The two authors won for the paper in the 2017 volume of the Journal of Technology having the ‘greatest immediate impact to practitioners’ for their paper ‘Testing for lack of fit in blocked, split-plot, and other multi-stratum designs’.

Peter and Steven collected the award on 4 October at the Fall Technical Conference in West Palm Beach, Florida.

Steven explained more about this research: ‘Many industrial experiments involve studying the effects of several input variables (factors) on one or more responses of interest. The complexity of the models means that it is usually impossible to derive a theoretical model for the data and instead purely empirical models are used.

‘It is important to check these models for lack of fit to the data, so that they can be improved if necessary. Lack of fit is routinely tested for in simply experiments in which the factor combinations are completely randomised to the runs. However, it is increasingly recognised that many industrial experiments involve factors whose levels are difficult to set, which leads naturally to a class of designs known as multistratum designs.

‘This paper, for the first time, develops a method and program to allow experimenters to routinely check for lack of fit of models fitted to data from multistratum designs.’

On his recent success, Steven said: ‘For me, the ideal research project is one which is mathematically interesting and challenging, but which also leads to methods which can be, and are, used in practice.

‘It is an honour to receive an award from ASQ, which represents quality practitioners working on important problems across a range of industries.’