Cleanroom Optimisation

Context & Aim

Classification 6-8 cleanrooms are using 40-60% more energy than required. In addition manual environmental monitoring practices lead to unnecessary product quarantine and scrap.

The aim is to:

  • Reduce/Eliminate the cost of manual testing.
  • Reduce the number of cleanroom recertification.
  • Minimise/Eliminate quarantine/scrap product due to cleanroom excursions.
  • Minimise the energy consumption while operating cleanroom within spec.

Challenge

Can Artificial Intelligence be utilised to reduce energy consumption in a cleanroom environment while maintaining critical to quality standards?

Solution

  • To produce a machine learning control algorithm that will control cleanroom air change rates based on critical to quality production and environmental parameters to reduce energy consumption.
  • Actively controlled cleanroom on a partner company’s facility.
  • 4 x simulations of potential energy savings on partner company facilities.
  • Energy Efficient HVAC system for cleanrooms design guide.

PROJECT MANAGER

David McCormack
Director of Sustainable Manufacturing

THEMATIC PILLAR

Sustainable Manufacturing

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