A feasibility study investigating how intelligence-based technologies can be used to connect predictive maintenance software to stock management software has received over £250,000 from UKRI's Industrial Strategy Challenge Fund (ISCF) 'Made Smarter innovation challenge' to evaluate emerging smart technologies. The collaborative research project driven by supply chain management company The NBT Group, Northumbria University and industrial software developers Senseye will provide outcomes and knowledge for what could be'a game-changer' in the Industry 4.0 journey – by increasing productivity, up-skilling work roles and effecting more economically, socially and environmentally sustainability. Toby Bridges, Executive Chair at The NBT Group, said: "NBT's ambition is to utilise automation and Industry 4.0 thinking in all its activities, generating more and better jobs within our business and drive operating efficiencies for our clients and suppliers," said Toby Bridges, Executive Chair at The NBT Group. "This funding allows us to work closely with a leading predicative maintenance company in Senseye and Northumbria University's Global Operations and Supply Chain Competitiveness (GLOPSCO) research interest group to widen our thinking on how we integrate our own supply chain technologies into other systems and technologies across the manufacturing plant." Initially the study will assess the use of intelligence – based systems to connect NBT Group's stock management software to Senseye's predictive maintenance software - a platform that allows prediction of upcoming issues with machinery so that failures can be avoided.

A new approach to energy efficiency uses high tech tools to make many small adjustments rather than more costly tactics such as replacing big ticket items like windows and cooling equipment. Startups including Carbon Lighthouse and Redaptive are using data collection and machine learning to make a building's mechanical and electrical infrastructure use power more efficiently. Carbon Lighthouse has helped Tesla cut electricity use at the electric vehicle maker's headquarters by using sensors, data collection, software algorithms, and technical analysis. Carbon Lighthouse engineers focused on two large cooling towers, two chillers, and some pumps at Tesla headquarters. They found an error in how two systems were communicating with each other.