Page 4


www.us-tech.com


Tech-Op-ed July 2026 SOUNDING OFF


By Michael Skinner Editor


Lights Off, Reality On T


he “lights out” factory has long been one of manufacturing’s most compelling images: a plant running through the night, with no operators on the floor and no need to keep the lights on.


In practice, the idea is both real and overstated. Fully autonomous factories exist, but they remain rare and carefully designed. For most manufacturers, including electronics producers, the realistic future is not an empty building, but a highly automated factory where people intervene less often and mostly by exception. Examples show that lights out manufacturing is possible when


the product, process and volume are right. FANUC in Japan is fre- quently cited for robot production lines capable of running for extend- ed periods with minimal human supervision. Philips has also been associated with highly automated shaver production in Drachten, the Netherlands, where robots handle much of the repetitive assembly work. In electronics, Siemens’ Electronics Works Amberg in Germany is one of the clearest models of a highly digitalized plant, producing Simatic automation products with extensive data integration, auto- mated testing and very high quality levels. More recently, Xiaomi’s smart factory in Changping, Beijing, has


pushed the conversation directly into consumer electronics. The com- pany has described the site as a next-generation smartphone factory with an annual capacity of 10 million flagship phones and automa- tion of key processes. The important point is not simply the presence of robots. It is the digital backbone connecting production equipment, process data, quality systems and factory software. Electronics manufacturing is well suited to partial lights out op-


eration. SMT lines already rely on automated printing or dispensing, pick-and-place systems, reflow ovens, automated optical inspection, X-ray inspection, traceability software and material handling. In semiconductor manufacturing, long stretches of production already take place inside controlled environments where human access is limited and automation is essential. The challenge is that electronics manufacturing is also unforgiv-


ing. A missing component, paste defect, feeder issue, moisture-sensi- tive device problem, wrong reel, soldering variation or test escape can create expensive failures. High-mix electronics manufacturing adds another layer of difficulty because frequent changeovers, engineering updates and component substitutions create more exceptions. Lights out operation is easiest when products are standardized, volumes are high and process windows are stable. It becomes harder in high-mix, low-volume EMS environments, where flexibility still depends on skilled technicians, process engineers and operators. The barrier is not only robotics. A true lights out factory needs


closed-loop process control, reliable automated material movement, predictive maintenance, automated inspection, strong factory software, cybersecurity, and machine data clean enough to act on. It also needs equipment that can recover from routine problems without human help. A robot that can place a component is useful; a system that can detect a feeder fault, verify the root cause, call the right material, ad- just the schedule and restart safely is much closer to autonomy. This is where AI may matter most. AI can help inspection sys-


tems reduce false calls, identify process drift earlier, predict equip- ment failure and optimize scheduling. Digital twins can simulate changes before they reach the line. Autonomous mobile robots can move reels, trays and finished goods. MES and ERP integration can connect demand, inventory and production status in real time. The reality is clear: lights out manufacturing is not science fic-


tion, but it is not a simple switch to flip. In electronics manufactur- ing, its future depends less on removing people from the factory than on building systems reliable enough that people no longer have to stand beside every machine to keep production moving. r


PUBLISHER’S NOTE


By Jacob Fattal Publisher


Testing, Testing T


esting has always been one of the most important safeguards in electronics manufacturing. As assemblies become smaller, denser and more complex, the margin for error continues to


shrink. A single weak solder joint, misplaced component or intermit- tent electrical fault can lead to field failures, warranty costs and dam- age to a manufacturer’s reputation. For industries such as automo- tive, aerospace, medical electronics and defense, the stakes are even higher, making test and inspection essential parts of the production process rather than final checkpoints. Across the factory floor, testing takes many forms. Solder paste


inspection helps verify print quality before placement. Automated op- tical inspection checks component presence, polarity, alignment and solder conditions. X-ray inspection reveals hidden joints under BGAs and other complex packages. In-circuit and functional testing confirm that boards not only look correct but perform as intended. Together, these methods create a layered quality strategy that catches defects early, reduces rework and supports process improvement. Artificial intelligence is now beginning to change how manufac-


turers approach this work. In inspection systems, AI can help distin- guish true defects from acceptable process variation, reducing false calls and easing the burden on operators. Machine learning tools can analyze large volumes of production and test data to identify recur- ring problems, predict equipment issues and recommend process ad- justments before defects multiply. AI is also improving programming efficiency by helping systems learn from previous inspections and adapt more quickly to new products. This is especially valuable in high-mix, low-volume manufactur-


ing, where frequent changeovers make traditional test programming time-consuming. AI-assisted inspection and test platforms can short- en setup, improve consistency and help less-experienced operators make better decisions. However, AI is not replacing the need for strong engineering judgment. Manufacturers still need reliable data, clear standards and human oversight to ensure that automated deci- sions are accurate and traceable. The future of electronics testing will be smarter, faster and more


connected. As AI becomes more deeply integrated into inspection, test and factory analytics, testing will continue to evolve from a quality gate into a real-time source of manu- facturing intelligence. r


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64