By Alexandra Brintrup, Lecturer in Digital Manufacturing

UK Aerospace companies no longer sell engineered products; but they sell the use of those products through the combined provision of product sales and support services. A competitive service offering and effective delivery are fundamental to new product sales, aftermarket profitability and growth.

Digital technologies such as predictive machine learning, agent based computing, and digital twins offer a unique opportunity to address the key priorities of the recently UK national strategy on through-life engineering services and its 2025 vision of  20% reduction in through-life cost with 20% increase in availability during the life of a product across the breadth of UK manufacturing sector output.

 DO-TES aims to create the world’s first standardised sector approach to Digital TES implementation, and by doing so, significantly improve the through-life productivity of the UK Aerospace sector. Two main strands are planned:

1. Consolidate existing UK industrial know-how on through-life services by creating a services knowledge platform, accessible to UK OEMs, supply chain companies and MROs, to spread knowledge and understanding of TES principles; and
2. Create a digital technology architecture for TES, integrating design, manufacturing and aftermarket activities, including tools, standards and technologies, to support sector capability development for advanced through-life service provision.

Within the above framework, DIAL leads the Spare Parts Inventory Optimisation work package; the aim of which is to better predict the future demand for spares inventory, responding to the variations in the current state, and usage history of the products. We will be using AI technologies to predict overhaul events, and balance spare parts needs with overhaul facility capacity and cost to optimise the delivery supply chain. The work will also contribute to the Digital TES architecture by creating AI based distributed planning and procurement approaches.

We ran our first workshop on Spare Parts Logistics Planning and Optimisation at Cambridge on the 4th April, with partners from Rolls Royce, Bombardier, BAE systems, ANSYS and Cranfield. The workshop included discussion around existing approaches, and brainstorming on how various strands of AI technology can be used to improve spare parts optimisation. The next few months of the project will see the development of use-cases and identification of initial opportunities within the industrial partners.