วารสารวิชาการเทคโนโลยีอุตสาหกรรม (J. Ind. Tech.) อยู่ในฐานข้อมูล TCI กลุ่ม 2 (2563) มีค่า JIF = 0.094 | The Journal of Industrial Technology (J. Ind. Tech.) is indexed in TCI Tier 2 (2020) with impact factor, JTIF 0.094

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Mathematic Model by Response Surface Methodology and Artificial Neural Network for Predict Result of Tensile Shear and Nugget Size of Zinc Coated Steel JIS G3313 Welded by Resistance Spot Welding

This research described to the determine an optimization mathematic model using response surface methodology in central composite design method and artificial neural network (ANN) for predicting the of tensile shear and nugget size in the zinc coated steel JIS G3313. The following resistance spot welding (RSW) parameters were studied: the welding current, welding time, and electrode force. The resulting materials were examined using tensile shear tests which were observed nugget size and microstructure with scanning electron microscopy (SEM). The microstructure phenomenon could be explained by the welding optimum condition that fine pearlite and intensity in heat affected zone. The research results reveal that an optimum RSW parameters were welding current of 12 kilo amperes, welding time of 9 cycle and 1.5 kilo newton electrode force. The fine acicular ferrite occurred in the nugget size, which results in increased welding material high mechanical property. The ANN model with the proposed mathematical model, which tensile shear represents 3 neurons for the input 10 neurons for 1 hidden layer and 1 output neurons (3-10-1). The ANN model was developed to establish of the nugget predict represents 3 neurons for the input 5 neurons for 1 hidden layer and 1 output neurons (3-5-1). The mean square error (MSE) and coefficient of determination (R2) for tensile shear predict was showed that of 0.0026 and 0.956 respectively, which nugget size predicted MSE of 0.0004 and R2 of 0.958. This research, the related manufacturing sector can use research data and mathematical models was used to predict and quality control of the RSW processes to obtain tensile shear and the nugget size according to the acceptance criteria.

Design and Developed Product the Kindergarten Classroom Furniture with Rubber Wood Using Quality Function Development

This research is to apply a Quality Function Deployment (QFD) technique for designing and developing rubber wood furniture of a kindergarten classroom. The objective of this research is to design and create the classroom furniture by focusing on the shape and usability according to the user requirements. The methodology began with a survey in the kindergarten classroom instruction in order to specify of the sample groups. After that the user requirements were collected by using the designed questionnaires. The collected data from the questionnaires, such as the importance requirement scores, was calculated and then analyzed by the QFD technique. The analysis of QFD technique was divided in to two matrixes, including the furniture product planning matrix and the furniture part deployment matrix. The furniture product planning matrix was related to translate the user requirements to the technical requirements, while the furniture part deployment matrix was about the translation of the technical requirement to the part characteristics. The results of this research showed that the QFD technique was able to design and develop the shape and usability of the kindergarten classroom furniture that responded to the user requirements. The survey results from the users revealed that the average of satisfaction values in case of all new products were greater than that of the previous products from 3.437 scores to 4.373 scores, which increased approximately 22.23 percentage.

Assessment of Wind Energy Potential in Thailand Based on Using the Multiple-Weibull Distribution

Wind energy potential analysis is a design key to maximize wind turbine efficiency and annual energy output. Typically, the annual wind speed frequency is represented by a Single-Weibull distribution curve in spite of strong and calm wind patterns could occur through a year in many regions in the world, Thailand for instance. For this reason, wind energy potential should be analyzed by Multiple-Weibull distribution curves which are the representative of the meteorological seasons due to the monsoon’s effect. Therefore the objective of this study is to compare the accuracy of the Single-Weibull distribution and the Multiple-Weibull distribution in assessment of wind energy potential. The comparison was made between these two statistical distribution functions and the actual wind speed distribution (measured wind speed frequency) in order to determine the level of credibility of these two distribution functions. The wind speed data employed in this study was measured at Lamtakhong dam site in Nakhon Ratchasima province, Thailand. As the results, the error between the Single-Weibull distribution was 16.46% where the error between the Multiple-Weibull distribution was 14.82%, it was revealed that the smaller error, the higher reliability. Two of the most widely used wind turbines (Enercon E-30 and Windspot) were selected to verify the Multiple-Weibull concept. Approximately 40% increase in annual energy yield by using this method. So, the results confirmed that the Multiple-Weibull distribution is valid for the assessment of the annual energy production of wind turbines. Therefore, this will be a practical method for achieving the optimal design of stall-regulated wind turbine in the further work.
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วารสารวิชาการเทคโนโลยีอุตสาหกรรม ปีที่ 14 ( 2561 )

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วารสารวิชาการเทคโนโลยีอุตสาหกรรม ปีที่ 13 ( 2560 )

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