Manufacturing Matters

Hosted by Tech B2B

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Episodes

155

Latest episode

Oct 2026

Language

EN-US

About the show

The Manufacturing Matters podcast aims to get to the heart of automation technology and how it plays into the growing manufacturing industry. Join us for insights and interviews discussing trends, innovations, and advanced automation technologies, such as robotics, machine vision, AI, and much more. Follow our social channels here: http://linktr.ee/m_mp

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60 recent

October 15, 2026Episode 15534 min

Episode 155 - Dr. Jae Son, Dr. Charles MacLeod, and Stu Shepherd

“Now tactile is an array of information that gives you insight into the contact mechanics between two objects.” Pressure is a scalar value. Force is a vector. Tactile sensing, says Pressure Profile Systems founder Dr. Jae Son, is something else entirely — a map of contact across an entire surface, the same sense humans rely on to pick up a coffee cup without crushing it, and one that most robots still don’t have. In this episode of “Manufacturing Matters,” TECH B2B Marketing’s Winn Hardin sits down with Dr. Son, PPS’s Dr. Charles MacLeod, and longtime robotics industry leader Stu Shepherd (Shepherd Solutions) to unpack why tactile sensing is finally getting its due — driven by humanoids and robots working in unstructured environments where fixed, pre-programmed grasps no longer cut it. The conversation covers PPS’s 65-point Tactile Glove (used both to collect human grasp data for robot training and, oddly, fitted directly onto robotic hands), and two very different medical spinouts: a radiation-free breast exam device now shown to outperform mammograms, and a new sensor for knee-replacement surgery that finally gives surgeons data instead of feel. Shepherd brings the industry-veteran perspective: Grip force has long been over-engineered because robots couldn’t tell how they were gripping something, and tactile data opens the door to lighter, smarter grippers. Dr. Son also pushes back on humanoid-robot hype, arguing the bigger near-term opportunity is smarter automation broadly, and walks through a very literal use case: giving assembly robots the ability to feel whether a connector clicked into place — something factory-floor noise often makes impossible to hear. Support the show

October 9, 2026Episode 15433 min

Episode 154 - Lindsey Sullivan, Founder, Technical Marketing Manager, CCS America

Machine vision teams will happily argue for hours about cameras, sensors, and AI models. Then they choose the light last — and wonder why the system can’t see the defect it was built to find. Lindsey Sullivan has a demo that ends the argument. At CCS America’s hands-on lighting roundtables, she hands engineers a battery with a small dent in it. Put a coaxial light at one working distance and the dent is unmistakable — any camera, any software, even the cheapest black-and-white setup catches it instantly. Move that same light a few inches closer and the dent vanishes. No camera can find it. No filter brings it back. No amount of AI rescues it. In this episode of Manufacturing Matters, TECH B2B Marketing’s Jimmy Carroll and Aaron Hand talk with Sullivan, technical marketing manager at CCS America, about why lighting deserves a bigger role in machine vision. She explains when standard lighting gives way to custom designs, how manufacturing environments can change the equation, and why finding the right wavelength often involves some experimentation. UV can make coatings and inks fluoresce. IR can reveal defects hidden beneath packaging graphics. And SWIR? Sometimes you just have to try it. Sullivan also explains where artificial intelligence fits into the picture: It can sharpen the marginal calls that once tripped up machines and human inspectors alike, but it can’t recover a defect that the wrong lighting has already hidden. Her advice to machine vision integrators is simple: Stop choosing the light last. Support the show

