A Digital Twin-Driven Framework for Talent Training and Certification in Wafer Dicing Processes
Year: 2025
Type: article
Abstract: This article explores the application of digital twin technology to enhance the operation of wafer sawing machines in materials handling and semiconductor manufacturing. An empirical study was conducted on the packaging production line at Minghsin University of Science and Technology, aimed at addressing talent training challenges and the imbalance between supply and demand in the industry. The research focuses on designing and developing an integrated system that combines digital twin and mixed reality technologies. The development process involved multiple stages, including on-site visits, machine operation instruction, certification content creation, expert validation, small-scale testing, and iterative improvements. The study evaluates the effectiveness of the system by comparing pre- and post-experiment scores provided by industry experts, analyzing operation times of five participants, and gathering qualitative feedback. Results indicate that simulation training using digital twin and mixed reality significantly enhances participants' scores and operational proficiency. This research presents a digital twin-based training and certification model that effectively improves students' success rates in certification exams.
Source: Advanced engineering forum
DOI: 10.4028/p-yj3lfw
Authors: Lai Chung Lee, Shou Yen Zhao, Whei Jane Wei
Institution: Minghsin University of Science and Technology
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414999830