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.
การเก็บรักษาข้าวใน ไซโลเก็บข้าวอินทรีย์ เป็นแนวทางสำคัญในการรักษาคุณภาพข้าวและลดการสูญเสียหลังการเก็บเกี่ยว อย่างไรก็ตาม ปัญหาการปนเปื้อนของแมลงศัตรูข้าว เป็นอุปสรรคสำคัญที่ส่งผลกระทบต่อคุณภาพและความปลอดภัยของข้าว โดยทั่วไป การกำจัดแมลงในไซโลมักใช้สารรมยาเคมี เช่น ฟอสฟีน (PH₃) หรือ เมทิลโบรไมด์ (CH₃Br) ซึ่งอาจก่อให้เกิดสารตกค้าง ส่งผลต่อสุขภาพผู้บริโภค และสร้างผลกระทบต่อสิ่งแวดล้อม
คณะอุตสาหกรรมอาหาร
This study aimed to develop a formula and production process for snacks made from germinated brown rice flour and banana flour using the extrusion process. The results indicated that both germinated brown rice flour and banana flour could be effectively used as the main raw materials for snack production via extrusion. The proportion of flour in the formula and production conditions, such as moisture content of the raw materials, barrel temperature, and screw speed, significantly influenced the nutritional value, bioactive compound levels, and antioxidant activity of the final products.
คณะวิศวกรรมศาสตร์
The evaluation of mango yield and consumer behavior reflects an increasing awareness of product origins, with a growing demand for traceability to understand how the produce has been cultivated and managed. This study explores the relationship between mango characteristics and cultivation practices before harvest, using location identification to provide insights into these processes. To achieve this, a model was developed to detect and locate mangoes using 2D images via a Deep Learning approach. The study also investigates techniques to determine the real-world coordinates of mangoes from 2D images. The YOLOv8 model was employed for object detection, integrated with camera calibration and triangulation techniques to estimate the 3D positions of detected mangoes. Experiments involved 125 trials with randomized mango positions and camera placements at varying yaw and pitch angles. Parameters extracted from sequential images were compared to derive the actual 3D positions of the mangoes. The YOLOv8 model demonstrated high performance with prediction metrics of Precision (0.928), Recall (0.901), mAP50 (0.965), mAP50-95 (0.785), and F1-Score (0.914). These results indicate sufficient accuracy for predicting mango positions, with an average positional error of approximately 38 centimeters.
คณะครุศาสตร์อุตสาหกรรมและเทคโนโลยี
The Research aims to create Computer Assisted Instruction (CAI) on Kitchen Design for Residence for 20 undergraduate students at the Interior Environmental Design Division, School of Industrial Education and Technology, King Mongkut’s Institute of Technology Ladkrabang. This CAI is a self-learning program for Interior environmental design courses focused on kitchen design for residences. The program is designed to interact with students to create learner engagement and improve learning achievement by providing course content and end-of-chapter quizzes. The research hypothesis is CAI: Interior Environmental Design: Kitchen design for residence affects learners’ learning achievement and students' knowledge toward learning by this CAI. The Development testing (DT) with E1/E2 is the criterion for this instructional media to examine learning achievement. The research findings indicate that CAI is an effective instructional media, scoring 71.50/89.00, which meets the criteria of 80/80, demonstrating students’ learning achievement. Students achieved higher scores than before by using Computer-Assisted Instruction (CAI).