Executive Briefing - Towards Self-Serving Aircraft
Cambridge and Boeing breakthrough to revolutionise supply chain industry
Promising early results for intelligent aviation spares
Researchers from the University of Cambridge have developed a system where components in the supply chain effectively make their own decisions.
Working in collaboration with Boeing, Duncan McFarlane from the Institute of Manufacturing and a team from Cambridge Service Alliance, have designed a system where aircraft parts monitor their own condition, detect when a replacement is needed, order a replacement and schedule a refit.
The system has wide implications for a range of industries, particularly those with complex supply chains. Results from early evaluations are encouraging.Duncan McFarlane said: “Like many other organisations, the airline industry is under intense pressure to reduce costs and increase performance. With a Boeing 747 400 made of six million parts, there is ample opportunity for significant performance gains and cost reduction in the hugely complex aviation services industry.”
The team is using intelligent object technology to develop “self-serving assets”. These are an information-based representation of each unique part; they can communicate effectively with their environment; retain or store data about themselves; deploy a language to display their features and requirements; and can participate in or make decisions.
But, in order for these self-serving assets to be valuable, they have to work tactically, operationally and strategically.
McFarlane explains: “Ideally they need to be able to monitor their environment in order to decide on actions, decide on service needs and select providers, interact with providers and other assets to make co-operative decisions and monitor whether anticipated activity has taken place, re-ordering if necessary. The critical breakthrough came when we were able to create a multi-agent system architecture through which software agents can act on behalf of their physical counterparts.”
This multi-agent system is showing considerable promise. Typically, the same process would be carried out manually, involving database searches, paper-based proposal exchanges with providers, and selection, possibly based on human judgement.
“With self-serving assets, decision-making and procurement is faster. Decisions are now traceable and based on algorithmic models, thus eliminating human errors in data gathering and decision-making,” McFarlane says.
“The intelligent self-serving asset has the potential to deliver reduced complexity, reduced time to service, less risk of system failure and better decision-making. Overall this should result in considerable costs savings through greater efficiency, as well as improved performance. We still have some way to go, but it is already clear that self-serving assets are viable with the potential to revolutionise the aerospace and other complex supply chain industries.”
The research is closely linked to the work of the Cambridge Service Alliance, a partnership between global business and academics, focused on understanding and developing service systems.
For further information contact:
Colin Hallmark / Rod de St Croix: 3:nine
(Tel: 0207 736 1888; 07745 914170; email: firstname.lastname@example.org)
Notes for Editors
The Cambridge Service Alliance was founded by Cambridge University in 2010. A global co-operation between businesses and universities, the Alliance was established to help companies gain competitive advantage by addressing the challenges they face in designing and delivering tomorrow’s high performance complex services.
Towards Self Serving Aircraft: Revolutionising the service supply chainThe research was conducted by colleagues of the Cambridge Service Alliance, working in the Distributed Information and Automation Laboratory (DIAL) at the Institute of Manufacturing, in collaboration with the Boeing Company. The report was authored by Alexandra Brintrup, Member of the Institute of Electrical and Electronics Engineers (IEEE); Duncan McFarlane, Damith Ranasinghe, and Tomas Sanchez Lopez, University of Cambridge; and Kenneth Owens, The Bo