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Collaboration between the University of Southampton and scientists at GlaxoSmithKline (GSK) has resulted in the adoption of new statistical design of experiments and modelling methods for the confirmation of a robust operating region for the industrial production of new drugs. These methods have enabled larger numbers of factors to be investigated simultaneously than previously possible, improving scientific understanding of the chemical processes and producing savings of time, money and effort. Southampton's new methods were used in a key process required for the registration of a new skin cancer drug with the US Food and Drug Administration, where the research enabled the verification of a robust operating region to be completed in a third of the previous time.
BRITEST is a global leader in the development of innovative process solutions for the chemical processing sector with > £500m of value being realized since 2008. Research in Manchester (1997-2000) generated a set of novel tools and methodologies which analyse chemical processes to identify where and how process improvements could be made. BRITEST was established in 2001 as a not-for-profit company to manage the technology transfer and effective deployment of these tools and methodologies into industry. Manchester holds the IP arising from the underpinning research and has granted an exclusive license to BRITEST for use and exploitation of the toolkit.
The petrochemical industry is eager to develop advanced fuels which improve fuel efficiency both for economic and environmental reasons. Statistics plays a crucial role in this costly process. Innovative Bayesian methodology developed by Gilmour was applied at Shell Global Solutions to data from fuel experiments to solve a recurring statistical problem. The usefulness of this approach to the wider petrochemical industry has been recognized by the industry-based Coordinating European Council (CEC) for the Development of Performance Tests for Fuels, Lubricants and other Fluids, who in their statistics manual have included Gilmour's method as an alternative to procedures in the ISO 5725 standard.
The safe operation of ships is a high priority task in order to protect the ship, the personnel, the cargo and the wider environment. Research undertaken by Professor Alexander Korobkin in the School of Mathematics at UEA has led to a methodology for the rational and reliable assessment of the structural integrity and thus safety of ships and their cargos in severe sea conditions. Central to this impact is a set of mathematical models, the conditions of their use, and the links between them, which were designed to improve the quality of shipping and enhance the safety of ships. The models, together with the methodology of their use, are utilised by the ship certification industry bringing benefits through recognised quality assurance systems and certification.
Reversible Jump Markov chain Monte Carlo, introduced by Peter Green [1] in 1995, was the first generic technique for conducting the computations necessary for joint Bayesian inference about models and their parameters, and it remains by far the most widely used, 18 years after its introduction. The paper has been (by September 2013) cited over 3800 times in the academic literature, according to Google Scholar, the vast majority of the citing articles being outside statistics and mathematics. This case study, however, focusses on substantive applications outside academic research altogether, in the geophysical sciences, ecology and the environment, agriculture, medicine, social science, commerce and engineering.
The field of conceptual chemical process design as practiced industrially has been influenced significantly by the outputs from the Centre for Process Integration (CPI) at Manchester. Process Integration Ltd (PIL) was spun-out from Manchester and currently employs over 50 staff globally, who have conducted projects that have resulted in annual cost savings of hundreds of millions of US dollars. The application of CPI technology has led to significant reductions in both energy costs and emissions of greenhouse gases. Since 2008 ca. US$350m of savings have been realized through the exploitation of CPI technology with US$1.4m generated from software sales.
RTT (Real Time Tomography) scanning systems for airport baggage are becoming increasingly important due to growing air traffic and greater security concerns. Prior to our research, Rapiscan, a leading producer of baggage scanners, had been unable to make full use of the hardware in their latest generation of scanner prototypes. Our novel theory and image reconstruction algorithms are now a core part of a commercially successful 3D scanner that is significantly faster and more accurate than previous generations. The two models, RTT80 and large RTT110, have been approved by regulatory authorities and have already been field trialled at Manchester Airport and deployed at Seattle airport, with further US$20m orders placed.
The research and impact described herein was flagged in the citation for the UoM's 2013 Queen's Anniversary Prize for Higher and Further Education for its work in imaging techniques to support advanced materials and manufacturing.
Software has been developed by City University London in cooperation with Rolls-Royce that exploits the strengths of Bayesian statistics in improving the design of aircraft engines. The software, `4Cast', allows engineers to elicit design characteristics that in turn allow the design to be modelled relative to reliability targets. The targets are determined by failure rates. This enables better evaluation of design choices and of the risk of faults and failures in engines and supports rapid decisions as to whether a proposed design meets requirements.
By using 4Cast to enumerate reliability, Rolls-Royce has been able to determine confidence in asset management and in project management policies. 4Cast also supports Rolls-Royce's programme to reduce the so-called `Disruption Index', a measure of the cost of supporting an engine.
The software has had a significant impact on the business performance and consequent economic achievement of Rolls-Royce, a global company supporting civil and defence aerospace, marine and energy markets worldwide.
Through a close collaboration with Ford Motor Company, simulation modelling software developed at the University of Southampton has streamlined the design of the car giant's engine production lines, increasing efficiency and delivering significant economic benefits in three key areas. Greater productivity across Ford Europe's assembly operations has generated a significant amount [exact figure removed] in direct cost savings since 2010. Automatic analysis of machine data has resulted in both a 20-fold reduction in development time, saving a large sum per year [exact figure removed], and fewer opportunities for human error that could disrupt the performance of production lines costing a large sum [exact amount removed] each to program.
The WinBUGS software (and now OpenBUGS software), developed initially at Cambridge from 1989-1996 and then further at Imperial from 1996-2007, has made practical MCMC Bayesian methods readily available to applied statisticians and data analysts. The software has been instrumental in facilitating routine Bayesian analysis of a vast range of complex statistical problems covering a wide spectrum of application areas, and over 20 years after its inception, it remains the leading software tool for applied Bayesian analysis among both academic and non-academic communities internationally. WinBUGS had over 30,000 registered users as of 2009 (the software is now open-source and users are no longer required to register) and a Google search on the term `WinBUGS' returns over 205,000 hits (over 42,000 of which are since 2008) with applications as diverse as astrostatistics, solar radiation modelling, fish stock assessments, credit risk assessment, production of disease maps and atlases, drug development and healthcare provider profiling.