Professor Jonathan Corney

Design, Manufacturing and Engineering Management

Publications

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)
https://doi.org/10.1007/s12289-019-01507-1
A pilot study : A statistical analysis for the crowdsourced design evaluation results based on the cDesign framework
Wu Hao, Corney Jonathan, Gan Jing
Proceedings of the 2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design, CSCWD 2019 23rd IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2019, pp. 295-300 (2019)
https://doi.org/10.1109/CSCWD.2019.8791874
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)
https://doi.org/10.1080/09537287.2018.1471750
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)
https://doi.org/10.1007/s12289-018-1446-z

more publications

Research interests

Geometric Reasoning for Design and Manufacture, Advanced Materials

Professional activities

Mechanical Engineering Department, University of Edinburgh (External organisation)
Advisor
1/10/2010
CAD conferences
Keynote/plenary speaker
6/2010
Coordinationg Design aspects of WeirSPM pump redesign project
Advisor
1/3/2010
EPSRC (Journal)
Peer reviewer
2010
Joint Conference on Geometric and Physical Modelling
Chair
9/10/2009
West of Scotland KTP advisory board (External organisation)
Member
6/2008

more professional activities

Projects

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)
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
INDUSTRIAL DOCTORATE CENTRE IN ADVANCED FORMING AND MANUFACTURE | Rae, William
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
Enabling Design Re-use through Predictive CAD
Corney, Jonathan (Principal 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 novel user interface proposed can be best understood in term of an analogy 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 can be regarded as an example of big data being 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-2015 - 31-Jan-2017

more projects

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Design, Manufacturing and Engineering Management
James Weir Building

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