Sort by
Refine Your Search
-
AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
for wider industry adoption Cranfield University is a specialist postgraduate institution with a strong track record of applied research and close industry collaboration. The successful candidate will be
-
supported by collaborations with industry giants including Boeing, Rolls-Royce, Thales, and UKRI, this research offers a unique platform to contribute to the advancement of secure, reliable, and transparent
-
world-class programmes, cutting-edge facilities, and strong industry partnerships, attracting top-tier students and experts globally. As an internationally recognised leader in AI, embedded system design
-
sectors like aerospace, healthcare, and manufacturing. The convergence of AI with fault-tolerant design principles is transforming traditional maintenance paradigms, leading to more robust and intelligent
-
and Britain are world leaders and major exporters. This high technology global industry is worth more than £30 billion per annum. Current challenges are arising from the need to address environmental
-
-harvesting technologies to promote sustainability. Cranfield University offers a distinctive research environment renowned for its world-class programmes, cutting-edge facilities, and strong industry
-
-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
-
significant impacts on reducing machine downtime in many industrial applications, including steel casting, paper mill, food industry, wind energy, etc., which leads to reductions in operation and maintenance
-
attracted the attention of businesses in this Industry 4.0 era. Even though the PdM strategy has been introduced more than two decades ago, its adoption and implementation in the industry have been rapidly
-
This PhD project aims to address one of the key challenges in the manufacturing industry, the increase in productivity by utilizing the equipment with its optimum performance and without any