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Last updated 14th March 2023

Andrew Longstaff is Professor of Machine Tool Metrology at the University of Huddersfield. He is a research Director in the Centre for Precision Technologies (CPT).

Andrew has an honours degree from Edinburgh University in Mathematics and Masters in Engineering Control Systems and Metrology from the University of Huddersfield. He then completed a PhD in modelling the errors of machine tools and non-Cartesian machines under the supervision of Prof Derek Ford at the University of Huddersfield. Since that time he has been very active in instigating national and international collaborative research projects. He led the University’s research on three high-value European research and innovation projects and has instigated four major Innovate UK projects, proposing and leading the main themes of the projects. He has also instigated four Knowledge Transfer Partnerships and co-supervised on three others.

He was a co-investigator, Theme 1 technical lead and member of the advisory board for the “EPSRC Centre for Innovative Manufacturing in Advanced Metrology,” and is a co-investigator for the “EPSRC Future Metrology Hub.” He was awarded an EPSRC High Value Manufacturing Catapult Fellowship in 2014, during which he has forged close links with the Advanced Manufacturing Research Centre at the University of Sheffield.

Andrew is Course Leader for the MSc Engineering Control Systems and Instrumentation, where his research and that of his colleagues is embedded in the teaching.

Andrew is a member of the EPSRC Peer Review Full College, a fellow of the Higher Education Academy (FHEA), Member of the IET, Member of the CMI and Chartered Manager. He is heavily involved in standards as Chair of the British Standards Institute committee MTE/1/2, “Machine tools – Accuracy” and member of ISO/TC 39/SC 2 “Test conditions for metal cutting machine tools.” He works closely with the Manufacturing Technologies Association (MTA) as part of their Technical Committee.

Andrew’s research career has been focussed on evaluating and improving the performance of machine tools in terms of their build-geometry, control and response to external influences, such as temperature. A necessary part of this is has been a scientific approach to the measurement of the errors on the machine and of the resulting manufactured part. His research has concentrated on the errors and uncertainties associated with a wide array of measurement tools, such as coordinate measuring machines (CMMs), comparator gauges, laser interferometers, laser trackers, etc.

In recent years, this has extended to projects related to artificial neural networks and machine learning, with applications in efficient analysis and processing data from manufacturing metrology.

Andrew’s research group has always worked in collaboration with industrial partners, from machine tool and instrument manufacturers to end-users. They seek to tackle everyday technical problems, while undertaking a parallel fundamental research plan to create the technologies that can help to overcome the anticipated problems of the future.