Professor John Quigley from the Department of Management Science is co-investigator on a successful three year EPSRC grant application worth £1.2 million, in collaboration with the universities of Edinburgh and Napier as well as being supported by industrial partners Babcock, Simul8 and Ubisense. The aim of the project is to use data to optimise industrial operations, identify opportunities for improvements in efficiency, productivity and sustainability.
The rapid advance of digital sensing technologies is making the real time recording of activities in a manufacturing environment both practical and affordable. However, the availability of diverse, real time data about movement and activity does not automatically help engineers manage the complex, dynamic environments typical of modern industrial operations. To do this they need tools that support their interpretation of constantly changing data in ways that enhance productivity and sustainability. In other words, the research challenge posed by digital manufacturing is not the capture of data, but rather the lack of computational methods to analyse large flows of diverse (i.e. multimodal) sensor data and recognise the patterns that allow engineers to assess the current state of the shop floor, understand the impact of past events and predict the consequences of incidents on a range measures.
Motivated by this need, this project will investigate if the forms of probabilistic networks that have been employed to generate computational models from location tracking data in other contexts (eg vehicle movements in traffic models and the daily routines of individuals in domestic environments) can be extended to work with multiple forms of industrial activity data recorded on a factory floor. Such a model would allow diverse signals of manufacturing activity (eg material transport, staff movement, vibration, electrical current and air quality etc) to be used to infer the behaviour of an industrial workplace and generate quantitative measures that support decisions which impact on a sites’ production and sustainability performance.
The research will be led by Jonathan Corney, Professor of Digital Manufacturing at Edinburgh University and includes Professor Andrew Sherlock (Edinburgh University) and Dr Gokula Vasantha (Napier University). Together with Professor Quigley, they form a team with expertise in probabilistic networks, pattern recognition and industrial manufacturing systems.
The research will be supported by three industrial partners. Babcock International is a UK based Multinational Corporation that specialises in managing complex assets and providing complex engineering services. They will contribute access to areas of Babcock Rosyth (one of the largest waterside manufacturing and repair facilities in the UK) to provide a test bed for assessment and validation of the project’s results. Simul8 are leading suppliers of a Discrete Event Simulation system used to model assembly lines or material flows around a factory. Ubisense is UK based SME whose uses sensors to track the precise location, movement and interaction of things.