A RESEARCHER from Universiti Tunku Abdul Rahman (UTAR) has been given a boost in his effort to ensure the efficient use of tin, particularly in tin soldering, which is an integral process of printed circuit board manufacturing.
Dr Tham Mau Luen (pic) recently secured a research grant worth RM10,000 from the Tin Industry (Research and Development) Board, with the aim of developing a system for tin soldering defect detection.
According to the Lee Kong Chian Faculty of Engineering and Science (LKC FES) academic, automating visual inspection systems using machine learning has become a popular trend with the emergence of the Fourth Industrial Revolution (IR4.0) and the rapid development of artificial intelligence (AI).
He explained in a press release that while tin soldering can adopt AI techniques to detect defects, deploying these AI models on resource-limited embedded systems remains an issue.
“Existing works have focused on evaluating the feasibility of a neural network model in an ideal environment with a large number of computing and storage resources.
“How to put AI models into sustainable production remains a key challenge,” he said.
He hopes that his research on developing “a deep learning-based machine vision for tin soldering defect detection in a low-powered embedded platform” will bridge the gap between AI research and practice.He emphasised that early detection of tin soldering defects and the removal of the elements that may produce them are essential to improve product quality and to reduce the economic impact caused by discarding defective products.
He added that a low-powered embedded system design improves reliability and sustainability due to less power waste or heat, besides reducing the operating expenditure of the local tin-based manufacturing industry.
“Overall, the project goal is to meet the United Nations’ Sustainable Development Goal 12, which is responsible consumption and production, and in this instance, to achieve the sustainable management and efficient use of natural resources,” he said.
He added that the research can also help UTAR to identify more industry challenges, especially in the local tin industry, and to provide innovative solutions that benefit society as a whole.
For this research, Dr Tham will be joined by another LKC FES academic Chean Swee Ling.