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60 SMT007 MAGAZINE I JULY 2025 S M A RT AU TO M AT I O N Why Mid-sized Manufacturers Need a Different Approach Mid-sized SMT operations face unique pres- sures. Many focus on high-mix, low-to-mid-volume builds. They must adjust quickly, manage frequent changeovers, and maintain traceability, often for demanding industries such as automotive, medical, and aerospace. Many do not have large full-time IT departments or unlimited CapEx budgets. Invest- ments need to pay off quickly, be easy to imple- ment, and scale gradually. That's where a practical Industry 4.0 strategy can shine. Practical Steps Toward Industry 4.0 Leverage existing information on the shop floor. Extract and contextualize the data already being recorded. Most modern SMT equipment collects and stores vast amounts of important data. The problem is the ability to paint a full picture when that data is siloed within a given machine. Unifying data through connectivity solutions allows the manufacturer to see the entire line as a living entity, rather than separate systems operating independently toward a single goal. Whether it's correlating a misprint with a defect found at AOI or understanding placement yields across multiple lines, understanding and contextu- alizing this data is a critical step in Industry 4.0. By taking this step, the manufacturer has the building blocks to one day implement AI-driven predictive analysis tools. Basic connectivity gives the user visibility they didn't previously have, and it's the first building block to everything else. Use AOI and SPI data to improve yield in real time. Inspection systems are common in most mid-sized operations. Closed- loop feedback with upstream and downstream machines is an easy win. Many modern inspec- tion systems support some level of closed-loop feedback, where print inspection results can auto- matically adjust printer settings, or AOI inspection results can drive placement offsets before reflow. These feedback loops improve first-pass yield with no operator intervention and help stabilize the line without added complexity. The hardware likely exists at the manufacturer today; often, it sim- ply takes a small investment for an SW license and configuration to begin. Automate human-intensive, low-value tasks. Not all automation requires convoluted SW integration or AI. In many facilities, the drag on efficiency is repetitive manual work, such as restocking components, placing labels, and hand-scanning barcodes. Targeting these human- intensive, low-skill tasks is one of the best ways to deploy smart automation. Tools such as intelligent storage towers, feeder verification systems, and automated laser marking help reduce errors and speed up line changes. They don't require a full dig- ital ecosystem to function, just planning and mod- ular integration. The result is higher throughput, fewer errors, and happier employees. Implement scalable MES or traceability systems. For many manufacturers, leaping into a full-blown MES is like jumping into a jet's cockpit without flying lessons. Many mid- sized operations can start with simple and scalable traceability systems that track board IDs and com- ponent placement data through the line. Choose platforms that are modular and scalable, expand- ing over time to include scheduling, WIP track- ing, and rework. The visibility gained, even from basic tracking, improves customer reporting, root cause analysis, and compliance documentation. A phased MES approach makes traceability another tool, not a burden. 1 2 3 4