October 2, 2026Episode 15345 min

Episode 153 – Kyle Haworth, Founder, GuildHall

Most discussions about industrial automation and analytics concern operations with hundreds of employees. This episode of Manufacturing Matters explores a less traveled quarter: Small shops with maybe a dozen people on the floor, a founder who has run the place for decades, and a spring sales bump nobody has ever been able to explain. Our guest, Kyle Haworth, built his career building large-scale enterprise data systems before co-founding GuildHall to bring that same discipline to manufacturers under 30 employees and under $10 million in revenue. He notes that small shops often buy advanced technology before their processes are ready to absorb it, which is how some of them end up using a tenth of the ERP system they paid for. In this episode, TECH B2B Marketing’s Dan McCarthy and Aaron Hand also talk with Haworth about the readiness of small shops to handle artificial intelligence. Asking what AI enables is more productive than asking what AI replaces, Haworth argues. He shares a working example of using AI to connect siloed accounting, ERP, inventory, and quality systems to let owners ask plain-English questions and get a dashboard on the fly. Haworth’s closing advice for owners who assume they can’t afford outside help: Understand the problem and its inputs first. The tooling is now the cheap part of the solution, but it won’t do much good until owners first understand their processes. Support the show

September 18, 2026Episode 15223 min

Episode 152 - Gerry Vannuffelen, CEO & Founder, Mantis Robotics

“You can have a high speed industrial robot, any type of robot really. And it doesn’t need fences, it doesn’t need safety devices. Everything is there. So it adjusts in real time to its environment.” A fence is usually the price of speed: put a high-speed industrial robot on a plant floor and you cage it off, or slow it down into a cobot and accept the productivity hit. Mantis Robotics founder and CEO Gerry Vannuffelen built the company to close that gap — fenceless robots that run at full industrial speed and adjust in real time to people working around them, reserving a hard stop for the rare moment someone actually reaches out and touches one. In this episode of Manufacturing Matters, host Wynn Hardin sits down with Vannuffelen at Automate 2026 in Chicago to unpack how Mantis certifies its fenceless robots to the same ISO 10218 and ISO 13849 standards as traditional industrial robots — not through power-and-force limiting like a cobot, but through speed-and-separation monitoring that lets the robot see people and avoid them rather than collide or stop. The conversation covers the real-estate cost of a traditional automation project, why cobots often can’t match a person’s throughput, and how Mantis’s newest dual-arm robot splits the difference between a caged industrial arm and an expensive, slower humanoid — mountable on a pedestal, a cart, or an autonomous mobile robot. Vannuffelen also digs into Mantis Studio, the no-code deployment platform and real-time digital twin that — unlike most simulation tools — models the people working alongside the robot, not just the work cell. He makes the case for “physical AI” as the layer that closes the gap between AI’s sandbox reasoning and real-world manipulation, why a deterministic safety layer has to sit underneath any AI model that isn’t 100% reliable, and why he expects mobile manipulators — arms on wheels — to keep gaining ground on humanoids in warehouse and plant-floor settings. Support the show

September 4, 2026Episode 15143 min

Episode 151 - Juan Aparicio of ReshapeX and Ajaiey Sharma of Novanta (ATI Industrial Automation)

“It’s really a needle in a mountain of needles and you just want to find one.” For most manufacturers, the hard part of AI isn’t the model — it’s the knowledge locked in the heads of veteran engineers. In this special Automate 2026 episode of Manufacturing Matters, TECH B2B Marketing’s Jimmy Carroll sits down with ReshapeX’s co-founder and CEO Juan Aparicio and Novanta’s Ajaiey Sharma (ATI Industrial Automation) for a candid case study of how the two companies turned decades of tribal knowledge into a working AI agent. Novanta’s ATI tool changers can be configured millions of ways — the team pegs a single product line at roughly 7 million combinations — and pinpointing the one right configuration used to take days of back-and-forth with application engineers. Sharma and Aparicio walk through how they codified that expertise into an “agentic application engineer” that returns the right answer in minutes, why they set out to be the 5% of enterprise AI projects that succeed rather than the 95% that fail, and the build-versus-buy calculus that led Novanta to partner with ReshapeX. The conversation digs into the unglamorous work behind a reliable agent: gamified, week-over-week testing with real customer queries, a human-in-the-loop feedback loop that moves the system from probabilistic to deterministic, a knowledge graph that reasons on relationships instead of semantics to reach 99.99% precision, and continuous evals to guard against model drift. They close with a playbook for other manufacturers — define the real problem, secure executive cover, get your solution fit right, and treat it like a high-risk project — plus why codifying knowledge before it walks out the door may be the most important thing an established company can do. Support the show

