Understanding Variance in Raw Material Management

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 direction setting (DDS) meetings help guide capital allocation, continuous improvement initiatives, and team alignment. They share observations on why some facilities succeed with these systems while others fall back into old habits.

Timestamps
00:00 Introduction to Episode 221 and monthly theme recap
02:00 Vlad’s background and approach to modernization projects
04:50 Dave’s background and focus on data-driven manufacturing solutions
06:30 Recap of previous episodes on data collection, historians, and MTP/MCP
07:30 Vlad’s Procter & Gamble energy monitoring project case study
13:40 Addressing power blips, capacitor banks, and ROI considerations
19:10 Choosing between proprietary and open monitoring solutions
23:40 Dave’s pet food manufacturing story and raw material variance
29:50 Methods for data collection without disrupting legacy systems
34:20 Improving accuracy, process changes, and remediation strategies
44:00 Organizational challenges in acting on data insights
52:00 OEE, DDS meetings, and capital allocation in discrete manufacturing
59:50 Predictions for the future of manufacturing intelligence and AI integration

References Mentioned
Ignition by Inductive Automation – https://inductiveautomation.com/
Ignition Community Conference (ICC) – https://icc.inductiveautomation.com/
Procter & Gamble – https://us.pg.com/
Rockwell Automation – https://www.rockwellautomation.com/
Mettler Toledo – https://www.mt.com/
Badwater Ultramarathon – https://www.badwater.com/
“Can’t Hurt Me” by David Goggins – https://davidgoggins.com/book/

About the Hosts

Vlad Romanov works with manufacturers to modernize operations by bridging the gap between legacy systems and today’s technology. He specializes in assessing current states, designing scalable architectures, and implementing solutions across control systems, SCADA, and MES infrastructures. His mission is to help plants run better from a technical and operational standpoint, whether through unlocking critical data from PLCs or leading full-scale digital transformation initiatives.
Connect with Vlad: https://www.linkedin.com/in/vladromanov/

Dave Griffith has over 16 years of experience in automation and manufacturing, with a technical foundation in aviation and aerospace. His work spans from OEM manufacturing to food and beverage production, with a strong focus on data-driven projects that deliver ROI. Dave leads teams at Kaplan to unlock operational data, design integration strategies, and deploy solutions that improve efficiencies and reduce waste.
Connect with Dave: https://www.linkedin.com/in/davegriffith/