The Manufacturing Executive · 31 Mar 2026 · 29m · Episode 303
Paul Ross, CMO of Limble, discusses findings from Limble’s 2026 Maintenance Benchmark Report, revealing that 72-78% of manufacturers remain in a reactive 'break-fix' mode due to poor data quality. He explains that only 20% of organizations trust their maintenance data for capital expenditure decisions, a figure that jumps to 51% when data quality is high. Ross highlights how shifting to preventative maintenance reduces unplanned work from 64% to 34%, citing Alagash Brewing as a case study that achieved a 40% reduction in downtime by digitizing asset tracking.
Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.
Running the companyAI (visual imagery)
AI analyzes photos taken by mobile phones of equipment model data to automatically generate asset records in the maintenance system, enabling rapid digitization of physical assets.
“One of the most interesting applications actually of AI that we've seen … is the ability to use a mobile phone to take a picture of the model data on a piece of equipment and use that to generate that as a record within their systems.”
Speaker 2 · Hear it at 14:52
companies scaling up
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Graham Immerman, Head of Marketing at MachineMetrics, explains how the company’s platform democratizes manufacturing data by collecting high-frequency signals from CNC machines to drive predictive maintenance and capacity optimization. He details the 'analytics journey' from descriptive to prescriptive insights, highlighting a case study where a customer canceled a $14 million equipment order after discovering only 22% machine utilization. Immerman argues that data democratization requires transforming siloed IT/OT data into actionable apps for operators, a shift accelerated by recent supply chain fragilities.
Colin Morris, Senior Director of Solution Consulting at MaintainX, explains that while many manufacturers have data, it is often unstructured and siloed, creating a barrier to effective AI-driven predictive maintenance. He argues that facilities must first digitize logs and capture accurate parts information before implementing advanced analytics, noting that 'no insights' from a predictive system can simply mean assets are running well. Morris details how MaintainX uses voice transcription and agentic AI to reduce administrative burden, allowing agents to handle scheduling drafts while humans approve plans, thereby increasing wrench time for technicians.
Nick Haase, Co-Founder of MaintainX, explains how his non-traditional background in medical device sales and B2C startups like Startup Drugs informed the design of his CMMS and EAM platform. He argues that digitizing maintenance is critical for digital transformation because it captures tribal knowledge from an aging workforce and provides the high-quality, contextual data required for effective AI implementation. Haase emphasizes that software must be hyper-intuitive for frontline workers to ensure adoption, bridging the gap between high-tech equipment and analog processes on the plant floor.
Peter Baker, President of Live Oak Quality Assurance and former FDA Drug Investigator, discusses his career uncovering data integrity breaches in overseas manufacturing facilities. He explains that 99% of data integrity issues stem from poor process design and 'right environment' failures rather than human error, urging companies to shift from compliance-focused checklists to quality-driven critical thinking. Baker highlights specific field failures, such as the manipulation of product quality by blending failed batches with passing ones, and emphasizes the importance of honest reporting of unknown discrepancies to ensure patient safety.
Patrick Carmitchel, VP of Product Management, and Dustin Moore, Condition Monitoring Engineer Manager at AssetWatch, discuss the practical application of condition monitoring and predictive maintenance in manufacturing. They explain how monitoring vibration, temperature, and oil analysis helps identify early warning signs of equipment failure, allowing maintenance teams to plan repairs and avoid unplanned downtime. The conversation highlights the importance of starting with critical assets and managing cultural change on the plant floor to prove ROI before scaling monitoring efforts.
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