August 21, 2026Episode 15040 min

Episode 150 - Dale Hopkinson, Senior Product Manager, Cloud Services, Thales

“The value is moving from the metal to the code.” As manufacturers add AI and software to their products, the old one-time hardware sale is running out of runway when it comes to improving AI models for manufacturing. For Thales’s Dale Hopkinson, the real opportunity — and the real risk — sits in how that software and AI actually get monetized: not as a bolted-on price tag, but as a flexible, recurring business built to change as fast as the technology does. In this episode of Manufacturing Matters, TECH B2B Marketing’s Winn Hardin sits down with Hopkinson, Senior Product Manager for Cloud Services at Thales, to unpack why software is decoupling from hardware, what that means for OEMs retasking and repackaging existing equipment, and why Bain projects AI, software, and data will add roughly $70 billion to the market within five years. The conversation covers the organizational groundwork companies need before they can monetize AI — P&L ownership, dedicated staff, and roadmaps that survive personnel changes — plus the shift from subscription tiers to usage-based and hybrid pricing, the operational lift of managing renewals, entitlements, and channel relationships, and why protecting AI models and training data on the edge is now a board-level conversation. https://www.manufacturing-matters.com https://www.techb2b.com LinkedIn: https://www.linkedin.com/showcase/manufacturing-matters/ Instagram: https://www.instagram.com/manufacturing_matterspodcast/ #manufacturing #automation #manufacturingmatters #techb2b Support the show

August 7, 2026Episode 14932 min

Episode 149 – Ed Garstkiewicz, Senior Business Development Manager, Emerging Markets, HARTING

“The more we can do with it, then the more likely the humanoids are going to take off and be adopted.” Connectors rarely get top billing. Nobody designs a device around a connector — yet these humble components increasingly determine whether a smart factory, an edge deployment, or a humanoid robot works. As manufacturers push more data, more power, and more intelligence through the same shrinking footprint, the demands on interconnect technology are evolving as fast as the systems they serve. For this episode of Manufacturing Matters, TECH B2B Marketing’s Aaron Hand sits down with Ed Garstkiewicz, HARTING’s Senior Business Development Manager for Emerging Markets, at Automate 2026 in Chicago to talk about the fast-changing world of industrial connectivity. They dig into smart connectors that add sensors, status indicators, and intelligence right at the connection point; the constant balancing act between miniaturization and ruggedization; and why connectors may be one of the keys to making humanoid robots lighter, more efficient, and easier to repair. “A humanoid robot is the perfect example for the need for smart connectivity,” Garstikiewicz notes. “The wiring and connectors make up 5 to 10% of the weight of a humanoid. So if we can add functionality to the connector and reduce the need for other systems, we’re lowering the weight and improving the efficiency of the humanoid robot.” This could be a deciding factor in how quickly humanoids get adopted. If you’ve never given much thought to what’s at the end of the cable, this conversation makes the case that the connector is quietly becoming one of the smartest components on the factory floor. Support the show

July 30, 2026Episode 14833 min

Episode 148 - Andre Marino, Senior Vice President, Industrial Automation, NAM, Schneider Electric

