Inventory management.

Abstract

Normally, items waiting to be purchased or purchase are considered to be in inventory. One of the most pressing problems in the manufacturing and use of goods is the control of this inventory. Many companies experience financial difficulties each year due to a lack of adequate control in this area. Whether it is raw material used to manufacture a product or products waiting to be purchase, problems arise when too many or too few items are available. INTRODUCTION The basic decisions to be made once a source has been determined are how much to order and when to order. Inherent in this analysis is the concept of demand. Demand can be known or unknown, probabilistic or deterministic, constant or lumpy. Each of these characteristics affects the method of approaching the inventory problem. For the unknown demand case a decision must be made as to how much the firm is willing to risk. Normally, the decision would be to produce some k units for use and then determine after some period of time to produce more or to discontinue production due to insufficient demand. This amounts to the reduction of the unknown demand situation to one of a lumpy demand case after the decision has been made to produce the batch of a finite size. Similarly, if a decision is made to begin production at a rate of n per day until further notice, the unknown demand situation has been changed to a constant known demand case. Lumpy demand, or demand that occurs periodically with quantities varying, is frequently encountered in manufacturing and distribution operations. It is distinguished from the known demand case. This second case is that of a product which has historic data from which forecasts of demand can be prepared. A factor of concern in these situations is the lead time and the unit requirement on a periodic basis. The following are the major factors to be considered in the modeling of the inventory situation. Demand is the primary stimulus on the procurement and inventory system and it is the justification for its existence. Specifically the system may exist to meet the demand of customers, the spare parts demand of an operational weapons system, the demand of the next step in a manufacturing process, etc. The characteristic of demand, although independent of the source chosen to replenish inventories, will depend on the nature of the environment giving rise to the demand. The simplest demand pattern may be classified as deterministic. In this special case, the future demand for an item may be predicted with certainty. Demand considered in this restricted sense is only an approximation of reality. In the general case, demand may be described as a random variable that takes on values in accordance with a specific probability distribution. Procurement quantity is the order quantity, which in effect determines the frequency of ordering and is related directly to the maximum inventory level. Maximum shortage is also related to the inventory level. TYPES OF INVENTORY MODELS Deterministic models assume that quantities used in the determination of relationships for the model are all known. These quantities are such things as demand per unit of time, lead time for product arrival, and costs associated with such occurrences as a product shortage, the cost of holding the product in inventory, and that cost associated with placing an order for product. Constant demand is one case that can be analyzed within the category of deterministic models. It represents very effectively the case for some components or parts in an inventory which are used in multiple parents, these multiple parent components having a composite demand which is fairly constant over time. RESEARCH OBJECTIVE 1. Develop a framework for inventory management 2. Classify the inventory 3. Provide a demand forecasting method International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463 Vol. 3 Issue 6, June-2014, pp: (456-459), Impact Factor: 1.252, Available online at: www.erpublications.com Page | 457 SCOPE OF STUDY The research is carried out by analyzing one year of data provided by workshop. The model of bus that has been considered in this research is Mod 1, Mod 2, Mod 3, And Mod 4. Fig 1 shows the compiled yearly data for part 01, front glass. The demand data will be modeled and analyzed and the demand for part 01 shall be forecasted for first month of next year. A quick analysis of the forecasted data shows that the demand trend for part 01 is increasing. This could be due to the buses start running many year ago being returned to workshop for repair. In chapter 3, the research will interpret the demand patterns and chapter 4 will show the inventory policies for such phenomenon.