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
คณะวิทยาศาสตร์
With the development of space technology, wide-field sky surveys using telescopes have expanded the range of new data available for time-domain astronomical research. Traditional data analysis methods can no longer respond quickly and accurately enough to the growing volume of data. Thus, classifying time-series data, such as light curves, has become a significant challenge in the era of big data. In modern times, analyzing light curves has become essential for using machine learning techniques to handle and filter through massive amounts of data. Machine learning algorithms can be divided into two categories: shallow learning and deep learning. Numerous researchers have proposed and developed a variety of algorithms for light curve classification. In this study, we experimented with Support Vector Machine (SVM) and XGBoost, which are shallow machine learning algorithms, as well as 1D-CNN and Long Short-Term Memory (LSTM), which are deep learning algorithms, which are branches of deep machine learning, to classify variable stars. The training and testing data used in this study were from the Optical Gravitational Lensing Experiment-III (OGLE-III), consisting of variable star data from the Large Magellanic Cloud (LMC), categorized into five main classes: Classical Cepheids, δ Scutis, eclipsing binaries, RR Lyrae stars, and Long-period variables. The results demonstrate the performance analysis of each machine learning algorithm type applied to light curve data, while also highlighting the accuracy and statistical metrics of the algorithms used in the experiments.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
Study on Parasites in Blackchin Tilapia and Value-Added Processing Parasites play a crucial role in affecting fish health and the balance of marine ecosystems. The study of parasites in fish is essential for assessing fish population status and their impact on the ecosystem. This research focuses on a preliminary survey of parasites in Blackchin Tilapia (Sarotherodon melanotheron) found in the waters of Chumphon Province to determine whether this species carries parasitic infections. The findings will provide valuable insights for managing marine resources and developing strategies for processing Blackchin Tilapia into food products to help control its population in the ecosystem. One of the value-added processing approaches for Blackchin Tilapia is the "Nai Hoi Hua Fu" product. This product involves deep-frying the fish to achieve a crispy and fluffy texture before mixing it with mango salad to enhance its flavor and make it more appealing. This processing method not only adds value to the fish but also serves as a practical solution for managing the Blackchin Tilapia population, which may impact the ecosystem. The study results indicate that no parasitic infections were found in either the internal or external organs of the sampled fish, suggesting that the marine environment in the study area is favorable for fish health. However, continuous research is recommended to monitor long-term ecological changes and evaluate the impact of Blackchin Tilapia on ecosystem balance to ensure sustainable resource management.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
Design a graphic concept for a vending machine and its surrounding area (5x6 meters) featuring INGU skincare products