"AI needs data, and industrial data is not available on the general internet." “It's not like you do either AI or manufacturing. If you're smart, you optimize what you have. You would be amazed how much you can gain by just retrofitting your old asset.” AI is finally moving “from PowerPoints to the real world” on the factory floor, but it can’t deliver when fed siloed, proprietary data. For Schneider Electric’s Andre Marino, the foundation comes first: open, software-defined automation that harmonizes industrial data, so manufacturers can train AI models on their own operations instead of buying technology and getting frustrated. In this episode of Manufacturing Matters, TECH B2B Marketing’s Jimmy Carroll sits down with Marino at Automate 2026 in Chicago to talk through what it takes for manufacturers to modernize and compete — from the hyperscale “AI factories” racing to add capacity to the small and midsize companies that make up 85% of the U.S. manufacturing base. The conversation covers the growing competition for energy between AI data centers and factories and why the answer isn’t adding capacity alone while digging into digital twins for upgrading lines with minimal downtime, closing the skills gap by drawing IT talent into the OT world, and a task-first (not form-first) take on humanoid robots and world models. Additionally, the discussion covers what Marino would like to see in U.S. robotics legislation, and his playbook for smaller manufacturers: know what you’re solving for, digitize, automate, optimize — and repeat. Support the show

July 24, 2026Episode 14741 min

Episode 147 - Dr. Ray Hoare, Founder Concurrent EDA

“What we bring to the table is we understand how to take the data, do real-time compute, and turn it into knowledge. So, you got raw data coming in, you got knowledge coming out.” Modern machine vision and imaging systems can throw off a firehose of data far faster than a general-purpose computer can absorb it. Concurrent EDA founder Ray Hoare, PhD, has spent two decades on the other side of that firehose, taking algorithms and moving them into electronics so the compute happens right at the sensor, in real time. In this episode of Manufacturing Matters , TECH B2B Marketing’s Jimmy Carroll sits down with Dr. Hoare to talk through the latest in real-time processing. Dr. Hoare discusses how AI has reshaped the way his team builds — including generating 600,000 lines of code in a single month — and why he keeps telling engineers to “dream big” and prototype what used to feel impossible. The conversation covers when GPUs like NVIDIA Jetson win versus when FPGAs are the only option, such as scenarios involving submillisecond latency, 1,000+ fps cameras, and 50-to-100 Gbps data rates in real-world high-speed applications from additive manufacturing melt-pool monitoring to laser tracking and 3D metrology. The discussion also covers open smart cameras, MIPI sensors, image signal processing techniques, and how the same “firehose” thinking applies to RFSoCs for defense; time-sensitive networking as “Ethernet 2.0”; and a UDP/IP core that moves data from programmable logic to Python far more efficiently than Linux. Dr. Hoare closes with the diagnostic questions he asks every customer: where is your data coming from, what are you trying to extract, and where is it going? Support the show

July 17, 2026Episode 14629 min

Episode 146 - Sheldon Zimmerman & Isabelle Durso, Rockwell Automation

“The end goal for a lot of clients is this dream of a lights-out factory. Before you get there, there’s a stepping stone in between — and it’s this connected factory.” Autonomous mobile robots spent years confined to warehouse aisles. Now, driven by a persistent labor shortage and a wave of AI, they’re moving into the heart of the factory — handling the material movement between “islands of operation” that people increasingly don’t want to do, and taking on mission-critical roles once considered too risky to automate. In this episode of Manufacturing Matters, TECH B2B Marketing’s Jimmy Carroll sits down with Rockwell Automation’s Sheldon Zimmerman (Global Head of AMR Sales) and Isabelle Durso (Business Manager, AMRs) at Automate 2026 in Chicago to unpack where mobile robotics is really headed and what it takes to get robots up and running on a plant floor. The conversation covers how AI is reshaping AMRs from the sensor up to the orchestration layer, the rise of mobile manipulation (and where humanoids do and don’t fit), why simulation and digital twins are becoming essential for de-risking deployments, and the real hurdles to adoption: IT/OT integration, physical infrastructure, and the brownfield-versus-greenfield divide. Zimmerman and Durso also make the case for starting small with pilots, the evolving safety standards that let robots and people share a floor, and why the “connected factory” — MES and ERP talking through a single orchestration layer — is the practical stepping stone toward lights-out manufacturing. Support the show