FranceFood and restaurants2020 – ongoingTereos
Dalkia Analytics by METRON for Lillebonne energy management
Tereos reported about 5% less steam consumption after introducing AI energy monitoring
Problem
Lillebonne's teams reviewed energy indicators in spreadsheets and investigated deviations after they occurred. Corrective action sometimes came too late because engineers lacked timely operating context.
Approach
Tereos introduced Dalkia Analytics by METRON to model reference energy consumption and detect deviations during production. Plant specialists worked with energy experts and data scientists to configure the models. Operators received control screens and reviewed performance daily.
Results
Takeaway
The models connected unusual consumption with operating conditions that staff could investigate. One detected problem involved excess steam consumption caused by a bypassed heat exchanger.
Categories
- Size
- Large enterprise
- Industry
- Food and restaurants
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Vendor solution
- Evidence
- Company's own claim
Sources
Source summaries
The joint presentation described Lillebonne's reference models and operational monitoring. It reported a steam-consumption reduction of about 5% over 1 year and an example of detecting excess consumption from a bypassed exchanger.
Full details are in the original sources.
