Postgraduate Researcher, Loughborough University
Andrew obtained his honours degree in Automotive Engineering Design at Coventry University before joining Triumph Motorcycles as a Chassis Design Engineer. A Chartered Engineer with nearly 20 years’ experience CAD modelling using PTC products he has subsequently worked as a Design Engineer/Consultant with several of the UK’s leading product design consultancies, on a diverse range of products spanning multiple industrial sectors.
With a continued interest in the motorcycle industry, he has punctuated his work in product design with involvement on projects for BMW, Harley Davidson, Indian, Norton, Royal Enfield and Triumph. Experienced in the production of complex engineering drawings, carrying out FMEA and statistical tolerance analysis, he is a named inventor on numerous patents and author of CAD guidelines and procedures.
In his time responsible for modifying existing CAD models Andrew observed a common theme across all design departments and industries: noticeable numbers of ineffective parts were being submitted as master models, occasionally even despite quality analysis tools being used in their production.
The evolution of Industry 4.0 combined with the availability of exciting new engineering development tools means the importance of CAD model effectiveness has never been higher. Andrew decided that this was an area worthy of closer examination and in July 2017 he took a sabbatical from work commitments to develop and pursue a full-time doctoral research study at Loughborough University. He is currently examining how to identify and quantify inefficiencies within industrial parametric CAD models, with the support of Triumph Motorcycles, Concurrent Engineering Ltd and PTC.
Tell Us Something Interesting:
I am continually intrigued to hear about the development of new tools that assist the engineer in developing the best products possible. However, these tools require the most suitable CAD models and I am thrilled to be currently pursuing a PhD examining how these can be identified and quantified