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Mathematical Sciences

Improving engine production at Ford

Ford Motor Company has made significant savings with the launch of a tool for automatic analysis and data presentation developed by mathematical science researchers at the University of Southampton.

Research challenge

Southampton’s Operational Research Group has worked with Ford for more than a decade to improve the accuracy of their simulation models and develop tools to automate tasks such as data analysis.

Ford Motor Company has a large number of machines in its production line and each has its own set of data on the duration of breakdowns suffered.

Their latest challenge was to develop a machine breakdown analysis tool that would identify machines that are particularly vulnerable to failure, so that they can reduce future machine failures and reduce the repair time and limit the downtime of these production lines.

Context

Ford Motor Company relies on the development of simulation models to optimise throughput on its production lines, while minimising the use of factory space. These simulation models give the best results when they are accurate. Reworking a simulation model or introducing a new line following an error can cost thousands of pounds.

Our solution

Southampton researchers from Mathematical Sciences needed to pool the available data regarding machine breakdowns at Ford and present it as a simple package: generating information on the downtime recorded for each machine on a complex production line that could be used in the creation of a simulation model.

This three-year project saw them develop the machine breakdown analysis tool that has a user-friendly interface allowing analysts to quickly understand the results – saving time and money. Its simple presentation means data can be analysed in a much shorter time than previously.

This new software tool is the most significant development in the partnership between the University of Southampton and the motor company and has the potential to be applied to other manufacturing companies as well as to healthcare.

What was the impact?

The machine breakdown data has enabled staff at Ford to quickly identify machines that are more likely to fail. They now work with suppliers to reduce machine failures and repair times – which limits the time the production line is out of action. This has led to an increase in the number of jobs each production line can complete in an hour.

The productivity of the simulation team has also increased as they don’t need to spend so long researching each machine on a production line. They can now develop two additional production line simulations per year that tend to be better quality, with reduced human error.

The machine breakdown analysis tool has also been trialled as a way of helping timetable medical procedures.

Car assembly line

Related Staff Member

Southampton’s Operational Research Group has worked with Ford for more than a decade to improve the accuracy of their simulation models and develop tools to automate tasks such as data analysis.

Dr Christine Currie - Lecturer in the Operational Research group

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