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58 SMT007 MAGAZINE I OCTOBER 2023 In electronics manufacturing, automated production has undeniably revolutionized the industry, enabling the creation of high-quality products at an unprecedented scale. However, it comes with its own set of challenges, particu- larly the potential for specific failures that need human intervention. e rapid advancements in technology, such as the Industrial Internet of ings (IIoT), big data analysis, cloud com- puting, and artificial intelligence (AI), have ushered in the era of Industry 4.0 and promise more intelligent manufacturing processes. Smart manufacturing, a pivotal part of this transformation, relies on real-time decision- making based on operational and inspectional data, seamlessly integrating the entire man- ufacturing process into a unified framework. Collaborating to Develop AI-powered Smart Assembly Processes is digital transformation of cyber-physical systems enables proactive responses to uncer- tain situations while ensuring heightened effi- ciency. In the context of printed circuit board assem- bly (PCBA) with surface mount technology (SMT) lines, IIoT technology accelerates data collection on equipment status and production quality. Data-driven solutions powered by AI and machine learning algorithms can diagnose abnormal defects, as well as adjust machine parameters on the fly in response to unex- pected changes during production. Collabo- rating with various SMT industry partners, researchers at the State University of New York at Binghamton (Binghamton University) have developed a groundbreaking framework based Feature Article by Brent A. Fischthal KOH YOUNG TECHNOLOGY Professor Daryl Santos (left), Systems Science and Industrial Engineering, in the lab with a research student at Binghamton University. (Source: binghamton.edu)