The School of Mathematics and statistics from the University of Sheffield have collaborated with engineers from the Advanced Manufacturing Research Centre (AMRC) to find solutions allowing for the automatic adjustment of cutting parameters. 
The process first began when the school of mathematics and statistics approached the AMRC in order to find ways of cutting time wastage and increasing cost efficiencies. 
Jeremy Oakley, the Professor of Statistics at the University of Sheffield identified that the main problem manufacturers face when cutting materials such as Titanium is that the batches can change quite regularly, meaning the cutting parameters also need changing, resulting in a costly and timely process. 
The AMRC conducted physical cutting trials on batches of titanium alloys with different properties, and used an orthogonal peripheral climb milling operation to collect data such as temperature, cutting forces and vibration. A finite element (FE) model which replicated the machining process was also used to extract the same data through simulations of the process.
University statisticians used the output data from the cutting trials and FE model to identify robust optimal cutting parameters to use during the manufacturing process, which allow for the uncertainty of the material properties changing between batches.
According to Dr Keith Harris, it is unusual to use this sort of statistical modeling on a project such as this, where you are required to collect data from a variety of different sensors and then integrate them with the predictions of an FE model, something that is difficult to do. 
These tests will also allow the statisticians to identify when the machines need replacing/servicing.  
There is no doubt the introduction of the mathematics and statistics school to the AMRC has reaped rewards. Hateem Laalej, the AMRC project engineer believes that a fully automated machine can be used outside and far beyond just cutting titanium, in order to increase available time and decrease costs. 

The possibilities are endless when you combine the minds of specialists from different industries…

Source: http://www.amrc.co.uk/news/university-of-sheffield-statisticians-and-amrc-engineers-collaborate-to-create-new-autonomous-manufacturing-processes/