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Most automation conversations stop at the cell. This one keeps going, through a fab shop, a machine shop, a Department of Defense contract, and eventually a coal mine.
Michael McHale runs PSA Systems, an automation integrator in Pennsylvania that also fabricates, machines, and delivers turnkey projects in house. He bought the business in 2016 with four employees and about $900,000 in revenue. Today it's 100 people, 65 engineers, and over $30 million, split across five verticals that all feed each other. That structure is the whole point of this episode. When PSA chases something that looks like a distraction, like reclaiming and selling coal, it works because they already own every capability that business would otherwise have to outsource.
We also get into the part almost nobody wants to talk about, which is time. Mike runs on a five year plan and makes capital commitments for 2029 and 2030. He bought an $800,000 five axis mill that was closer to a million by the time it was wired and sitting on concrete, and he committed to it six or seven months before he had work to put in it. He's six figures into an IBM Watson rollout that he openly says won't show real value for another three to five years. His point is to stop treating technology like a series of purchases and start treating it like a position on where the business is going.
There's a practical thread for smaller shops too. Mike doesn't think a 15 or 20 person shop needs an enterprise AI rollout, and he says so. But if you're holding controlled information or working in regulated industries, he walks through why the guardrails matter, what goes wrong when drawings end up in a public model, and why the CMMC picture is so confusing right now.
Then it gets personal. Broke, rich, double broke, way richer than the first time. We asked how you stay level headed on that ride, and his answer came back to people instead of EBITDA. Can your employees buy a house? Can they send their kids to college? That's the scorecard.
What's Covered in this EpisodeWhen Uriel Eisen needed more capacity in his 325-square-foot shop, his first instinct was to buy a robot. But the machine wasn't the real bottleneck. Production kept getting derailed by missing material, forgotten orders, and inexpensive supplies that nobody noticed until they were gone.
Uriel's path from designing spacesuits to manufacturing CNC-machined hardware eventually led him deep into Kanban, lean manufacturing, and continuous improvement. What began with index cards and a Sharpie ultimately became Arda—a system built to connect what happens on the shop floor with the people responsible for keeping it supplied.
In this episode, we explore why some of the best automation projects look surprisingly low-tech, how small interruptions quietly consume far more capacity than most shops realize, and why a process that depends on discipline may actually be designed to fail.
Before you invest in another machine or shave a few seconds from a cycle, take a closer look at what's already stopping the work. The fastest return in your shop may be hiding inside an empty bin.
What's Covered in this EpisodeEric opens this episode describing a dream he had. A shop with no standalone machines. Three hundred and nine pallets moving 1,600 times a day. A central tool system holding 5,500 tools, five Fanuc robots shuttling up to 800 of them daily, and not a single crash. The punchline is that it wasn't a dream. He'd just walked through it.
That shop is Norbert Kempf CNC-Technik in St. Ingbert, Germany, a 100-person contract machine shop that runs simple to highly complex parts in batches of one to 500. We caught up with owner and managing director Stefan Kempf on his own floor, along with Risto Niemi of Fastems, who has spent 28 years helping shops rethink how they grow, and Yanick Müller of swissMODULAR, who thinks about work holding the way most people think about religion.
The number that stops you is this one: Setup time inside the machine is zero. Every tool arrives staged, every pallet is built offline, and the price a customer pays is the same whether they order ten pieces or a thousand. Utilization sits above 90 percent every single day, across 23 four-axis horizontals split between two buildings and joined by a bridge with a robot running tools across it. Any machine can run any part, so there is no bottleneck to schedule around.
What makes this more than a hardware story is how Stefan got there. He spent three years preparing the business before the first flexible manufacturing system arrived, standardizing machine brands, tool interfaces, and pallets into what he calls a monoculture of machines. Then he built a bonus system that pays the whole company on utilization and measures it every shift, so a bad night is just a bad night and tomorrow is a fresh chance.
If you've added machines and watched your utilization fall, this is the conversation to sit with. Stefan, Risto, and Yanick each leave you with one tactic you can act on, and none of them require a new building.
What's Covered in this EpisodeWhat if the most powerful sensor on your shop floor isn't a camera or a probe or a vibration puck—but a power cord? That's the premise Lauren Dunford, co-founder and CEO of Guidewheel, brought to the show, and she explained it using a hundred toasters.
Guidewheel clips a current transformer around the cord and reads the electrical heartbeat of a machine. No PLC integration, no open heart surgery, no waiting on a controller vendor. From those tiny fluctuations the platform gets run, idle, and down, then cycle counts, cycle times, early maintenance warnings, and in a lot of cases which SKU is running and where the anomalies are. It works on your CNC equipment, and it works on the compressors, chillers, conveyors, and palletizers that quietly stop your plant.
