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									  Analysis the Demand for Automobile Parts of Foreign Markets from
                             Thailand

  Prasert Wirotcheewan1*, Athakorn Kengpol2, Kazuyoshi Ishii3 and Youichi Shimada4
     1
       Department of Mechanical Engineering, Rajamangala University of Technology
                             Phra Nakhon, Bangkok, Thailand
2
  Department of Industrial Engineering, King Mongkut's University of Technology North
                                Bangkok, Bangkok, Thailand
   3,4
       Department of Industrial and Social Management Systems, Kanazawa Institute of
                               Technology, Ishikawa, Japan
                                 (prasertwirot@rmutp.ac.th)*



                                        Abstract
     The problem of this research is automobile part companies have variable demand
because of the world economic crisis and effect to automobile industry. Automobiles and
automobile parts demand in the world decrease. Automobile Industry of Thailand
received affect. Automobile part companies cannot export to foreign markets. The
companies want of forecasting demand quantity automobile parts for foreign markets to
Thailand by selecting model is the best accuracy. This paper presents analysis the
modeling for forecasting demand for automobile parts of foreign markets to Thailand
with traditional quantitative forecasting techniques and artificial neural networks. In this
study the automobile parts are wheels and including parts and accessories because of
Thailand exported the most in group of automobile parts. These five countries have
consistently demanded the largest number of wheels and including parts and accessories
are Japan, China, South Korea, Germany, and Indonesia. The research involves historical
collecting data for the period of 1997 to 2008. The evaluation functions of forecast error
are used. The results reveal that each country suits for each model depend with
considering error. We can use the forecasting demand for effective production planning
for manufactures.

Keywords: Analysis, Forecasting, Demand, Automobile parts

								
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