Induction Heating Machine (IHM) is a crucial device in the jewelry industry, utilizing electromagnetic fields to generate heat and join precious metals. This research focuses on developing a Dual Coil Induction Heating Machine (Dual Coil IHM) to enhance production efficiency and reduce costs in jewelry factories using Electromagnetic Analysis (EMA) through Ansys Maxwell software. The research process began with testing a single-coil IHM under real operating conditions and using EMA to analyze the generated magnetic flux density (B). Subsequently, dual-coil configurations in Parallel and Series arrangements were designed and compared. The experimental results revealed that the series dual coil produced a higher magnetic flux and allowed for optimizing current (I), frequency (f), number of coil turns (N), and coil spacing (d) for better manufacturing performance. The findings indicate that the series dual-coil IHM can double production capacity compared to the conventional single-coil model. Furthermore, EMA technology minimizes physical testing, reduces errors, and enhances precision in designing industrial machinery for the jewelry manufacturing sector.
1.ข้อจำกัดของเครื่องทำความร้อนแบบเหนี่ยวนำขดลวดเดี่ยว 2.ความต้องการเพิ่มประสิทธิภาพการผลิตและลดต้นทุน 3.การประยุกต์ใช้เทคโนโลยีการจำลองทางแม่เหล็กไฟฟ้า (EMA) 4.แนวโน้มการเติบโตของอุตสาหกรรมเครื่องประดับในประเทศไทย 5.การพัฒนาองค์ความรู้ด้านเทคโนโลยีการผลิต
คณะวิศวกรรมศาสตร์
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คณะวิทยาศาสตร์
The development of a fruit spoilage detection system originates from the need to reduce agricultural product losses, a global issue affecting both the agricultural and food distribution industries. Spoiled fruit can negatively impact product quality and result in significant economic losses. The primary goal of this system is to assist in screening and removing unsuitable fruit from the supply chain, thereby preserving product quality and meeting consumer demands for fresh produce. The system was designed to simulate the sorting process by utilizing images as a key factor in detecting spoiled fruit. Experimental results demonstrated high efficiency and rapid prediction capabilities, highlighting the system’s potential for practical applications.
คณะวิศวกรรมศาสตร์
Under The National Broadcasting and Telecommunications Commission (NBTC), the Telecommunication Enforcement Bureau collects a lot of data on service quality by monitoring and controlling the quality of telecommunications services, mainly by assessing mobile network infrastructure. The NBTC used Microsoft Excel for data analysis but became ineffective and slow. We used Python programming for preparation, analysis, and data processing to address this. Raw data was obtained from the Syberiz program in CSV format, processed in Python, and displayed on a dashboard. The dashboard, developed using Power BI, meets NBTC's telecommunications quality standards. It features maps, test results, and graphical representations. This method enhances the dashboard's appearance and usability and speeds up data processing and visualization compared to Microsoft Excel. This project is primarily designed to help the Telecommunication Enforcement Bureau's operations by making data processing and display for telecommunications quality monitoring faster, more effective, and easier to use.