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Abstract
A recent study of material management in the U.S. construction industry shows that annual material costs are $82 billion. A small improvement in material costs would result in a substantial savings for contractors, which eventually would be passed on to owners due to competitive bidding.
Most contractors believe that buying material as soon as possible is most economical because it ensures them against price increases and avoids construction delays. However, they fail to recognize cost factors involved in purchasing material before it is needed. Such factors include financing costs, storage costs, handling costs, and other unpredictable costs such as theft or losses.
This research formulated a quantitative model to represent construction material inventories. The Japanese just-in-time philosophy was used to formulate the model. The model's objective is to identify the most economical material procurement policies. The effect of storage limitations and budget constraints on inventory costs in particular are considered.
A decision support system, the Optimizer, is presented and fully documented. The program is user friendly. It extracts data from the user, generates the model, then solves the model. The program utilizes Lindo. A case study is presented to test the model. Results indicate that decisions reached by using the new model lower total inventory cost by 7 percent.
Methods of implementing the Optimizer in inventory procurement cycles are presented. Two possible systems, a split system and a loop system, are developed.