This research aimed to establish the power transformer fault management system by applying Sustainable Industrial Management Engineering (SIME.) method. The research tools were electrical and chemical testing. As power transformer is usually huge when it is damaged the possible way to manage such damage is to send such power transformer to the manufacturer’s plant for repair which requires long period of time and high costs of repair. As a result the researcher therefore establish the power transformer fault management system as a tool for assessing damage to decide whether power transformer repair should be instead done at the power station or not in order to decrease the number of power transformer returned to the manufacturing plant for repair. This would eventually help reduce costs and time for repairing power transformer and allows faster period of reuse of power transformer concomitantly. According to the result it would found that the power transformer fault management system by applying Sustainable Industrial Management Engineering (SIME) method could be used as guidance for decision making to have power transformers repaired at the power station as much as possible. This could help reduce average time spent for repair by 84.44 percent with the cost reduction by 68.62 percent when comparing to returning power transformers to the manufacturing plant. This could also be applied in planning for power transformer maintenance prior to the occurrence of any damage to power transformers further.

This research aimed to determine the optimal sand mold mixture’s ratio by using return sand bentonite water content and new sand component. Then the properties of the mixture according to the standards of American Foundrymen’s Society include the ability of compactability moisture content permeability and green compressive strength. This study applied mixture experiments and response surface methodology to determine an optimal sand mold mixture components condition. After the experiment and linear programming it indicated that the condition was at return sand (95.5387 %) bentonite (1.130102 %) water content (2.331196 %) and new sand (1 %). The green sand mold has compactability (58.37923 %) permeability (73.80148 %) moisture 6.5 % and green compressive strength (0.53 Kg/cm2). At this condition the cost is 11.31579 baths per kilogram.

This research aimed to study the awareness of impacts on global warming that is relevant to Home Economics knowledge base of Home Economics students Suan Dusit Rajabhat University and compare their awareness of impacts on global warming relevant to the Home Economics knowledge base considering their gender and year of study. The sample was 254 undergraduate students from Home Economics of Suan Dusit Rajabhat University. The research tool was questionnaire. The study revealed that the majority of the sample had been aware of impacts on the global warming relevant to Home Economics knowledge base in a high level. Most of them agreed with the awareness point that students wore the clothes that were appropriate with climate; for example they chose to wear light and thin clothes to reduce workload of air conditioners the students chose food containers made from natural materials instead of Styrofoam containers to reduce waste that took long time to decompose and they planted trees at their residences to reduce home temperature respectively. Comparing the awareness categorized by gender and year of study it was found that the students of Suan Dusit Rajabhat University of different genders had different levels of awareness of the impacts on the global warming relevant to Home Economics knowledge base. The awareness of female students was higher than that of male students and as for year of study the students of Suan Dusit Rajabhat University had different levels of the awareness of the impacts on the global warming relevant to Home Economics knowledge base. The second year students had higher awareness than the first third and fourth year students.

This research aimed to develop and evaluate a blended learning model for Home Economics students at Rajamangala University of Technology to increase teaching and learning effectiveness. The model development was collected from 9 experts. Questionnaires were used to ask for their opinions on the model’s 9 components which were 1) teaching and learning objectives 2) student readiness 3) instructor readiness 4) course plan 5) e-learning courseware design and development 6) teaching and learning environmental availability 7) Blended Learning instruction procedure 8) supportive activities and 9) monitoring and evaluation. To test for effectiveness the experimental one-group and pre-posttest method were used. The sampled group was a class of the first-year students enrolling in Science of Cookery Course at Rajamangala University of Technology Phra Nakhon. The findings suggested that the model was practical. Both the knowledge and self-directed learning post-test scores were higher than the pre-test scores. Moreover the students were highly satisfied with the model.

The purpose of this research was to construct the appropriate forecasting model for the export values of alcoholic beverages using three-time series analysis methods including Box-Jenkins method damped trend exponential smoothing method and combined forecasting method. Time series data from the website of Office of Agricultural Economics with total 199 months from January 1998 to July 2014 were used and divided into two series. The first 192- month data from January 1998 until December 2013 were used to build the forecasting models and the last 7-month data from January to July 2014 were used to compare the forecasting method accuracy via the criteria of the lowest mean absolute percentage error and root mean squared error. Research findings indicated that for all forecasting methods that had been studied combined forecasting method was the most accurate method and this model was when and represent the single forecasts at time t from Box-Jenkins method and damped trend exponential smoothing method respectively.