The research purposes were to analyze and search for wastes in the planning process and transportation of the automobile parts of a transport company in Samut Prakan using Makigami Lean and ECRS Techniques. The informants used in this study were the support staff working the planning process and automobile part transportation for the car assembly factory in the industrial estate Rayong Eastern Seaboard. Six employees from different work units took part in the in-depth interview as the research tool for the data collection. Statistics used in the data analysis including percentage and workflow analysis with related management tools. The study indicated that searching for the waste in the technical planning process with Makigami Lean and ECRS Techniques could help reduce the work time for 1060 minutes in each step.

The objectives of this research were to select the most appropriate forecasting model for uncertain demand of hot-rolled steel and to find the purchase amount and the reorder point of some raw materials in order to minimize the total cost of production in an iron and steel production planning. The three forecasting models which were exponential model ARIMS model and the proposed Bayesian model were studied. An iron and steel factory in Samutprakarn province was a prototype for this study. Because of their uncertain high demand the Steel H-Beam Steel plate steel round bar and black steel round bar with various sizes were selected and their parameters including demand rate inventory cost back order cost and setup cost were collected. The study found that the proposed Bayesian forecasting model is the most appropriate. The predicted demand and all parameter values were used to find the purchase amounts and the reorder points of the raw materials under the (rQ) policy of the stochastic inventory model.