Active Education & Skills Economics & Business

Manchester Metropolitan University and Jacobson Group Limited KTP 24_25 R5

In plain English

AI plain-English summary

A product development cycle—from initial design to final product—is being overhauled with new digital tools to cut waste and speed up the process. This matters because most manufacturing still relies on slow, resource-heavy cycles: physical prototypes, repeated testing, and late-stage fixes that consume energy and materials. The project aims to embed digital capabilities—such as simulation, data analytics, and automated decision-making—directly into the development workflow, so problems are caught and corrected before any physical part is made. If the research succeeds, manufacturers could shorten development times, reduce material waste, and lower energy use across the product lifecycle. The impact would be felt in sectors people rarely think about: supply chains, industrial machinery, and consumer goods production. Fewer discarded prototypes and less rework mean lower costs and a smaller environmental footprint. This is applied, commercially focused work—a Knowledge Transfer Partnership between Manchester Metropolitan University and Jacobson Group Limited. It is not fundamental science. The goal is a practical, deployable system that makes product development leaner and more sustainable, not a new theoretical insight.

View original technical description
To develop novel digital capabilities to improve the efficiency and sustainability of the product development cycle.

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

Manchester Metropolitan University and Jacobson Group Limited AKT3 2024
Manchester Metropolitan University and Laker Vent Engineering Limited KTP 23_24 R4
Manchester Metropolitan University and Gerrards of Swinton Limited KTP 21_22 R4
Manchester Metropolitan University and Siemens Energy Limited KTP 25_26 R1
Manchester Metropolitan University and Aspire for Intelligent Care and Support CIC KTP 23_24 R1

Original classification

Knowledge Transfer Partnership

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.