Active Materials & Manufacturing Engineering

Teesside University and Ford Aerospace Limited KTP 24_25 R2

In plain English

AI plain-English summary

A materials science partnership between Teesside University and Ford Aerospace Limited is developing new surface engineering and joining techniques to unlock commercial opportunities in advanced manufacturing. The project addresses a specific industrial gap: current methods for bonding and treating metal surfaces limit what can be built—particularly for lightweight, high-performance components used in aerospace and other precision industries. Without better surface engineering, manufacturers cannot reliably join dissimilar materials or achieve the durability needed for demanding applications. If successful, these techniques could allow Ford Aerospace and similar companies to produce stronger, lighter, and more complex parts. That matters for aircraft, where every kilogram saved reduces fuel consumption, and for any system that depends on reliable joints between different materials—from vehicle chassis to industrial machinery. The work is applied and commercially focused: the goal is to move new surface treatments and joining processes from the lab into production lines, creating new products and supply chain opportunities for UK manufacturing.

View original technical description
To unlock new market opportunities through advanced materials, products, and processes by establishing a material science innovation in surface engineering and joining techniques.

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

Teesside University and Enginuity KTP 22_23 R1
Teesside University and Lionweld Kennedy Flooring Limited: KTP 22_23 R2
Teesside University and Saturn Turbo Services Limited KTP 24_25 R3
Teesside University and Tekgem (UK) Limited KTP 21_22 R4
The University of Sheffield and Boeing United Kingdom Limited 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.