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Professor Jonathan Corney

Design, Manufacture and Engineering Management


A methodology for near net shape process feasibility assessment
Marini Daniele, Corney Jonathan R.
Production and Manufacturing Research Vol 5, pp. 390-409, (2017)
Grain boundary precipitation in Inconel 718 and ATI 718Plus
Hassan Bilal, Corney Jonathan
Materials Science and Technology (United Kingdom) Vol 33, pp. 1879-1889, (2017)
A methodology for assessing the feasibility of producing components by flow forming
Marini Daniele, Corney Jonathan
Production and Manufacturing Research Vol 5, pp. 210-234, (2017)
The generation of problem-focussed patent clusters : a comparative analysis of crowd intelligence with algorithmic and expert approaches
Wodehouse Andrew, Vasantha Gokula, Corney Jonathan, Maclachlan Ross, Jagadeesan Ananda
Design Science Vol 16, (2017)
Business models : a routine dynamics reconceptualization
Nair Anup Karath, D'Adderio Luciana, Corney Jonathan
British Academy of Management 2017 Conference, (2017)
Rethinking the foam cosmesis for people with lower limb absence
Cairns Nicola, Corney Jonathan, Murray Kevin, Moore-Millar Karena, Hatcher Gillian D, Zahedi Saeed, Bradbury Richard, McCarthy Joe
Prosthetics and Orthotics International, (2017)

more publications

Research interests

Geometric Reasoning for Design and Manufacture, Advanced Materials

Professional activities

Mechanical Engineering Department, University of Edinburgh (External organisation)
CAD conferences
Keynote/plenary speaker
Coordinationg Design aspects of WeirSPM pump redesign project
EPSRC (Journal)
Peer reviewer
Joint Conference on Geometric and Physical Modelling
West of Scotland KTP advisory board (External organisation)

more professional activities


Rahimi, Salaheddin (Principal Investigator) Corney, Jonathan (Co-investigator) Rae, William (Research Co-investigator)
Period 01-Oct-2015 - 01-Oct-2019
Impact Acceleration Account - University Of Strathclyde 2012 / R120526-111
Corney, Jonathan (Principal Investigator)
Period 01-Oct-2012 - 31-Mar-2017
Smart RoboCarer: Towards Next-generation Robotic Care System for the Elderly
Yang, Erfu (Principal Investigator) Corney, Jonathan (Co-investigator)
This project aims to improve the mobility and independent living of the elderly by carrying out fundamental research programme in the targeted domain with the focus of addressing the gaps in applying robotics and autonomous systems (RAS) to the healthcare field for widening RAS’s social and economic impact. The research objective is to investigate affordable next-generation assistive healthcare technologies by performing a PhD-level study on the smart robotic carer for facilitating the diagnosis, monitoring, preventative care, treatment and rehabilitation of the elderly in the presence of chronic disease conditions such as mild cognitive impairment. To achieve this objective, the proposed project will be focusing on the following three research tasks: 1) To automatically detect and intelligently recognize the hazardous situations within the residential areas of the elderly. 2) To provide reliable and accurate alarms for medical interventions and predictive risk assessments through safe and reliable networks. 3) To facilitate the self-management of the elderly by integrating different health data (multimodal information) and monitoring the trends and changes in a timely manner. The proposed project is closely aligning with one of priorities within the EPSRC’s Prosperity Outcomes Framework, i.e., Health. The ultimate ambition of this proposed research is to deliver effective interactive solutions and services in social healthcare – underpinned by adopting novel cognitively-inspired, proactive human-robot interaction paradigm.
Period 01-Oct-2017 - 30-Sep-2020
Design the Future 2: Enabling Design Re-use through Predictive CAD
Corney, Jonathan (Principal Investigator) Quigley, John (Co-investigator)
"Engineering Design work typically consists of reusing, configuring, and assembling of existing components, solutions and knowledge. It has been suggested that more than 75% of design activity comprises reuse of previously existing knowledge.

However in spite of the importance of design reuse activities researchers have estimated that 69% of companies have no systematic approaches to preventing the reinvention of the wheel. The major issue for supporting design re-use is providing solutions that partially re-use previous designs to satisfy new requirements. Although 3D Search technologies that aim to create a Google for 3D shapes have been increasing in capability and speed for over a decade they have not found widespread application and have been referred to as a solution looking for a problem! This project is motivated by the belief that, with a new type of user interface, 3D search could be the solutions to the design reuse problem.

The system this research is aiming to produce is analogous to the text message systems of mobile phones. On mobile phones 'Predictive text' systems complete words or phrases by matching fragments against dictionaries or phrases used in previous messages. Similarly a 'predictive CAD' system would complete 3D models using 'shape search' technology to interactively match partial CAD features against component databases. In this way the system would prompt the users with fragments of 3D components that complete, or extend, geometry added by the user. Such a system could potential increase design productivity by making the reuse of established designs an efficient part of engineering design.

Although feature based retrieval of components from databases of 3D components has been demonstrated by many researchers so far the systems reported have been relatively slow and unable to be components of an interactive design system. However recent breakthroughs in sub-graph matching algorithms have enabled the emergence of a new generation of shape retrieval algorithms, which coupled with multi-core hardware, are now fast enough to support interactive, predictive design interfaces. This proposal aims to investigate the hypothesis that a Predictive CAD system would allow engineers to more effectively design new components that incorporate established, or standard, functional or manufacturing geometries. This would find commercial applications within large or distributed engineering organizations.

This project is an example of how data mining could potentially be employed to increase design productivity because even small engineering companies will have many hundreds of megabytes of CAD data that a Predictive CAD system would effectively pattern match against."
Period 01-Aug-2017 - 31-Jul-2020
Epsrc Doctoral Training Grant | Wilson, Michael
Xirouchakis, Paul (Principal Investigator) Corney, Jonathan (Co-investigator) Wilson, Michael (Research Co-investigator)
Period 01-Oct-2014 - 01-Oct-2018
Ion, William (Principal Investigator) Ion, William (Principal Investigator) Corney, Jonathan (Co-investigator) Appleby, Andrew (Research Co-investigator)
Period 01-Jan-2015 - 01-Jan-2019

more projects


Design, Manufacture and Engineering Management
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