Contact Vaishnav Venkata Subhadu
Areas of expertise
- Digital Twinning
Background
Vaishnav is a PhD researcher co-funded funded by the EPSRC Industrial CASE award and Rolls-Royce Plc. He is based at the Centre for Design and Digital Engineering (CDDE) at Cranfield University and wroks in close collaboration with the Services Team at Rolls-Royce. His research lies at the intersection of environmental sustainability modelling and multi-objective optimisation, particularly focusing on the operation and maintenance stages of high-value engineering assets, such as aircraft engines.
Originally from Mauritius, Vaishnav moved to the UK in 2017 to pursue a fully funded MEng degree in Mechanical Engineering at the University of Bristol, where he graduated with First Class Honours. He also brings professional experience in design, maintenance planning, and safety management in the Power Production and Aircraft Maintenance sectors.
His broader interests revolve around the development of systematic and systemic solutions to support the global transitions toward Decarbonisation and Digitalisation.
Research opportunities
- Environmental sustainability modelling and assessment; Decarbonisation
- Multi-objective optimisation
- Asset lifecycle management
- Digital Twin solutions
- Decision support systems for complex engineering assets
Current activities
Vaishnav's current research explores how environmental sustainability can be effectively modelled as a decision-making objective alongside economic cost and performance in multi-objective optimisation. This research is contextualised across different life cycle phases, industry sectors, and decision-making levels (strategic, tactical, operational).
He is also investigating the comparative effectiveness of various optimisation strategies, including normalisation methods, single-objective optimisation, and multi-objective optimisation, in supporting sustainability-driven engineering decisions.
The outcome of this research is a decision support model tailored for maintenance planning and scheduling of complex engineering assets, such as aircraft engines. The research also distinguishes between optimal, near-optimal, and satisficing solutions, supporting more robust and sustainable asset management aligned with decarbonisation/net-zero roadmaps and climate policies.
Clients
- Rolls-Royce Holdings PLC