Professor Jonathan Corney

Design, Manufacturing and Engineering Management


Process selection methodology for near net shape manufacturing
Marini Daniele, Corney Jonathan R
International Journal of Advanced Manufacturing Technology Vol 106, pp. 1967-1987 (2020)
A state of the art review of hydroforming technology : its applications, research areas, history and future in manufacturing
Bell Colin, Corney Jonathan, Zuelli Nicola, Savings David
International Journal of Material Forming (2019)
Semantic path planning for indoor navigation and household tasks
Sun Nico, Yang Erfu, Corney Jonathan
The 20th Towards Autonomous Robotic Systems Conference (TAROS 2019) (2019)
Improving the efficiency of remanufacture through enhanced pre-processing inspection–a comprehensive study of over 2000 engines at Caterpillar remanufacturing, U.K.
Ridley Sara J, Ijomah W L, Corney J R
Production Planning and Control Vol 30, pp. 259-270 (2019)
Semantic enhanced navigation among movable obstacles in the home environment
Sun Nico, Yang Erfu, Corney Jonathan, Chen Yi, Ma Zeli
UK-RAS19 Conference, pp. 68-71 (2019)
Enabling sheet hydroforming to produce smaller radii on aerospace nickel alloys
Bell Colin, Dixon Caleb, Blood Bob, Corney Jonathan, Savings David, Jump Ellen, Zuelli Nicola
International Journal of Material Forming (2018)

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


Smart pumping for Subsurface Engineering (Prosperity Partnership)
Shipton, Zoe (Principal Investigator) Corney, Jonathan (Co-investigator) Dempster, William (Co-investigator) Perry, Marcus (Co-investigator) Pytharouli, Stella (Co-investigator) Stankovic, Lina (Co-investigator) Stankovic, Vladimir (Co-investigator) Yang, Shangtong (Co-investigator) Fan, Ding (Researcher) Parastatidis, Emmanouil (Researcher) Rizzuto, Francesco (Researcher) Xi, Xun (Researcher)
01-Jan-2018 - 31-Jan-2023
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.
30-Jan-2017 - 29-Jan-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."
01-Jan-2017 - 31-Jan-2020
Rahimi, Salaheddin (Principal Investigator) Corney, Jonathan (Co-investigator) Rae, William (Research Co-investigator)
01-Jan-2015 - 01-Jan-2019
The emergence of business models in the 3D printing industries
D'Adderio, Luciana (Principal Investigator) Corney, Jonathan (Co-investigator)
This RCUK funded project will seek to examine, document and analyse the emergence of business models in the 3d printing industries, drawing on a novel inductive and observational methodology for business model taxonomy developed by the PI.
01-Jan-2015 - 31-Jan-2017
Quantifying patent commercialisation to support engineering design
Wodehouse, Andrew (Principal Investigator) Corney, Jonathan (Co-investigator) MacLachlan, Ross (Co-investigator)
"This project will investigate if crowdsourcing can be used to aggregate the content of disparate, open-data sources across the internet to determine which patents underpin commercial products, and organise and present these according to technical criteria in a visual form appropriate for engineering design.

Patents are frequently used to quantify levels of innovation associated with specific regions or companies. However despite the development of sophisticated data mining tools to support the analysis of over 50 million online patent records, little is known about which patents are actually commercialized and how they are embodied in commercial products. Because of this patent informatics has been inherently limited to the study of the records, rather than the use, of Intellectual Property (IP). This information gap inevitably reduces the accuracy of academic and commercial analysis that use patent data for applications such as innovation research, fore-sighting, and IP portfolio valuations. Furthermore, the presentation of existing data maps is not in a form that is useful for engineering designers when conceptualising and embodying products: it is predominantly text-based (and often deliberately obfuscated) when more visual presentation with exemplars and appropriate technical taxonomic terms would greatly enhance utility when undertaking engineering design development.

Crowdsourcing utilises large networks of open people to compete discrete tasks. Virtual tools are used to co-ordinate the distribution, payment and co-ordination of results, resulting in a labour market that is open 24/7 and a diverse workforce available to perform tasks quickly and cheaply. The distributed network of human workers provide on-line, black-box reasoning capabilities that could far exceed the capabilities of current AI technologies (i.e. genetic algorithms, neural-nets, case-based reasoning) in terms of flexibility and scope.

This project proposes that crowdsourcing can be utilised to access open data sources such as user manuals, product labelling, court proceedings and company web pages to understand which patents are actively used in current products and how they have been embodied. With a more accurate representation of innovation commercialisation, technical metadata (labelling), and utilisation, we envisage patent searches not as a stage-gate check but as a revitalised source of design inspiration. Indeed, if crowdsourcing proves a cheap, scalable way of collating this information and applying appropriate taxonomic and visual engineering information, it could fundamentally alter the early phases of engineering design. To this end, the project will result in a visualization tool that can be used to both guide and inspire design conceptualisation and embodiment."
01-Jan-2015 - 31-Jan-2017

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Design, Manufacturing and Engineering Management
James Weir Building

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