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62 SMT007 MAGAZINE I OCTOBER 2025 A RT I C L E by S h o b h i t Ag ra wa l , Keys i g ht Te c h n o l o g i e s Unlocking the Promise of AI in Electronics Manufacturing tems to capture structured as well as unstructured data. This data can be fed to AI engines to help engineers in troubleshooting new issues in highly complex production lines, to find the machine per- formance data, most relevant procedures, and his- tory of relevant issues. Companies that are adopt- ing AI can quickly identify the root cause of different issues, solve them, and integrate those learnings to optimize processes. AI transformation has just begun and still is in early stages of development. It is expected to rap- idly grow and disrupt traditional problem-solving methods currently followed in manufacturing. AI use cases have demonstrated tangible value and ability to be implemented at scale. While the theoretical advantages of adopting AI are clear, the practical implementation in a complex, dynamic, and fast-paced production line has its own challenges. Successful implementation of an AI/ML initiative into such an environment not only requires deep understanding of specific manufacturing tech- nologies and processes, but also comprehensive strategies around data security, data infrastructure, user data literacy, and AI adoption. Success of an AI/ML initiative is not just about identifying impact- ful use cases, but also about end-to-end implemen- tation where the value can be quantified. (Editor's note: This paper was originally published in the IPC APEX EXPO 2025 Technical Conference proceedings.) T he electronics manufacturing industry is rap- idly evolving as more complicated products are introduced in the production lines, which require technological advancements even in the production processes. The requirements for production that is efficient, product quality that is greater, and prod- uct life cycles that are shorter are more crucial than ever before. In the electronic device life cycle, from design to maintenance, test phases have a signifi- cant impact on the economy of the company. Test processes are closely linked to the production vol- ume and impacted by the complexity of the prod- uct. For businesses to maintain their competitive edge, they need to adopt innovative solutions and redefine processes. AI is one such solution that is being widely adopted. The historical data collected during the lifecycle and test phases is analyzed to fine-tune equipment, identify the most efficient pro- duction processes, and reduce wastage. Most of manufacturing faces challenges which are common across organizations and can be eas- ily solved using AI. As companies are getting more data-driven, they are setting up processes and sys-