TwinThread Seminar Series: Achieving Your Manufacturing Goals in the Age of Uncertainty
Using an AI-Assisted Top-Down / Bottom-Up Process to Accelerate Innovation & Operationalize Results
Typical Manufacturing Exec Scorecard
We all have them - scorecards and goals.
We all have operating plans to achieve them.
We all have technology and process backing them up.
And yet… Does this sound familiar to you?
- Are you worried about the high cost of materials?
- Have you been given an energy mandate and are uncertain of your order of solve?
- Does operating performance vary by SKU, line, plant or region?
- Do you know why?
- Are you able to pivot quickly in the face of supply chain disruptions?
Starting with a top down approach to select optimum targets, and then implementing a bottoms up approach to hit those targets is common.
However, manufacturing being what it is, you may have run into some hurdles:
Insufficient Data: Data in multiple, unrelated units, not enough data, bad or missing data
Time Constraints: Not enough time to dig into and analyze your data
Human Subjectivity: Meaning it’s hard for someone to analyze a problem objectively when it could mean big changes for them
Change Adoption: Having the ability to confirm that a change, once implemented, continues.
Over the next few weeks, I’ll be breaking down the steps of an AI-assisted, top-down approach to optimizing manufacturing performance.
- What are the elements of an AI Assisted Top Down Approach?
- What is a bottoms up approach and when should it be used?
- The truth about KPIs
- Top Potential V Top Cause
- Data Lakes
- Digital Twins and Threads
- Reporting Engines V Analytics
Making it Stick
- Execution Execution Execution
- Iteration and Innovation
- Energy Intensity
- Managing Change
Tags:Blog, Digital Twin, Quality, Digital Thread, IIoT, AI, Contextualization, Visualization, Operationalize, Efficiency, KPIs, Manufacturing, Operational Metrics, Innovation, Energy Cost Reduction, Operational Costs
June 28, 2023