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Energy and waste reduction in Foundation Industries

AI6S: Energy and waste reduction in Foundation Industries


Most Foundation Industries (FI) rely on legacy machines for their daily operations. Legacy machinery results manufacturing processes that are energy inefficient and often generate higher volumes of waste. The cost of upgrading legacy equipment to permit more modern manufacturing processes can prove a barrier to uptake by industry. The AI lean process optimisation framework will provide a cost-effective means for Foundation Industries to make significant gains in both energy efficiency and waste reduction. Such powerful platforms will assist a number of industries to optimise their processes backed up by a regression algorithm.

Specifically, the AI6S project will use artificial intelligence to develop a next generation lean process optimisation framework for complex industrial data analysis. This will support UK Foundation Industries to take a data driven approach to achieve the British Government's carbon emissions targets through informed process interventions for increased energy efficiency and reduced waste material.


AI6S will develop a novel toolkit for process optimisation in Foundation Industries , enabling process efficiency improvements resulting in

  • reduced energy consumption
  • reduced waste
  • improved ability to meet challenging (and commercially attractive) specifications
  • short turnaround times

Current lean six-sigma methodologies provide efficiency gains through continuous improvement following manual procedures over process iterations. AI6S will make a step change in the ability of companies to achieve "right first time" production output to challenging specifications and stringent quality criteria whilst reducing energy consumption, waste and cost through higher yields.


AI6S process improvements will make significant contributions to reduction in energy use and CO2 emissions in Foundation Industries, reducing pollution and greenhouse- gas emissions, benefitting the environment and quality of like.

AI6S will support UK Foundation Industries making them more competitive in areas where UK manufacturers specialise such as high-quality fast turnaround products e.g. for nuclear and aerospace, helping maintain these industries and the jobs that go with them within the UK. It will also benefit customers - again in areas of importance to the UK through improved quality, lower prices and faster turnaround, promoting growth in the industry and new job creation especially for companies in regions that are recovering from loss of traditional industries such as the north of England and midlands where many Foundation Industries are located.

AI6S will add weight to a growing UK industry sector providing technologies and services in data-intensive industrial tools based on Industry 4.0 concepts, helping to maintain world-class competitiveness for UK manufacturers, but also making the UK the go-to place for software and services within a global market for I4.0 expertise.

AI6S automation will reduce the need for experts engaged in routine process formulating and optimising. Rather than jeopardise their jobs, this will free up this scarce resource to carry out higher added-value work.

Brunel Innovation Centre's Role

Brunel University London and the University of Sheffield will open up a wide range of techniques and facilities for the academic and industrial researchers involved i.e. large-scale manufacturing machinery, historic data, and simulation capabilities. This process will stimulate new ideas and innovative design, which are only possible in such a multidisciplinary collaboration environment. It will accelerate the development of enabling technologies. The use of machine learning to improve lean six sigma process optimisation for foundation industries will be a step change for energy efficiency and to minimise waste material.

As part of the project, Brunel University will develop a machine learning regression model to support the analysis phase of process optimisation. This will be further verified and supported by the process simulation capabilities of the University of Sheffield. This algorithm will then be plugged in to the lean six sigma framework by IVY TECH. This will be a powerful optimisation tool for all industries which require process optimisation, including Foundation Industries such as metal, glass, ceramic, paper etc.

Project Partners







Meet the Principal Investigator(s) for the project

Mr Jamil Kanfoud

Related Research Group(s)

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Project last modified 09/01/2024