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.