{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Manufacturing Hub","title":"Ep. 221 - Manufacturing Intelligence: Data Collection, OEE, and Energy Monitoring Case Studies","html":"","width":"100%","height":180,"duration":4176,"description":"In Episode 221 of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith sit down without a guest to share valuable real-world lessons on data collection, manufacturing intelligence, and implementing solutions that deliver measurable ROI. This episode wraps up the month’s theme on manufacturing intelligence by tying together the insights from previous episodes and putting them into the context of real plant-floor projects.Vlad begins with an in-depth story from his time at Procter & Gamble, where he led an energy monitoring project with the ambitious goal of reducing power consumption by 20 percent. He explains the practical challenges of turning a corporate initiative into an actionable plant-level strategy, from limited baseline data to deciding between standalone meters and integrated monitoring solutions. Vlad shares the lessons learned in balancing cost, data ownership, and scalability, and why a more open solution can sometimes offer greater long-term value than proprietary systems.Dave then takes us into the world of pet food manufacturing, where millions of dollars in raw materials can be lost each year due to inaccurate batching and poor measurement practices. He walks through the process of defining the problem, setting up data collection without overhauling legacy systems, and using that information to identify overages, improve tolerances, and design remediation strategies. The conversation dives into practical engineering decisions, such as when to invest in VFDs for precision dosing, when to redesign process equipment, and how to ensure data insights lead to lasting operational changes.The discussion expands into organizational challenges, including why decision-makers often lack actionable visibility into losses, how to present findings in terms of tangible business impact, and the cultural shift required to actually use the data once it is available. Vlad and Dave also explore examples from discrete manufacturing, where OEE tracking and daily...","thumbnail_url":"https://img.transistorcdn.com/yoKAvzBXZ3YjQTekFk7KFGXeuwJ29WgXvop3dVEfhLs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzE3MjEzLzE2MDk0/MzA1OTgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}