The Hidden Knowledge Layer

Why Engineering Organisations Need More Than Data and Models in an AI Enabled World

F​ree Webinar

Thursday, 28 January 2027

15:00 (London) | 16:00 (Berlin)
07:00 (Los Angeles) | 10:00 (New York)

This webinar is being held as p​art of the ASSESS Artificial Intelligence and Machine Learning Theme

Engineering simulation is often discussed in terms of models, solvers, automation, data management and AI. These are essential, but they are not the whole story. In many organisations, the capability that makes simulation valuable sits in a less visible place: the judgement of experienced engineers, the assumptions behind modelling choices, the memory of past failures, the confidence built through repeated decisions, and the context that determines whether a result is useful, misleading or dangerous.

This webinar will introduce the idea of the Hidden Knowledge Layer: the tacit engineering knowledge that sits around simulation workflows but is rarely captured with the same discipline as data, reports, processes or models. Drawing on a practitioner perspective from senior engineering leadership, the session will explore why this hidden layer is becoming a capability risk for engineering organisations, particularly as they pursue automation, democratisation, AI-enabled engineering and broader reuse of simulation capability.

The session will ask a simple but important question: what do engineering organisations protect, and what do they merely hope will be remembered?

Rather than proposing more bureaucracy, the webinar will offer a practical way of thinking about how simulation leaders can make critical engineering judgement more visible, transferable and reusable. It will discuss how organisations can begin to identify where expertise sits, how decisions are actually made, what assumptions are repeatedly relied upon, and how this knowledge might be structured without stripping engineering of judgement.

The webinar will also create a bridge from problem recognition to future implementation. If engineering capability is embodied in people rather than processes, then workflow automation alone is not enough. The longer-term opportunity is to capture and embed engineering knowledge within workflows so that simulation capability becomes more repeatable, resilient and scalable.

Agenda

W​elcome and Introduction
Jo Potts, NAFEMS

The Hidden Knowledge Layer
D​avid Panni

Q&A D​iscussion

U​se the "book" button on the right to register your free place.

A​bout our speaker ...

Dr David Panni CEng FIMechE MWeldI is a senior engineering leader with more than 25 years' experience in simulation-led product development, engineering transformation and applied AI in the off-highway equipment industry.

During his career at JCB, David held senior engineering roles including Chief Engineer for Structures and Simulation and more recently Head of AI Implementation. He led the development of simulation capability from a small UK-based function into a global engineering capability, using simulation-first approaches to improve engineering efficiency, reduce development cost and accelerate product development.

More recently, his work has focused on the intersection of engineering judgement, simulation, AI and organisational capability. He is working with how the knowledge and experience surrounding engineering models can be made more visible, reusable and resilient as organisations adopt AI. His broader AI work has involved turning complex industrial problems into scalable capabilities and faster product development.

David is a Chartered Mechanical Engineer, Fellow of the Institution of Mechanical Engineers and Member of The Welding Institute. He is also a Non-Executive Director of The Welding Institute and Chair of the UK NAFEMS Steering Committee.