A scalable IoT solution utilising machine-learning to discover actionable insights to reduce energy/resource consumption utilising manufacturing process data.

EdgeMethods(IoT platform developers/integrators) and Victrex(High-performance polymer manufacturers) have completed a successful _Proof of Science_ energy efficiency project on a single polymer powder manufacturing process. Work included defining the key energy and emissions reduction KPIs and integrating key technological requirements (e.g. sensors to read gas measurements on oil skids) for energy efficiency measurement. Utilising the EdgeMethods _SaaS_ IoT platform, machine-learning based energy efficiency models were developed enabling optmisation of the polymer manufacturing process and real-time energy-based event detection.

This project will focus on further development of our novel sustainability models that have been evaluated in a Proof of Science environment and are ready to be further developed with real-world data in Victrex's polymer production factory.

This project will enable EdgeMethods to finalise core platform development and develop/improve/validate sustainability ML algorithms within a polymer manufacturing process which has synergies enabling us to rapidly scale across the polymer/chemical and pharmaceutical and food/drink manufacturing sectors.