Nowadays an automotive industry steadily has been growing and playing a major role on economy development for many years. The crash box is one of the most important parts for safety but it was found that the crash boxes manufactured domestically are not met international standard requirements. This is due to process and material limitation. This process for automotive safety test requires high budget and there is unclear approach for specific test. Therefore a study of crash boxes referred to energy absorption project was conducted as the alternative materials for product. Consequently this project was aimed to design and test crash boxes which made from the diversity of the alternative materials such as aluminum aluminum reinforced by foam resin reinforced by fiberglass resin reinforced by water hyacinth and resin reinforced by water hyacinth and husk. In addition it was also emphasized in studying energy absorption behavior and physical deformation of crash boxes after dynamic and static energy being applied. The experimental works were applied for these tests in partly referenced to US NCAP and ECE R29 standard for automobile collision test. Testing all types of crash boxes indicated that the aluminum reinforced by foam type was able to absorb energy at 189 MJ/m3. It is higher than resin reinforced by water hyacinth and husk at 1 MJ/m3 as 188 times. Furthermore the comparison of the energy absorption (per unit volume) between the aluminum reinforced by foam type and the steel type from the previous project equivalent 20 MJ/m3 found that it is 8.45 times of difference. While the front impact test was not successful because the size of crash boxes was not suitable for the energy volume. It was a cause for non-available calculation of energy absorption value.

The aim of this research is to create the center of mass testing machine for vehicles with maximum mass 3000 kilograms. By the performance of this machine is able to determine the center of mass 3 axis by horizontal longitudinal and vertical. On the other hand the verities of mass from 50 to 250 kilograms and the several of weight distribution at horizontal and longitudinal are applied to the condition of testing for reasonable to the position of the center of gravity for vehicle. The result of research discovered to the performance of center of mass tester was activated following to test conditions. Furthermore the position of the horizontal of center of gravity depends on the weight distribution at horizontal axis and an increasing of mass under non-uniform along the longitudinal and horizontal axis. In term of the position of the longitudinal of center of gravity the weight distribution at longitudinal axis and an increasing of mass rate are points. Otherwise the weight distribution at longitudinal axis and an increasing of mass are effect to the position of the vertical of center of gravity.

This research proposes a Bayesian logistic regression model which is applied to the data from autoparts manufacturing machines. Factors related to defective and bad products are investigated. The proposed model is compared with the logistic regression using maximum likelihood method for parameter estimation. The data were collected from 132 machines in an autoparts manufacturing factory. The research found that useful life machine type 6 worker group 3 and 4 working step 1 and 2 influence to the risk of producing defective and bad products. When the useful life is increased by 1 month the risk of producing defective and bad products will be increased by 2.2%. The risk that the machine type 6 will produce defective and bad products is 4.078 times greater than the risk that the machine type will do. The risk that the worker group 3 will produce defective and bad products is 61.7% less than the risk that the worker group 12 will do. The risk that the worker group 4 will produce defective and bad products is 61.5% less than the risk that the worker group 12 will do. The risk that the working step 1 will produce defective and bad products is 2.831 times greater than the risk that the working step 4 will do. The risk that the working step 2 will produce defective and bad products is 13.8 % greater than the risk that the working step 4 will do. The parameter estimates from the Bayesian logistic regression are very close to the ones from the logistic regression using maximum likelihood method for parameter estimation

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.

The purposes of the research were 1) to study the consumers’ perception of the brand image of Toyota Camry Hybrid in Bangkok and 2) to compare demographic characteristics with consumers’ perception of the brand image of Toyota Camry Hybrid in Bangkok. The data was collected by using questionnaires completed by 200 respondents who bought Toyota Camry Hybrid from authorized dealers in Bangkok.Data analysis employed frequency average percentage and standard deviation. Statistic used for testing the independent sample was the independent t-test and the F-test to determine the difference with the one-way analysis of variance. The LSD was used to find a statistical difference. The study presented the following results: Consumers’ demographic in the research study were males (67.0%) age between 41-45 (38.5%) university graduates (85.5%) salaried employees (44.5%) and average monthly income between 50001-60000 baht (36.0%) The survey showed that consumers’ perception of the brand image of Toyota Camry Hybrid was the most brand recall in the highest level. Three top brands were Toyota Camry Hybrid (40.0%) Benz C 180 (31.0%) and BMW Series 5 (26.0%). Consumer’s brand recognition that was medium-size car was Toyota Camry Hybrid (100.0%). Brand image assessment of the Toyota Camry Hybrid that was the most brand recall to high technology was 99.5 percent and the perception of consumers towards the Toyota Camry Hybrid brand image overall was at high level. Having considered in each aspect strength and favorability of brand associations and uniqueness of brand associations were at the highest level and marketing communication was at the high level.The hypothesis testing showed that different age education and occupation of consumers had statistically significant differences at the level of .05 on their perception of Toyota Camry Hybrid brand’s image. On the contrary difference in gender and monthly income had no statistical significance for their perception of Toyota Camry Hybrid brand image.