Nowadays one of major problems of SMEs is improperly planning the production to serve for the true demand of customers. Therefore this research was set the objective to apply forecasting techniques to predict the right demands and feed them together with other constraints as inputs for the LP model in production planning to get maximum profit and also conform to the restriction constraints such as production processes sales volume labor constraints inventory and investment requirements. As a result from this study the Decomposition Technique by Minitab program was the most accurate technique for sales forecasting of Quilt Products of Hmon-Oon Group. The sales forecasting information was then used as input to a mathematical model (LP) targeting maximized profit processing by Solver program in Microsoft Excel 2010. Eventually the business can gain more benefit by using this method from 358830 Baht in one quarter to 504425 Baht or 40.57% increase. Cost of inventory decreases from 17764 Baht to 16670 Baht or 6.16% decrease. Production labor hours in one quarter decreases from 2984.12 hours to 2378.77 hours or 20.29% decrease

The objectives of this research were to find the distribution of food demand for laying hens and to find the optimum amount of that food production which had minimum cost. The data consisted of customer purchase orders for the food of laying hens price of food for laying hens cost per unit for the food inventory cost related to food of laying hens in which the food was out of stock such as fine overtime urgent purchase for material. They were collected in 2008-2009 form a factory in Nakhonratchasima province. The collected data were analized in order to explore the distribution of the monthly food demand for the laying hens and to see the rate of inventory per unit. The results were used in the stochastic linear programming model for aggregate planning in which the optimum production minimum cost could be obtained. Programming algorithm in MATLAB and tools in Linprog software were used to get the solution. The distribution of the food demand for laying hens and the random numbers were used in the model. The study found that the distribution of food demand for laying hens every month has normal distribution (January to December). The monthly average amount of production from January to December were 10936.94 12913.74 11898.12 13096 15443.26 14916.33 10322.64 10818.21 11393.11 11700.72 9706.05 and 11702.05 respectively. The minimum total cost average for 12months was Baht 62422386.98.

The purposes of this research were to study demand forecasting and production planning. The case study company manufactured the fish sauce product that was made to stock. To design the system the sale data was studied in order to choose the appropriate forecasting technique for the sale data. After using the system with the company case study it revealed that the prediction system can forecast the production of 1126570 units in July 2008 whereas the total sales were 1134322 units. The difference was equal to 2718 units or 0.69 percent of the actual sales which was a total cost of 116280 baht which was more equivalent to the actual sales predicted by a sole experienced decision maker who predicted the production at 1274098 units. The difference was equal to 139776 units or 10.97% percent of the actual sales which mean 2096640 baht of total cost