skip to content

Timetable (OFB010)

DAE Industry Day

Wednesday 30th November 2011

Wednesday 30th November 2011
10:00 to 11:00 Registration and coffee
11:00 to 12:00 T Davis
Dimensional Analysis in Experimental Design
In this talk, and since we are in the Isaac Newton Institute, I will focus on using the physics of the problem being tackled to determine a strategy to design an experiment to fit a model for prediction. At the heart of the approach is an application of Edgar Buckingham’s 1914 “Pi” theorem. Buckingham’s result, which is based on dimensional analysis, has been seemingly neglected by statisticians, but it provides a “bridge” between a purely theoretical approach to model building, and an empirical one based on e.g. polynomial approximations such as 2nd order response surfaces. I will illustrate the ideas with a few examples, in the hope that I can show that dimensional analysis should take its place at the heart of experimental design in engineering applications.
12:00 to 12:30 DoE in the Automotive Industry - Approaching the Limits of Current Methods?
The presentation outlines the main applications of DoE in the field of automotive engine development and calibration. DoE has been applied to engine calibration (optimising the settings of electronically-controlled engine parameters for low emissions and fuel consumption) for many years. The task has become significantly more complex in recent years due to the various new fuel injection technologies, and up to ten variables must be calibrated at each and every engine speed and load. Many engine responses are non-linear and there are considerable interactions between control variables so the conservative approach of separate DoEs at multiple speed-load conditions still predominates. Polynomials are adequate for such "local" models with narrow variable ranges and six or fewer variables. But over wider ranges or when speed and load are included (so-called "global" models) responses are highly non-linear and polynomials are unsuitable. Some practitioners use radial basis functions, neural networks or stochastic process models but such methods do not always yield the requisite accuracy for "global" models. Furthermore, the most reliable of these techniques, stochastic process models, are limited by computational considerations when datasets are large. The overview of the current "state of the art" methods is presented with the aim of stimulating discussion on what mathematical methods could form the basis of future DoE tools for the automotive industry.
12:30 to 14:00 Lunch
14:00 to 14:30 From ideas to implementation
At GlaxoSmithKline we use sequential experimental design to generate the process understanding that identifies critical process parameters and safe operating conditions for the manufacture of active pharmaceutical ingredients used in medicines. We are always looking for more efficient and effective experimental strategies and ways of managing uncertainty. At a recent conference, Stuart Hunter observed that "within the last ten years there has been some spectacular progress in the field of experimental design - the arena has completely changed". We want to show the decision-making progress around how much, and when to invest in experimental designs, what are the benefits, what risks are faced and are these acceptable? We will discuss how we have taken learnings from a couple of recently published papers on Supersaturated Designs and Definitive Designs and show how we have implemented these ideas to add value within GlaxoSmithKline References Marley, C. J. and Woods, D. C. (2010), "A comparison of design and model selection methods for supersaturated experiments," Computational Statistics and Data Analysis, 54, 3158-3167. A Class of Three-Level Designs for Definitive Screening in the Presence of Second-Order Effects Brad Jones, SAS Institute, Christopher J. Nachsteim Journal of Quality Technology Vol. 43, No. 1, January 2011
14:30 to 15:00 Mixture of Mixture Designs: Optimisation of Laundry Formulations INI 1
15:00 to 15:30 Experimental design challenges in fuel & lubricant R & D INI 1
15:30 to 16:30 Tea and breakout session
16:30 to 17:30 Industry Day Panel Discussion INI 1
17:30 to 19:00 Wine Reception
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons