Unilever & Laminar – AI-Driven CIP Optimization

Unilever partnered with Laminar through the 100+ Accelerator to tackle inefficiencies in factory cleaning. By deploying Laminar’s AI-driven in-line spectral sensing technology, Unilever reduced cleaning times by 20%, cut utility use by 10%, and saved €100,000 per year at its Poznań, Poland foods factory.

Challenges Faced

Unilever’s Clean-in-Place (CIP) systems were designed to guarantee product safety but often led to over-washing, excessive utility use, and lost production time. Traditional manual sampling made it difficult to balance compliance with efficiency.

Implemented Solutions

• Installed Laminar’s IoT-enabled spectral sensors in process lines to monitor cleaning cycles in real time.
• Applied AI-powered analysis to identify over-washing and determine exactly when cleaning steps were complete.
• Automated detergent, temperature, and duration settings — ensuring the right clean at the right time.
• Enabled Unilever to move from manual checks and static protocols to dynamic, science-led optimization.

“AI insights from sensor data showed multiple examples of over-washing. It also identified when protocol said cleaning was complete and the data said it wasn’t.”

Results

• 20% faster cleaning times, unlocking additional production capacity.
• 10% reduction in utility use, including water and energy.
• €100,000 annual savings per line at the Poznań foods factory.
• 16.7% faster changeovers year-over-year.
• Planned roll-out to 35 additional sites by 2026.

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“In our foods factory in Poznan, the system has reduced machine cleaning times by 20%, cut utility use by 10% and helped save €100,000/year.”

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This was original published by Unilever.