DO-TES

Digitally Optimised Through-life Engineering Services (DO-TES) is a project pursuing the development of digital tools in order to improve the design, maintenance and operation efficiency of engineering components throughout their lifecycle. The project consortium includes Rolls-Royce UK, CFMS, BAE Systems, University of Cambridge, Cranfield University, and Siemens.

The DO-TES project utilises digital tools to reduce the through-life cost whilst increasing the efficiency and availability of complex engineered products across the UK manufacturing sector, predominantly within the aerospace industry. Introducing intelligent and adaptive maintenance to sophisticated engineered products, resulting in a more prominent, cost-effective and safer in-service operation.


In more detail, the core value propositions are; to avoid the need to perform maintenance through better design and operation processes; contain events impact and the demand for maintenance; and recover asset life and performance through cost effective maintenance.

Over the course of the projects lifetime DO-TES evolved greatly, with a broad spectrum of digital tools being developed and tested throughout. With specialist expertise within knowledge management (KM), CFMS’ role began as the owner of a degradation knowledge base management solution, which would create an easily accessible store of degradation oriented knowledge relating to the performance of an engineering system. However, in the pursuit of generating data CFMS developed a range of engineering modelling capabilities as well as a knowledge base management solution.

CFMS produced a number of digital engineering technologies including automated system structure generation, automated hypothesis generation and testing, high fidelity and system model integration and a hardware accelerated ray tracing physics framework. These digital tools contribute to the improvement of design and operation at different stages of the product life cycle, helping to reduce costs and increase efficiency within the manufacturing industry.

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