This research aims to study the development of the Para rubber press machine with wrought pattern for continued 2-year project. Used natural Para rubber mixed in ta-Kuong by normally practical Para rubber farmers to evaluate the rubber press machine. It has developed the 11 roller the 3 plain duo sets of normal press rollers and the 2 duo sets of wrought rubber press rollers with the induction motor at 1430 rpm. The rotating transmission based on belts and chains. The evaluated results produced the dried Para rubber sheets thickness at 3.75 mm. on average as standard market need. From a robber sheet with enough patted on with a worker to carry the ta-Kuong to a top tray and a rubber press man to put the Para rubber piece to a machine on average the completed 185 wrought rubber sheets per hour in shorter time.

The objectives of this research are to propose a proper model for detecting defective machines in auto parts factories to apply the proposed model to the defective product data and to investigate the factors influencing on the machine producing defective products. A Bayesian hidden Markov model (HMM) is adopted. The results show that if the number of defective products increases the machine will be in the hidden bad state. The probability of changing from a hidden bad state to a hidden good state is higher than the probability of changing from a hidden good state to a hidden good state. The highest probability that the machine will be in a good state is at the work process 4 followed by 1 3 and 2 respectively. The highest probability that the machine will be in hidden good state is at the Worker no. 10 followed 9 3 12 7 2 1 6 11 4 8 and 5 respectively and The highest probability that the machine will be in the hidden good state is at the product type 1 followed by 2 and 3 respectively.

This research proposes a hidden Markov model for detecting machines with multiple fillers producing soft drink for quality control in order to reduce defective products. The proposed model is compared with a classical generalized estimating equations model (GEE). The monthly data the number of defective products the correctness and the time spending in correction were collected from a machine in a sample factory in Pratumthanee province. The two hidden states of the fillers are workable and unworkable. The states has a logistic distribution. The results show that the correctness of the filler error occurrence does not improve the probability of being in a unworkable state neither the period of time spending on correction. The current state seems to be the same as the previous state

This research proposes reliability analysis in order to find the probability that a machine will work properly the failure rates of a machine and the factors related to the failure rates. The data were collected from 8 types of machines in an autoparts manufacturing factory. They consist of the times measured from the first day of the study until the machine produces defective product workers and production steps. The study duration is 90 days. The results show that the probability that the machine type 4 will work properly more than days is 0.40 machine type 5 more than 68 days is 0.32 machine type 6 more than 72 days is 0.31 machine type 8 more than 85 days is 0.26 machine type 9 more than 109 days is 0.80 machine type 10 at more than 52 days is 0.38 machine type 11 more than 71 days is 0.32 and the probability that the machine type 12 will work properly more than 85 days is 0.26. The failure rate of the machine type 4 at day 51 is 6.61 machine type 5 at day 68 is 1.61 machine type 6 at day 72 is 0.77 machine type 8 at day 85 is 1.26 machine type 9 at day 109 is 1.31 machine type 10 at day 52 is 0.92 machine type 11 at day 71 is 1.24 and the failure rate of the machine type 12 at day 85 is 2.15. The factors influencing on the failure rates are worker group 2 and production step 3 at the significance of 0.05.

Thailand is an agricultural country. Most of the population consists of farmer. The rice is suitable to the climate of the country. And the main export of Thai is rice. The preparation of grain is also important.The farmer have to has an experience to choose the grain for growing the rice in farm. Good grian will give the high product. And good grain should completely free from contamination of disease and insect. Then it will be healthy seedlings. It is easy to harvest crops in a very high quality. Even it has good and high quality but it still has in impurities in the seed. Then the idea to create a project of sorting impurities from seeds. From the first it was built to help farmers to separate impurities such as grasses and husks. But the problem is the size of the maching is 140 x 150 x 160 cm which is larg and heavy then it makes the inconvenient to move. The preparation of the project is to develop an interest in sorting impurities in grain. The objective is to reduce the size to a smaller size than before. And increase the work more efficiency. The main aim is to sorting impurities in grain. Preparing the rice and put into the machin when power is opened. Rice will be flowing through the sieve which it works as a distribution and contamination. Then it will fail down into the sorting room. Impurities will be removed and the wind from the fan will blow the seeds. So we will get the good product and high quality. The results of the test. Wind is the best performance of the machine. Separating rice grains is 5.4 meters per second. The test of separating of the rice grains in 5 times and in the test of the 10 20 30 40 and 50 kg with a mixture of 10 percent of husk. the most effective of sorting rice is 10 kg. It can be isolated 99.30 percent with in 1.23 minutes.