Bridging the Pacific: Why Global Manufacturing Is No Longer Optional
Knocking Down the Bone Pile: Minimizing X-ray Dosage During PCB Inspection
Global Sourcing Spotlight: Finding Your Greatest Sourcing Asset in Partnerships
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, particularly the potential for specific failures that need human intervention. The rapid advancements in technology, such as the Industrial Internet of Things (IIoT), big data analysis, cloud computing, 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 manufacturing process into a unified framework. This digital transformation of cyber-physical systems enables proactive responses to uncertain situations while ensuring heightened efficiency.
In the context of printed circuit board assembly (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 unexpected changes during production. Collaborating with various SMT industry partners, researchers at the State University of New York at Binghamton (Binghamton University) have developed a groundbreaking framework based on AI-based closed-loop feedback control and parameter optimization. This innovation promises to implement a smart manufacturing solution in the PCB assembly, with a focus on improving yield and throughput. This AI-based framework holds the potential to pave the way for data-driven process control in SMA.
Binghamton University Collaboration
Since 2016, Koh Young Technology and the Smart Electronics Manufacturing Laboratory (SEMLab) at Binghamton University’s Integrated Electronics Engineering Center (IEEC) have been collaborating on several key research initiatives to improve the assembly process in electronics manufacturing using AI integration. The aim of the SEMLab is to develop smart electronics manufacturing solutions using data science and AI principles to manufacture sophisticated printed circuit board assemblies with a focus on advanced robotics to revolutionize the electronics manufacturing process with improved yield and productivity. With automatic optimization, real-time intelligence techniques, and the implementation of advanced analytical approaches to the data collected from the equipment, the smart systems can deliver fewer defects, higher productivity, and increased reliability with cost-efficient results.
Continue reading the rest of this article in the October 2023 issue of SMT007 Magazine.
