Professor Peter Kinnell

MEng, PhD, AFHEA, CEng, MIMechE

  • Professor of Metrology
  • High Value Manufacturing Beacon Lead

Having completed a degree in mechanical engineering, and then a PhD in micro technology, in 2003 Peter joined GE Sensing, where he progressed to the role of senior design engineer. While at GE, he was responsible for developing the company’s high performance TERPS range of sensor. Peter left GE Sensing to take a Lectureship in manufacturing and metrology at The University of Nottingham in 2007 where he worked on metrology for high precision manufacturing.

In 2010, he joined Loughborough University as a Senior Lecturer in Metrology and Automation. Peter holds an EPSRC Fellowship in manufacturing, and is currently a member of the Intelligent Automation Centre at Loughborough, where he leads the Robust Intelligent Metrology Laboratory.

Peter graduated from the University of Birmingham in 2001, with a MEng in Mechanical Engineering, and a Diploma of Industrial Studies. During his studies, he spent one year at the Danish Technical University as part of the Erasmus exchange programme. Peter then stayed at Birmingham to complete a PhD in Micro Electro Mechanical Systems (MEMS), funded by EPSRC and GE Sensing. His thesis investigated novel micro mechanical structures and manufacturing processes suitable for improving the performance of MEMS resonant pressure sensors.

Peter's research is focused on supporting the current and future measurement and sensing needs of industry. He is currently involved in the following active areas of research:

  • Ultra-compact fibre-based high precision displacement sensor technology for on-machine or in-process applications
  • Multi-sensor robot mounted metrology systems for high resolution inspection of large complex parts
  • Understanding, mapping and simulating the performance of 3D machine vision
  • Metrology for enhanced performance robotics manufacturing, currently focused on large format 3D printing of concrete parts
  • Measurement systems to digitise and track the factory workspace, including high speed marker less tracking of people in 3D
  • The use of machine learning for defect detection or quality prediction

Current teaching responsibilities:

  • WSB501: Integrating studies
  • WSC504: Applied Engineering Design & Analysis
  • WSD503: Total Product Design - Project Engineering

Current administrative responsibilities:

External collaborators:

  • The Future Metrology Hub at Huddersfield University
  • Institution of Mechanical Engineers (IMechE)
  • EPSRC College of peer reviewers
  • Manufacturing Technology Centre (MTC)
  • National Physical Laboratory (NPL)
  • British Standards Institute (BSI)