This cooperative education project aims to enhance speed and facilitate the verification process for stock issuance, transfers, distributions, and receipts in the warehouse. The primary focus is to address issues related to wasted time and delays in operational processes. Through analysis, it was found that SAP, the current system, involves complex processes requiring specialized expertise. Although the company has developed the iWarehouse system to improve efficiency, delays and procedural complexity persist. To resolve these challenges, Power BI was utilized to visualize data related to stock issuance, transfers, distributions, and receipts, allowing warehouse staff to work more efficiently by minimizing waste and accelerating processes. Additionally, Power Automate was integrated to automate the processing of received stock numbers from emails, reducing errors and delays caused by manual data entry. The results of this improvement indicate a significant increase in employee efficiency and a noticeable reduction in wasted time. Upon project completion, the findings and development approach will be provided to the company for further enhancement.
เนื่องจากในกระบวนการทำงานในคลังสินค้า ในหน่วยงานส่วนจัดหาและบริหารพัสดุ กรณีศึกษาบริษัท ปตท. จำกัด (มหาชน) ศูนย์ปฏิบัติการชลบุรี มีเวลาสูญเปล่าเกิดขึ้นเป็นจำนวนมาก และมีกระบวนการทำงานที่ซับซ้อน และยังขาดเครื่องมือหรือเทคโนโลยีสมัยใหม่
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.
คณะวิทยาศาสตร์
-
คณะเทคโนโลยีสารสนเทศ
This research presents the development of an AI-powered system designed to automate the identification and quantification of dental surgical instruments. By leveraging deep learning-based object detection, the system ensures the completeness of instrument sets post-procedure. The system's ability to process multiple images simultaneously streamlines the inventory process, reducing manual effort and potential errors. The extracted data on instrument quantity and type can be seamlessly integrated into a database for various downstream applications.