APPROACH
To address this, the team at Tredence developed an analytically robust approach with the following specifications:
- Identified primary drivers among the selected machine variables using ML variable reduction techniques
- Driver models to understand key influential variables and determine the energy consumption profile
- Identified the right combination of drivers under the given production constraints – time, quantity and quality
- Optimization engine to provide the machine settings for a given production plan
KEY BENEFITS
- The learnings will be used across similar machines to create operational guidelines for reducing energy consumption
RESULTS
- We were able to achieve a ~5% reduction in energy consumption across major machines