Issue link: https://iconnect007.uberflip.com/i/1527276
56 SMT007 MAGAZINE I OCTOBER 2024 bility, necessitating robust detection and mit- igation strategies. As the threat of counterfeit electronics continues to evolve, it is crucial for organizations to stay informed about the lat- est techniques and implement comprehensive strategies to protect their supply chains and ensure the integrity of their products. By adopting a multi-layered approach that combines advanced detection methods, strin- gent supplier verification, and proper disposal procedures, organizations can significantly enhance their ability to combat even the most sophisticated counterfeit components. Con- tinuous education, vigilance, and collabora- tion across industries and governments will be key to staying ahead of this persistent and evolving threat. SMT007 Anthony (Tony) Bryant is a trained expert in component counterfeiting techniques who has been collaborating with IPC on a new intermediate-level course on counterfeits. by Julie Cliche-Dubois, Cogiscan Chapter 6: Driving Meaningful Action Normalizing and labeling shop-floor data is man- datory to feed an analytics tool with sensical infor- mation. Equally as important is the underlying infra- structure of the analytics tool; it should have a domain specific engine that interprets and manages the complexities of PCBA manufacturing. Without this data contextualization, the analytics tool can easily display inaccurate KPIs. Just consider how many configurations exist in PCBA manufacturing— from dual-lane or single-lane assembly or the configura- tion of panels in one-up or multi array, all these things need to be understood by the analytics system to per- form any relevant calcula- tions. Without this contextual- ization you won't have preci- sion. Sure, you'll still get KPIs, but they likely won't be accu- rate. For example, say there's a high defect rate at AOI that requires rework. When those PCBAs go through the AOI a second time to verify the work performed, if the analyt- ics tool doesn't "know" that those units are re-runs, it will falsely inflate the total job quantity—and all the KPIs that use job quantity (of which there are many) will be inaccurate. The analytics tool must have a way to "read" the identity of those PCBAs and prop- erly classify them as re-runs to ensure accurate KPI calculations. Regardless of the analytics dashboard, such as commercial solutions like Qlik, Tableau, or Microsoft BI, all these systems do an incredible job displaying information clearly. What is typically missing under- neath these visualization platforms is the domain specific engine to calculate KPIs correctly with contextu- alized data. Visualizing data is quite simple, it's getting the data normalized and cal- culated properly beforehand that's the tricky part. Powered with a clearer understanding of factory performance, efficiency, and quality, it's crystal clear that manufacturers using fac- tory analytics are armed with appropriate data insights to drive action to improve their manufacturing operation holistically. Continue reading... BOOK EXCERPT: The Printed Circuit Assembler's Guide to... Factory Analytics, Chapter 6