A Procurement Planning Improvement by Using Linear Programming and Forecasting Models

As known that an appropriate procurement policy is one of industrial competitive advantages, an over or under inventory in procurement system can significantly affect management in budget spending on stock of raw material. The objective of this research, therefore, is to improve a procurement planning in order to achieve an optimal inventory level and to optimize the purchasing policies by applying linear programming and forecasting models, which are corresponded with each of purchasing conditions. At the first phase, the trend in material's price is analyzed, then Microsoft Excel CB Predictor programme add-ins is applied to forecast the results, after that the model is optimized by using models in program Microsoft Excel add-ins. Finally, the models have been tested by improving raw materials purchasing since January 2004 to June 2005 (for 18 months), and then the results are compared on purchasing efficiency with the actual purchasing. The research results show that the mathematical models can improve the raw materials procurement planning. Moreover, performance index in inventory policies are increased 83.33%, performance index order quantity in ratio from Japan' suppliers are increased 44.45%, performance index supplier partnership are increased in 44.45% and total cost are decreased 0.68%. The other results, limitations and recommendations are also presented.