This research aims to develop an automatic gemstone color sorting machine to overcome the limitations of manual color sorting, which can be restricted by speed and accuracy. This study applies deep learning technology to analyze and classify gemstone colors precisely, developing an algorithm capable of accurately detecting and categorizing color shades. An automated conveyor system was also designed to efficiently transport gemstones through the color sorting process, allowing for continuous operation. The sorting machine works by capturing high-resolution images of the gemstones, processing them with software to classify color shades, and directing each gemstone to its designated position on the automated conveyor. Experimental results demonstrate that the automated color sorting machine, integrated with the conveyor system, achieves high speed and accuracy, significantly reducing labor costs and enhancing the efficiency of gemstone color sorting.
ปัจจุบันการตรวจสอบเฉดสีของพลอยถือเป็นขั้นตอนสำคัญในการประเมินคุณภาพ ทั้งในกระบวนการผลิตและการค้าขาย อย่างไรก็ตามการตรวจสอบเฉดสีที่ดำเนินการโดยมนุษย์นั้นมีข้อจำกัดหลายประการ ซึ่งหนึ่งในนั้นเป็นเรื่องความสามารถในการแยกเฉดสีที่ซับซ้อน ซึ่งอาจทำให้การตรวจสอบใช้เวลานาน และมีความแม่นยำต่ำ จากปัญหาดังกล่าว จึงได้พัฒนาแนวคิดในการสร้างเครื่องคัดแยกเฉดสีพลอยอัตโนมัติ โดยใช้ระบบ Computer Vision ร่วมกับระบบอัตโนมัติในการวิเคราะห์เฉดสีของพลอย เพื่อลดข้อจำกัดของการตรวจสอบด้วยมนุษย์ เพิ่มความแม่นยำและประสิทธิภาพในการทำงาน รวมถึงทำให้กระบวนการตรวจสอบเป็นไปอย่างรวดเร็วและมีมาตรฐานของเฉดสี GIA (Gemological Institute of America)
คณะวิศวกรรมศาสตร์
This thesis project was conducted to identify the optimal conditions for producing concentrated butterfly pea juice using vacuum evaporation to preserve key compounds in butterfly pea flowers, such as anthocyanins—natural pigments with high antioxidant properties. The study applies a Box-Behnken Design, a statistical method that facilitates analysis of multiple factors. The research focuses on the ratio of dried butterfly pea flowers to water, extraction temperature, and evaporation temperature, each of which has a direct effect on the preservation of key compounds, color, aroma, and flavor. The results indicate that using a dried flower-to-water ratio of 1:15, an extraction temperature of 60°C, and an evaporation temperature of 40°C under low pressure can minimize the loss of essential compounds and best retain the properties of the concentrated butterfly pea juice. Findings from this research provide a foundation for developing an industrial production process for concentrated butterfly pea juice and enhance the potential for creating new products from butterfly pea flowers.
คณะอุตสาหกรรมอาหาร
This research focuses on the development of mango powder using the foam-mat drying method, which is an effective technique for preserving the quality of fruit and vegetable products. Hydroxypropyl Methylcellulose (HPMC) was used as a foaming agent. The study evaluated the effects of HPMC on the chemical and physical properties, antioxidant activity, and shelf life of mango powder. The findings indicated that HPMC plays a crucial role in improving the foam stability before drying and enhancing the quality of the dried powder. This research provides a valuable approach to adding value to substandard mango yields and reducing agricultural waste. It also contributes to the development of high-nutritional processed food products with extended shelf life.
วิทยาลัยนวัตกรรมการผลิตขั้นสูง
Since organic rice storage silos were faced with an insect problem, an owner solved this problem using the expert system (ES) in the controlled atmosphere process (CAP) under the required standard, fumigating insects with an N2, reducing O2 concentration to less than 2% for 21 days. This article presents the computational fluid dynamics (CFD) assisted ES successfully solved this problem. First, CFD was employed to determine the gas flow pattern, O2 concentration, proper operating conditions, and a correction factor (K) of silos. As expected, CFD results were consistent with the experimental results and theory, assuring the CFD’s credibility. Significantly, CFD results revealed that the ES controlled N2 distribution throughout the silos and effectively reduced O2 concentration to meet the requirement. Next, the ES was developed based on the inference engine assisted by CFD results and the sweep-through purging principle, and it was implemented in the CAP. Last, the experiments evaluated CAP’s efficacy in controlling O2 concentration and insect extermination in the actual silos. The experimental results and owner’s feedback confirmed the excellent efficacy of ES implementation; therefore, the CAP is effective and practical. The novel aspect of this research is a CFD methodology to create the inference engine and the ES.