Coffee is a critical agricultural commodity to be used to produce a premium beverage to serve people worldwide. Coffee microbiome turned to be an essential tool to improve the bean quality through the natural fermentation. Therefore, understanding the microbial diversities could create the final product's better quality. This study investigated the natural microbial consortium during the wet process fermentation of coffee onsite in Thailand to characterize the microorganisms involved in correlation toward the biochemical characteristics and metabolic attributes. Roasting is another important step in developing the complex flavor/ aroma that make coffee to be enjoyable. During the roasting process, the beans undergo many complex and alternatively change in the physicochemical properties from the gained substances in the fermentation process. The changing in the formation of the substances responsible for the sensory qualities, physicochemical/ aroma attributes as well as the health benefits of the final product. Using the starter culture could also develop the distinguished characteristics of coffee (Research collaboration with Van Hart company)
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คณะครุศาสตร์อุตสาหกรรมและเทคโนโลยี
Industrial Education and Technology, King Mongkut's Institute of Technology Ladkrabang has a vision for sustainable excellence. The mission is to develop learners to be ready for the digital world, develop educational innovations using research as a base, strategic management with good governance, and academic services that benefit society. In this activity, the group of students joined with the Embassy of the Russian Federation in the Kingdom of Thailand, the working group of the Thai Silk and Culture Promotion Association, and the working group of the National Research Office (NRCT) to integrate knowledge to design a silk outfit that combines Thai and Russian cultures, create a network of cooperation in arts, culture, technology, innovation, and dissemination of knowledge and the beauty of Thai silk. The objective is to develop the potential of teachers and students in creative design, listen to the work guidelines from the working group of the Thai Silk and Culture Promotion Association, the working group of the National Research Office (NRCT) via an online meeting. The team of teachers and students from King Mongkut's Institute of Technology Ladkrabang under the name of the "Love Silk" group designed a Thai silk outfit that combines cultures with the identity of Thai silk and studying traditions and cultures of the Russian Federation's clothing. They studied related literature and research documents and integrated knowledge into the design process, inspired by the concept of the Rajapataen outfit. Since the reign of King Chulalongkorn (Rama V) in 1872, together with the clothing culture of the Russian Federation, emphasizing Thai silk, this concept has gone through the process of creating and selecting the design concept (Concept Generation and Selection). The concept received from the embassy was first submitted for feedback on July 25, 2024. There was a suggestion to add more uniqueness to Thai silk through a fashion show presentation by the wife and grandson of the Ambassador of the Russian Federation. Therefore, the designed outfits are 1 set of women's clothes and 1 set of boys' clothes. The women's set has an inner shirt adapted from the royal outfit using silk fabric, Kon Ka-ed pattern, with two separate pieces: 1 shirt and 1 skirt. The jacket is a modified long suit style, plain silk, dark pink and red. The boys' set has a long-sleeved shirt adapted from the contemporary royal style, tailored with cream silk, long slacks tailored with raw betel silk, and a collarless coat with blue silk and lotus pattern. Adapted from the Rajapattan suit with a long collar in an international style. On August 2, 2024, the designed suit and the prototype of the raw fabric suit were brought to the ambassador's wife and nephew to try on. On August 30, 2024, the ambassador was met for the 4th time to bring the silk suit that was cut into a real silk suit. The shirt was given to the ambassador's wife and nephew to try on. It was worn to join the fashion show in the 13th "Thai Silk to the World" Silk Festival at the Naval Auditorium, where lecturers and students from the Faculty of Industrial Education and Technology, King Mongkut's Institute of Technology Ladkrabang, joined the fashion show in the finale round, which proceeded smoothly. After the event, the working group of the Thai Silk and Culture Promotion Association brought the clothes designed and tailored by the "Rak Prae Mai" team to exhibit Thai Silk to the World Exhibition from September 1-8, 2024 at the Emsphere Shopping Mall. The team summarized the report and compiled a complete report. In the implementation of this project, the Faculty of Industrial Education and Technology, King Mongkut's Institute of Technology Ladkrabang has received support and facilitation throughout the project. The budget support from the National Research Council of Thailand (NRCT), the support of fabrics for sewing from the Thai Silk and Culture Promotion Association, and the information for designing valuable silk dresses from the Embassy of the Russian Federation in the Kingdom of Thailand are very important factors that made this operation a success. It is a very important experience for the team of teachers and students of Industrial Education and Technology, King Mongkut's Institute of Technology Ladkrabang. We sincerely hope to receive good cooperation in the future.
คณะวิศวกรรมศาสตร์
This cooperative education project aims to enhance the efficiency of Hydrogen Manufacturing Unit 2 (HMU-2) and Pressure Swing Adsorption 3 (PSA-3) by using AVEVA Pro/II process modeling and a Machine Learning model for process simulation. The study found that the AVEVA Pro/II model predicted outcomes with deviations ranging from 0–35%, including a hydrogen flow rate deviation from the PSA unit of 12%, exceeding the company’s acceptable limit of 10%. To address this, a Machine Learning model based on the Random Forest algorithm was developed with hyperparameter tuning. The Machine Learning model demonstrated high accuracy, achieving Mean Squared Errors (MSE) of 8.48 and 0.18 for process and laboratory data, respectively, and R-squared values of 0.98 and 0.88 for the same datasets. It outperformed the AVEVA Pro/II model in predicting all variables and reduced the hydrogen flow rate deviation to 4.75% and 1.35% for production rates of 180 and 220 tons per day, respectively. Optimization using the model provided recommendations for process adjustments, increasing hydrogen production by 7.8 tons per day and generating an additional annual profit of 850,966.23 Baht.
คณะวิทยาศาสตร์
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