As electronics become smaller, faster and more complex, the manufacturing systems used to build them are undergoing a transformation of their own. Panasonic Connect is one of the companies helping to drive that change.
A business-to-business technology company within the Panasonic Group, Panasonic Connect provides smart manufacturing solutions that combine surface-mount technology (SMT) equipment, robotics, manufacturing execution software, AI-powered analytics and connected factory platforms.
Through its “Gemba Process Innovation” strategy, the company aims to connect people, machines and production data to improve productivity, quality and operational resilience on the factory floor.
Its technologies are used by electronics manufacturers producing everything from automotive electronics and industrial equipment to medical devices and consumer products.
As vehicles, smartphones and industrial systems incorporate ever-greater numbers of sensors, processors and electronic components, manufacturers face mounting pressure to place smaller components with greater accuracy while supporting increasingly flexible, high-mix production.
To discuss these challenges, Robotics & Automation News spoke with Scott Zerkle, associate director of technical operations at Panasonic Connect North America.
Zerkle works closely with manufacturers adopting advanced SMT technologies and has extensive experience in production operations, process optimization and manufacturing automation.
During the interview, Zerkle explains why AI’s greatest value today lies not in replacing factory workers but in supporting them through predictive maintenance, defect detection and better operational decision-making.
He also argues that the next major step for smart manufacturing will not simply be adding more AI tools, but connecting data across machines, materials and production processes to create factories that continuously learn and improve from their own production history.
The conversation also explores how manufacturers are adapting to increasingly complex electronics, why automation is becoming essential for high-mix production, and how the convergence of AI, advanced sensing and robotics could reshape electronics manufacturing over the coming decade.
Interview with Scott Zerkle
Robotics & Automation News: Modern vehicles, industrial systems, and consumer devices now contain far more sensors, processors, and electronic components than they did a decade ago. How is this increasing complexity changing the way manufacturers design and operate production lines?
Scott Zerkle: Across the board, products from consumer devices to industrial equipment carry far more electronics than ever before. Modern vehicles alone now rely on 60 to 100 or more sensors, with some models exceeding 200.
That translates to more components, tighter pitch spacing, and tighter placement tolerances than production lines were originally designed to handle.
As a result, manufacturers are facing challenges on multiple fronts. Placement accuracy and repeatability matter more, as deviations that were once acceptable can now result in defects.
An incorrect feeder load or an unverified changeover can cause real disruption across more component variants. That’s why we’re seeing more emphasis on verifying materials and settings before a job even starts.
R&AN: As electronic components continue to shrink in size while increasing in capability, what are the biggest challenges facing manufacturers in SMT assembly and PCB production today?
SZ: Component miniaturization is outpacing what older lines were built for. We’re placing parts with spacing measured in tens of microns, where even the slightest deviation can throw off the solder joint.
And as components become smaller and more densely packed, printing and placement have to get more precise too, since paste deposition and placement accuracy must scale alongside them.
That’s pushing real-time correction, adjusting placement and paste volume as conditions shift mid-run instead of running a fixed program start to finish.
Printing, placement, and inspection need to work together so that a defect is caught at the step where it occurs, not after.
R&AN: Panasonic Connect talks about “Gemba Process Innovation”. How do you see automation and digital technologies changing day-to-day manufacturing operations on the factory floor over the next five years?
SZ: Gemba is the actual place where work happens, the factory floor itself. Rather than staying in someone’s head or buried on paper, the goal is to connect what’s happening there with a digital system that can see it in real time.
Over the next five years, I expect that to play out on SMT lines in two ways.
First, automation handles more of the verification before a changeover, checking feeders and settings against the next job rather than depending on an operator’s memory.
Second, more process data is captured on how skilled operators actually work, so that knowledge can train new hires and tune the machines themselves.
Artificial intelligence is being applied across almost every industry. Where do you see AI delivering the greatest practical value in electronics manufacturing today, and where do you think expectations may be running ahead of reality?
The greatest practical value today is predictive maintenance and defect detection to catch issues using machine data before they cause downtime or scrap.
Where expectations run ahead of reality is the idea that a factory can be run by AI alone, which is neither realistic nor the right objective. AI is only as good as the data it receives, and most plants still run legacy systems that don’t talk to each other, creating fragmented data.
The real opportunity is to use AI to support people on the floor, taking on repetitive analysis so operators can focus on the complex decisions that require human expertise.
R&AN: Manufacturers are under pressure to improve quality, increase throughput, and remain resilient in the face of supply-chain disruptions. How can automation help companies balance these competing priorities?
SZ: Automation’s real contribution is consistency, for things that tend to drift independently, like people, machines, and materials.
We think about it as the 5Ms: huMan, machine, material, method, and measurement, because issues in quality, throughput, and resilience typically trace back to a gap in one of those. That could be a worker underperforming, a machine drifting out of tolerance, or material shortage not caught in time.
Automated systems that monitor these five together can catch deviations before they evolve into defects or missed deadlines and correct them in real time. A line is resilient when one disrupted part doesn’t halt the rest or ripple across it.
R&AN: High-mix, low-volume production is becoming increasingly common in many sectors. How are manufacturing systems evolving to handle greater product variation without sacrificing efficiency?
SZ: High-mix production used to mean accepting slower changeovers in exchange for flexibility, though that’s changing. Today, manufacturers are reducing that tradeoff through greater automation and process intelligence.
Manufacturers are investing in faster, more reliable setups, verifying materials and feeder positions before a run starts. On many lines, switching between configurations now happens simply by selecting a different program rather than through manual reconfiguration.
Feeder capacity and early-warning systems that flag a component running low matter just as much as the software driving the changeover.
Reliability is just as important as speed. Getting the changeover right the first time is especially critical given workforce shortages and the growing challenge of relying on experienced technicians who know the process by memory alone.
R&AN: Panasonic Connect has visibility across a wide range of industries. Which sectors do you believe are currently leading the adoption of smart manufacturing technologies, and what lessons can other industries learn from them?
SZ: There are many industries, like automotive, consumer device, and medical device manufacturing, turning to smart manufacturing technologies. Automotive, in particular, has led the shift toward building to demand instead of holding inventory.
That same approach is extending across electronics manufacturing, where customers expect shorter lead times, so production has to respond quickly rather than draw from stock.
Medical and aerospace add another layer, since defects can carry costly regulatory and safety consequences, leaving no room for error.
The lesson for other industries is clear: move beyond reactive inspection and toward real-time predictive monitoring, so that deviations are captured as data points before they become defects.
R&AN: Looking ahead, what technologies or trends do you believe will have the biggest impact on electronics manufacturing over the next decade – whether that is AI, robotics, digital twins, advanced sensing, or something else entirely?
SZ: The biggest shift over the next decade will be convergence: AI, sensing, and automation feeding off the same data instead of running independently.
Many plants today have these capabilities, but tend to work in isolation, each system flagging its own deviations without the context needed to understand why they occurred.
What will change is how these systems connect. Instead of simply flagging a deviation, manufacturers will be able to trace it back to the root cause, whether it’s a worn part or a material lot, and use those insights to continuously optimize.
The factories that benefit most will be those that evolve and get smarter from their own production history, rather than those that simply invest in the newest technology.
The competitive advantage won’t come from adopting more tools. It will come from connecting them into a smarter manufacturing ecosystem.
