PhD Studentship - Data-driven Analytics and Modelling for Net-Zero Manufacturing

This PhD will be conducted full-time. This is open to home and overseas students. Students will receive a tax-free stipend of at least £19,237 per annum that covers the 3.5-year full-time PhD and a tuition fee waiver. Students are additionally eligible for funding to support their research, development, and conference attendance. Interviews for shortlisted applicants will take place in September/October. The start date is January 2025. Funded by the University of Manchester School of Engineering, this project aligns with the Royal Academy of Engineering Research Fellowship initiative, “A novel circular economy-modelling approach to achieving net zero manufacturing”.

Net emissions of Greenhouse Gases (GHGs) by human activities, which includes manufacturing, must approach zero in order to stabilize global mean temperature. With 2023 recorded to be the hottest year till date, a credible and effective plan is urgently needed to avoid the worst effects of climate change, particularly for industrial production. Research has shown that >45% of GHGs derives from products and services (Scope 3), and that a high proportion of embodied carbon, materials and value are lost or wasted at the end of a first lifecycle phase. While energy emissions are largely (and successfully) mitigated by renewable energy forms and carbon capture storage technologies, manufacturing emissions have been largely difficult to manage. This is due to the complexity of manufacturing supply chains; they are harder to reduce, as each manufacturing sector faces its own unique challenges and the lack of a tool kit designed from evidence from manufacturing product and value chain.

Circular Economy provides a framework to drive systemic innovation and transformational interventions in manufacturing through product-life extension, remanufacturing, and re-use. Implementation of CE in manufacturing requires a stronger evidence base to show both the economic and net zero opportunity and potential. Current modelling and analytical tools are not well suited to systemic transformations such as CE. Therefore, a hybrid top down/bottom up approach is proposed, applied to key manufacturing sectors to build the evidence base, prioritise key interventions and road-maps to future Net Zero manufacturing based on CE. Data analytics and modelling shall be a key focus area of the PhD. Within this context, this PhD will investigate how value chain and product scale mapping support CE value modelling, first using generic models, generic simulation and generic tools. This shall be applied to manufacturing supply chains, principally understanding how manufacturing value chains and product scale mapping support circular economy value identification and modelling.

The main of the PhD will thus be to investigate the transformative opportunities for a Net-Zero Circular Manufacturing through hybrid top-down/bottom-up modelling, via Multi-Regional Input Output modelling.

Expectations from the PhD:

1. Review and map the landscape of modelling methodologies (Scope 1, Scope 2 and Scope 3) and different forms of data-driven analytics for net zero manufacturing.
2. Review and define parameters for value chain and product scale mapping to support net zero manufacturing
3. Develop a conceptual decision-support framework for net zero manufacturing.
4. With industry partners, design and create exciting public and industry-facing case studies that apply the framework.

For further information on the project, please contact Dr. Okechukwu Okorie (okechukwu.okorie@manchester.ac.uk)

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