4 Ways AI Can Actually Speed Up Problem-Solving on the Manufacturing Floor

Digital Transformation in Manufacturing: How to Actually Make an Impact

Anne Emberson, Vice President of Digital at Nalco Water, joined Josh Santo on the Shop Floor/Top Floor Talk Show to talk about what digital transformation in manufacturing actually requires, separate from the hype cycle around it. Emberson described how her team stays current in a field that moves fast enough to make today's knowledge feel outdated within a week, splitting their attention between watching the outside world (conferences, vendors, customer behavior) and examining their own internal processes. The conversation moved through several of the most common failure points in digital projects. Emberson argued that waiting for perfect, complete data before acting is effectively waiting forever, since manufacturers already sit on enough data to act on now. She also pushed back on treating digital initiatives as IT projects, arguing instead that they should be framed as operational problems with measurable financial or operational outcomes attached from the start. Cross-functional involvement came up repeatedly, including her observation that the person most resistant to a new tool can sometimes become its strongest advocate once brought into the planning process early. Toward the end, the discussion turned to AI specifically. Emberson named two myths she sees often, that AI can solve everything and that AI is going to take over all the jobs, and described an internal experiment her team ran comparing the water and energy cost of an AI-generated song to roughly 1% of a steel production run. She closed by describing manufacturing as approaching a tipping point, where lessons learned from back-office digital adoption start showing up on the plant floor in lower-risk ways.

4 Ways AI Can Actually Speed Up Problem-Solving on the Manufacturing Floor

AI won't write your 8D for you — not one worth sending to a customer, anyway. That's where Rich Nave starts this conversation, and it sets the tone for everything that follows. The episode is a ground-level walkthrough of where AI actually earns its place in manufacturing problem-solving: not as a replacement for engineering judgment, but as something that helps teams move faster, stay focused, and stop reinventing the wheel. The conversation covers four specific areas where manufacturers are already seeing real returns. First, problem definition — where AI can quickly generate multiple versions of a problem statement, giving teams a starting point instead of a blank whiteboard. Second, data analysis — where AI's ability to surface correlations across thousands of data points narrows an investigation from overwhelming to manageable (with a clear-eyed reminder that correlation is not causation, and that part is still human work). Third, organizational knowledge — how AI can index past 8Ds, articles, and solutions so teams stop resolving problems that were already solved, sometimes in a different plant, years ago. The fourth area is where the numbers get hard to ignore: using AI to propagate the changes from a completed 8D into downstream documents — the PFMEA, control plan, LPA questions, standard work instructions. A process that typically takes a full day of skilled effort was completed in under thirty minutes in a recent real-world test. Not flawlessly — two of five AI-generated LPA questions had to be cut — but fast, and close enough that the human review step was the work, not the drafting.

Leadership, Leadership, Leadership: The Real Root Cause of Quality Failures

In this episode of Shop Floor, Top Floor Talk Show, host Josh Santo sits down with Rich Nave, COO of The Luminous Group and a returning guest with 38 years in manufacturing, to talk about one of the more stubborn problems in the industry: quality. Specifically, why so many manufacturers are still stuck inspecting parts after they're made instead of building quality into the design and process from the start. Rich walks through the difference between what he calls "reactionary quality" and proactive quality. The reactionary version measures parts after production, which means all the material, labor, electricity, and compressed air has already been used before anyone decides whether the part is any good. The alternative is designing a process reliable enough that consistent results are basically guaranteed, so you're checking process parameters like pressure and temperature rather than sorting good parts from bad ones at the end of the line. He makes the case that quality needs to run through design, process engineering, and operations, not sit in a single department acting as a gatekeeper. And the tools for doing this aren't new. FMEAs have been around since the 1980s, LPAs since the early 2000s. The reason manufacturers aren't using them well isn't a missing tool. It's leadership. Rich argues that leaders have to commit time and resources upfront instead of defaulting to firefighting after something goes wrong.

Next-Gen Quality in Manufacturing: Engineering the Future of Quality Systems

In this episode of Shop Floor, Top Floor Talk Show, host Josh Santo sits down with Sainyam Arora, Quality Assurance and Systems Engineer at Johnson Matthey. They explore why quality breaks down when companies treat it as a department instead of a shared responsibility. Sainyam explains how silos weaken ownership and turn quality into policing. He argues that leaders must ask better questions, connect quality to customer impact, and invite operators into the process. He also warns that standard work can slip into complacency when teams stop asking why. To build real improvement, companies need space for curiosity, trust, and shared language. Josh and Sainyam also dig into AI. Sainyam says most plants still run on fragmented systems and mixed data, which limits what AI can do. He argues that manufacturers need a common data language first. The episode ends with a look at workforce change and continuous improvement ahead.

Manufacturing Leadership: Why Quality and Customer Experience Belong Together

In this episode of Shop Floor, Top Floor Talk Show, host Josh Santo sits down with Anne Trobaugh, Vice President of Quality and Customer Experience at American Woodmark. Together, they explore what it takes to move quality beyond a compliance exercise and make it a real driver of customer satisfaction and business results. Anne shares how her team at American Woodmark developed a customer experience dashboard built on direct feedback, focusing on delivery, product quality, and response. She explains why keeping priorities clear, communicating results across all levels, and empowering teams to solve problems make a measurable difference. Anne also discusses the value of seeking diverse perspectives, learning when to end projects that no longer serve their purpose, and using data to drive decisions at the executive level. The conversation closes with Anne’s take on the need for more women in manufacturing, the power of mentorship, and the growing role of artificial intelligence in improving both back office and plant floor operations.