This research aims to reduce the time required to resolve customer issues by focusing on improvements based on lean principles and the application of technology. The researcher conducts the case study at Nexter Digital and Solution Co., Ltd. to enhance workflows, establish new work standards, and integrate Bot technology into the processes to reduce resolution time and set new performance benchmarks for the company. The research proposes key ideas, such as identifying the root cause of problems, reducing redundant processes, implementing Lean methodologies, and applying technology to streamline operations. The research identifies two main issues to be resolved. The first involves addressing customer complaints, where the results show that the average resolution time reduces from 5 days to 3 days, representing a 38% decrease. The second issue involves solving problems for vendors, where the results show that the average response time reduces from 20 minutes to within 1 minute, a 98.5% decrease. The findings from both cases not only improve customer service but also establish a new standard for responding to and resolving internal issues more efficiently.
ในยุคที่เทคโนโลยีและการแข่งขันทางธุรกิจพัฒนาอย่างรวดเร็ว คุณภาพการบริการเป็นปัจจัยสำคัญที่ทำให้บริษัทเติบโตอย่างยั่งยืน โดยผู้วิจัยได้เล็งเห็นความสำคัญของการยกระดับคุณภาพการบริการเพื่อตอบสนองลูกค้าของทางบริษัท เน็กซเตอร์ ดิจิตอล แอนด์ โซลูชั่น จำกัด โดยประยุกต์ใช้แนวคิด Lean เพื่อลดความสูญเสียในกระบวนการทำงาน พร้อมกับนำเทคโนโลยีบอทเข้ามาช่วยเสริมในการแก้ไขปัญหา ซึ่งช่วยลดเวลาการจัดการปัญหาได้อย่างมีประสิทธิภาพและเพิ่มความพึงพอใจของลูกค้า โดยนำเทคโนโลยีสมัยใหม่ เช่น AI และระบบอัตโนมัติ ยังช่วยให้การทำงานมีความรวดเร็วและแม่นยำ ลดความผิดพลาดจากมนุษย์ อีกทั้งยังช่วยวิเคราะห์ข้อมูลเพื่อการตัดสินใจที่ดีขึ้น จากการศึกษา พบว่าบริษัทยังขาดกระบวนการทำงานที่ชัดเจน มีเวลาเฉลี่ยในการแก้ปัญหาที่ค่อนข้างนาน และพนักงานมีภาระงานที่มากเกินไป การปรับปรุงกระบวนการทำงานจึงเน้นการสร้างผังขั้นตอนที่ชัดเจน ลดเวลาการแก้ไขปัญหาให้เหมาะสม และปรับภาระงานของพนักงานให้เหมาะสม เพื่อลดระยะเวลาการรอคอยและเพิ่มความพึงพอใจให้กับลูกค้า
คณะวิศวกรรมศาสตร์
This project aims to introduce an Automated Vertical Metal Sheet Storage System. The project is aimed at teaching how to make an Automation Vertical Metal Sheet Storage System with the integration of microcontroller devices. The project is divided into two main sections, which are the structure and control systems of the Automation Vertical Metal Sheet Storage System that will be designed and drawn through a computer program and constructed using major aluminum structures upon completion of their actual sizes outlined in the programs. Also, a Microcontroller control system using GX Works 2 program from Mitsubishi PLC has been designed for this purpose where it controls up and down movements as well as sideways movement of the pallet. It also has a weighing capability along with touch screen display for displaying information about the steel plates and controlling the Automation Vertical Metal Sheet Storage System with safety light curtain that protect users safety. These tests have shown that the machine operates normally. There are few mistakes whose rates fall within those expected by humans.
คณะวิทยาศาสตร์
Otitis Media is an infection of the middle ear that can occur in individuals of all ages. Diagnosis typically involves analyzing images taken with an otoscope by specialized physicians, which relies heavily on medical experience to expedite the process. This research introduces computer vision technology to assist in the preliminary diagnosis, aiding expert decision-making. By utilizing deep learning techniques and convolutional neural networks, specifically the YOLOv8 and Inception v3 architectures, the study aims to classify the disease and its five characteristics used by physicians: color, transparency, fluid, retraction, and perforation. Additionally, image segmentation and classification methods were employed to analyze and predict the types of Otitis Media, which are categorized into four types: Otitis Media with Effusion, Acute Otitis Media with Effusion, Perforation, and Normal. Experimental results indicate that the classification model performs moderately well in directly classifying Otitis Media, with an accuracy of 65.7%, a recall of 65.7%, and a precision of 67.6%. Moreover, the model provides the best results for classifying the perforation characteristic, with an accuracy of 91.8%, a recall of 91.8%, and a precision of 92.1%. In contrast, the classification model that incorporates image segmentation techniques achieved the best overall performance, with an mAP50-95 of 79.63%, a recall of 100%, and a precision of 99.8%. However, this model has not yet been tested for classifying the different types of Otitis Media.
คณะอุตสาหกรรมอาหาร
This research aims to optimize the production process of gamma-aminobutyric acid (GABA) in fermented pineapple juice using probiotics and acetic acid bacteria (AAB), which are microorganisms with the potential to enhance GABA levels. This process has been developed to improve the nutritional value of fermented pineapple juice and to increase the economic value of Thai pineapples, which have long suffered from low market prices. This study focuses on determining the optimal conditions for GABA production by examining factors such as sugar content, pH levels, fermentation duration, and L-glutamate concentration, as well as the co-cultivation of probiotics and acetic acid bacteria. The experiments are conducted using controlled fermentation techniques, and the bioactive components of the fermented juice are analyzed with advanced instruments such as HPLC and GC-MS. The findings of this research are expected to contribute to the development of formulations and production processes for a high-GABA pineapple-based functional beverage. This product could offer health benefits such as stress reduction, cognitive function enhancement, and relaxation while also strengthening the potential of Thailand’s fermented food and beverage industry.