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

EdgeMethods(物联网平台开发商/集成商)和Victrex(高性能聚合物制造商)已经成功完成了关于单一聚合物粉末制造工艺的科学证明能效项目。工作包括确定关键的能源和减排关键绩效指标，并整合关键技术要求(例如，读取油滑上的气体测量数据的传感器)，以衡量能源效率。利用EdgeMethods_SaaS_IoT平台，开发了基于机器学习的能效模型，实现了聚合物制造过程的优化和基于能量的实时事件检测。该项目将专注于进一步开发我们的新型可持续发展模型，这些模型已经在科学证明环境中进行了评估，并准备利用Victrex聚合物生产工厂的真实数据进行进一步开发。该项目将使EdgeMethods能够完成核心平台的开发，并开发/改进/验证聚合物制造过程中的可持续发展ML算法，使我们能够在聚合物/化工和制药以及食品/饮料制造行业快速扩展。

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.