Time/时间：4月18日（周五）10:00-11:30
Venue/地点：Room 501, Jiageng Building 2/嘉庚二号楼501教室
Topic/题目：Material Control to Cost Control: Machine Learning in Tobacco Manufacturing
Speaker/报告人： Lai Lai Aung, （2023 级财务学博士生）
Facilitator/主持人：陈亚盛 教授
Abstract/摘要：
The industrial sector struggles to enhance efficiency and reduce material costs, particularly in China’s tobacco industry, which generated 1.5217 trillion yuan in corporate taxes and profits in 2023. Traditional material analysis methods are imprecise, lack real-time data integration, and hinder decision-making. To address this, a machine learning (ML)-based solution was developed to shift focus from material control to strategic cost management. The project applied Activity-Based Management (ABM) principles via ML algorithms, leveraging a dataset of 1,044 records from a tobacco firm (2021–2023). Among four ML models tested, Random Forest achieved optimal performance (MSE: 0.11356, R²: 0.84601). This system enhances forecasting accuracy, enables real-time monitoring, and reduces waste, improving cost efficiency. This study bridges theory and practice by demonstrating ML’s potential to modernize conventional systems and deliver scalable solutions for industries. Researchers are exploring adaptive improvements to broaden commercial applicability.
About the Speaker/报告人简介:
Lai Lai Aung, 2023 PhD Student, Institute for Financial and Accounting Studies, her primary research focuses on management accounting, employing innovative methodologies including neuroscience approaches, design science frameworks, artificial intelligence, and machine learning applications. She specializes in producing management accounting research papers that integrate these advanced analytical techniques to address contemporary challenges in the field.