We also got into the question this show keeps circling. Is monitoring surveillance? Lauren's answer is that the data has to be used with the team, never on it. She would rather see posters, t-shirts, and a shift competing to win the hour than one manager holding a dashboard nobody else can see. If you have ever suspected your utilization number is fiction, this one is worth your commute.
What's Covered in this Episode
Every shop runs on a little tribal knowledge, the person who just knows where that tray of parts is headed and where it tends to get stuck. It works right up until they take a day off and the whole floor is hunting for a job that vanished somewhere between the mill and the heat treat rack. That gap is exactly what this episode is about: what happens when you stop guessing and start actually seeing where everything is.
Dave and Eric brought in Mitch Tucker of HID to break down RTLS, real-time location systems. In plain terms, RTLS tracks where your things are, your parts, your tooling, your material, even your people. The part that matters for us is where that data lives. It sits in the white space between your controlled processes, the handoffs and the staging and the waiting, and that's where most shops are quietly bleeding time.
Mitch's big point is that this isn't just a giant-warehouse toy. The same search-time problem that costs a 200 person facility around $400,000 a year shows up in a five person shop as a machine sitting idle while somebody looks for a tool that's thirty feet away. He makes the case for starting small and scaling deliberately, from a simple RFID setup to Bluetooth to ultra-wideband, matching the system to the size of your business instead of buying the most expensive thing in the room.
There's a real consulting streak to how Mitch approaches this, and it lines up with everything we preach. You don't drop RTLS into a chaotic shop. You know your processes first, you go to GEMBA and watch the work, you do your 5S, and then you add the visibility layer on top of a floor you already understand. From there the location data starts paying off in places you don't expect: the connected worker, safety and evacuation roll calls, job costing, and the honest conversation about where useful data ends and surveillance begins.
The throughline is one we come back to constantly. You can't run lights out, and you definitely can't jump to what Mitch calls Industry 5.0 and the AI wave behind it, without the data foundation underneath. Location data is a huge part of that foundation. If you've ever lost an afternoon to a missing tool, start here.
What's Covered in this EpisodeConexus Indiana is an industry-led nonprofit that pulls the state's manufacturers, logistics companies, colleges, and public sector into the same room to tackle the problems they all share: building a workforce pipeline, speeding up tech adoption, and getting shops to actually help each other. Every state is scrambling for exactly that, and Indiana seems to have cracked it. This week we sat down with Bryce Carpenter, EVP and Chief Operating and Strategy Officer at Conexus Indiana, to ask a blunt question. Is this a model the rest of us should be stealing?
At its core, Conexus runs on a simple idea, that industry knows what industry needs. Its Advanced Industries Council pulls 126 manufacturing, logistics, academic, and public sector partners into the same rooms all year long to name problems, share what's working, and go on offense together. In a state where advanced manufacturing and logistics is one in five jobs and a third of the economy, that kind of organization isn't a nice to have.
We got into the shift Bryce has watched over a decade, from automation is the enemy to automation being a foregone conclusion, and now the same cycle repeating with AI. He makes a case we come back to a lot on this show. The winning move isn't automating people out, it's automating the jobs nobody wants. His palletizing story is a clinic in change management.
We also dug into the Manufacturing Readiness Grants that have pushed matching dollars into more than 700 small and midsize shops, the FiberX company that 10x'd its business, and why Conexus works hard not to be a plaque factory. If you have ever wondered what it would take to build something like this where you are, Bryce lays out the non-negotiables.
What's Covered in this EpisodeMost shops picture automation the same way. A robot arm bolted to a machine, a green button, and a quiet promise that you can finally walk out the door at night. This episode takes that picture apart, and what replaces it is a lot more useful.
The trio is back together, and to kick off a new run of episodes we brought in Sarah Wierman of Fastems, someone Nick worked alongside for five years in workholding before both of them drifted into automation. Her big reframe is the one worth sitting with. Fastems isn't really a pallet company. It's a production orchestration company. The pallets moving in and out of the machine are the part you can see, but the real product is the software, MMS, that plans your jobs, runs them, and monitors the whole thing like the brain of the operation.
We get into why so many shops are feeling the pull toward automation right now, and it isn't a desire to replace people. It's labor shortages, a wave of retirements taking hard-won tribal knowledge out the door, and the need to stay flexible when demand swings the way it did during COVID. Sarah's point is that automation done right keeps your best people and frees them from babysitting a spindle.
From there it gets practical. Why you can get into automation too soon. Why repeatable fixturing is the foundation everything else sits on. Why tribal knowledge is the villain of the automation story, and why you should never automate chaos. Sarah walks through how the software can look 96 hours ahead to warn you a tool is about to run out, and how her cousin Caleb's rule, observe but don't intervene, separates a shop that trusts its process from one that keeps helicopter parenting the machine.
