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Ron Crabtree speaks with supply chain professional Philip Godden about finding the real system constraint before investing in automation. Philip explains how to model capacity across an operation, verify a bottleneck with data and direct observation, stabilize the process, and add flexible capacity without overbuilding. They also discuss peak demand, autonomous mobile robots, staging, robots as a service, and why solving the wrong problem can move work faster without improving total throughput.
Ron Crabtree speaks with reliability engineer Russ Parrish about improving maintenance and reliability without making the work harder than it needs to be. Russ explains how to establish a clear starting point, reduce conflicting metrics, standardize definitions across sites, and connect reliability work to safety, quality, output, cost, and customer performance. They also discuss OEE, asset criticality, design for reliability, and how to select AI use cases that solve a defined problem.
Ron Crabtree speaks with Robert Semethy about building a support function that can take on more work without relying on heroics. Robert explains how digital processes should create usable data, decision support, and evidence that can answer an auditor's questions years later. He also shares how training, external certification, internal succession, and regular reviews of risks and controls help teams increase capability while removing work that no longer matters.
Explore how to build a synchronized enterprise before AI amplifies the wrong things. Ron Crabtree speaks with David Friedson about diagnosing whether people across functions share the same measures of success, locating breakdowns where products, information, and decisions cross functional boundaries, and testing whether AI removes a true business constraint or only automates around it. They discuss contribution-margin models, the risk of tool-first AI projects, disintermediation, dynamic operating models, and the importance of measuring improvement across the entire value chain.
Explore why labor, digital transformation, and productivity are different expressions of the same organizational problem. Ron Crabtree speaks with Michael Carroll about how outsourcing can break the learning loop, how lost experience increases operational risk, and why digitizing work without transforming decision rights creates latency. They discuss mapping high-inference and high-permission points, starting with the decision rather than the technology, distinguishing information transfer from changes that carry responsibility, and using guardrails and a decision ledger to improve the path from signal to action.
Explore how organizations can pursue AI-enabled productivity without allowing trust to outrun governance and control. Ron Crabtree speaks with Clif Triplett of Watchman Global Alliance about treating information as a corporate asset, building an information bill of materials (I-BOM), compartmentalizing sensitive data, limiting access, and matching AI controls to business risk. They also discuss how to prioritize critical assets, examine supply-chain exposure, and avoid assuming that another technology purchase will solve a broader process, policy, skills, or architecture problem.
Explore how AI agents can help industrial organizations address labor shortages, digitize work, and do more with less. Ron Crabtree speaks with Len Landale and Scott McIsaac, co-founders of Helios Core AI, about moving beyond basic AI tools toward intelligent automation that can perform real work. They discuss where to begin, why processes and tribal knowledge must be documented, and how manufacturers can pursue measurable value without overlooking training or security.
Explore how manufacturing leaders can navigate the AI revolution with Ron Crabtree, Nick Caruso, and Sze “Z” Wong on MetaPod. Discover why executive adoption must come before company-wide transformation, how business context and secure data access make AI more valuable, and why every initiative should be tied to measurable operational outcomes and ROI. The conversation also examines AI governance, agent permissions, prompt injection, digital labor, and the importance of managing AI agents with clear roles, accountability, and version control.
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