- Special Case 1: The Realized Proportional Factor rt = 0 --- p.23 / Chapter 4.2 --- Special Case 2: The Realized Proportional Factor rt = 1 --- p.23 / Chapter 4.3 --- Comparison of the Two Special Cases --- p.24 / Chapter 4.4 --- "The Case with Partial Delivery (rt e (0,1))" --- p.26 / Chapter 4.5 --- Comparison of the Delivery Information Delay Model and the No Delivery Information Delay Model --- p.33 / Chapter 5 --- Nonoptimality of a Base-Stock Policy in Numerical Examples --- p.36 / Chapter 6 --- Conclusion and Future Work --- p.39 / Chapter 6.1 --- Conclusion --- p.39 / Chapter 6.2 --- Future Work --- p.40 / Chapter 7 --- Appendix --- p.42

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

The main idea of this research to solve the problem of inventory management for the paper industry SPM PVT limited. The aim of this research was to find a methodology by which the inventory of raw material could be kept at minimum level by means of buffer stock level.The main objective then lies in finding the minimum level of buffer stock according to daily consumption of raw material, finding the Economic Order Quantity (EOQ) reorders point and how much order will be placed in a year to control the shortage of raw material.In this project, we discuss continuous review model (Deterministic EOQ models) that includes the probabilistic demand directly in the formulation. According to the formula, we see the reorder point and the order up to model. The problem was tackled mathematically as well as simulation modeling was used where mathematically tractable solution was not possible.The simulation modeling was done by Awesim software for developing the simulation network. This simulation network has the ability to predict the buffer stock level based on variable consumption of raw material and lead-time. The data collection for this simulation network is taken from the industrial engineering personnel and the departmental studies of the concerned factory. At the end, we find the optimum level of order quantity, reorder point and order days.

This thesis studies three problems related to inventory control. The first problem is motivated by the need to eliminate the bullwhip effect in a supply chain. An important source of this effect is the inventory control policy, which is originally designed to smooth production in response to demand variation along the supply chain arising from the customers. To address this issue, we propose an estimation method based on the control variate technique. A byproduct of this approach is a stabilizing inventory control policy. We evaluate the effectiveness of the proposed method using the models from the literature. Generally, the derivation of the inventory policies requires the knowledge of the specific demand distribution. Unfortunately, in several cases the demand is not observable in a direct way. The second problem is motivated by a practical application where only partial demand information is observable. Towards this end we derive estimators of the first two moments of the (daily) demand by means of the renewal theoretical concepts. We also propose a regression-based approximation to improve the quality of the estimators. A series of numerical studies are carried out to evaluate the accuracy and precision of the estimators and to investigate the impact of the estimation on the optimality of the inventory policies. The last part of this dissertation studies a periodic-review inventory system with regular and emergency orders. Emergency orders, characterized by shorter lead-time, higher ordering cost and higher setup cost, are placed when the inventory level becomes critically low. Based on our assumptions, we formulate a dynamic programming model and prove the optimality of state-dependent sS type polices for both emergency and regular orders. We also derive analytic properties of the optimal policies. We gain some managerial insights into the optimal policies and cost performance from numerical studies.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 199-201). Also available on the Internet.