By the end she leaves listeners with three tactics you can start this week, none of them flashy, all of them the kind of one percent improvement that compounds. If you've ever told yourself you're too high mix to automate, start here.
What's Covered in this Episode
Every shop owner has stared at a floor full of expensive machines and thought the same thing: I need more capacity. More people. A second shift. Maybe another spindle. But the honest answer, most of the time, is that you already own the capacity you need. You just can't see how it's being used.
This week we sat down with Brian Anderson, Solutions Architect at ProShop ERP, for a conversation that hit uncomfortably close to home for all three of us. Brian has spent his whole career on both sides of this, first on the shop floor and now helping shops untangle the same knots. His core argument is simple. The problems you name out loud, scheduling, retention, quality, late deliveries, are almost never the real problem. They're symptoms. The real problem underneath is visibility.
From there the conversation moves the way a good shop assessment should. We get into the difference between a capacity problem and a utilization problem, and why calling it the wrong name sends you shopping for the wrong fix. Brian makes a level-headed case for automation, the three Ds of dull, dirty, and dangerous work, and why the shops he talks to have no interest in replacing their people with robots. They just want to stop asking good machinists to babysit a bar feeder.
Then we get practical. Splitting a job so the roughing runs unattended overnight. A five-minute shipping check that quietly eats hours off your week. Process Success Maps that treat the next person down the line as your customer. None of it is flashy. All of it is the kind of one percent improvement that actually compounds, which is a language we speak fluently around here.
By the end, the throughline is hard to miss. Running lights out was never really about the fanciest robot in the room. It's about knowing your shop well enough, and seeing it clearly enough, to trust it when you flip the switch and walk out the door. That's where this one lives.
What's Covered in this EpisodeEvery shop wants the shiny new machine. Walk a showroom floor like the one at ZOLLER's Technology Days in Ann Arbor and it's hard not to feel like a kid in a candy store. But the most useful question on this episode isn't which spindle to buy next. It's whether you're actually using the ones you already own.
We sat down at the ZOLLER Smart Manufacturing Summit with Walt Swenton, Senior Manager of Advanced Manufacturing at Eaton, for a conversation about problem-first thinking. Before you spend a dollar on technology, Walt argues, you have to name the problem you're solving. And for most shops, the real problem isn't cycle time. It's all the hours a machine sits idle while nobody's watching.
Walt walks us through his three levels of OEE, starting with the simplest question a shop can ask: is the machine running or not? From there we get into why quality beats cycle time as your first target, why availability is the number most owners overestimate, and how cheap, almost flip-a-switch monitoring can tell you the truth about your floor.
We also dig into the unglamorous foundation under every smart factory, which is standardized, digitized tool data. Walt makes the case that you can't run AI-driven CAM, predictive tooling, or anything close to lights-out until you've cleaned your own garage. Tool management, presetters, and a single source of truth for your cutting tools turn out to matter as much as the machines themselves.
And because none of this works without people, we close on the human side: change management, operator buy-in, and why the manufacturing engineer of the future lives in the data. Running lights-out was never about the fanciest robot in the room. It's about knowing your numbers well enough to trust the machines when you walk away. That's where this one starts.
What's Covered in this EpisodeRecorded live from the DN Solutions open house near Chicago, this special crossover episode between Lights Out and Buy the Numbers dives deep into what modern automation actually looks like inside growing machine shops. This isn't theory from a conference stage. It's a real-time conversation about throughput, utilization, machine strategy, and how shops can scale smarter without simply throwing more labor at the problem.
Nick and Mike explore one of the most important concepts in automation today: the "20-hour machine." Not the fantasy of perfect 24/7 uptime, but the practical reality of building reliable workflows that consistently create unattended runtime while still accounting for real-world interruptions, tooling, setups, and production variability. The discussion breaks down how manufacturers should think about automation investments through the lens of throughput, flexibility, and capacity instead of just labor reduction.
The episode also examines how shops evolve from traditional "lights in" manufacturing toward more autonomous workflows. From automated five-axis cells and pallet systems to machine monitoring and tool life optimization, Mike and Nick unpack how modern shops are using automation to free skilled employees from repetitive machine tending so they can focus on setup, process improvement, and higher-value work.
Along the way, the conversation touches on CapEx strategy, machine consolidation, spindle utilization, service support, and the hidden costs of downtime. More importantly, it reframes automation as a tool for creating flexibility, scalability, and even more time outside the shop. Because at the end of the day, the goal isn't just running machines longer. It's building a manufacturing business that runs smarter.
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