Applications of DOE in engineering often deal with large scale and highly complex systems where time and/or space are inevitable components. They may involve models in the form of ordinary differential, differential algebraic or partial differential equations. To some extent, optimal experimental design theory carries over to many dynamic problems in which the underlying design space can be a class of input sequences (time-domain analysis), a range of frequencies (frequency domain), a range of sampling intervals (sampling strategies), or a set of spatial sensor locations. However, the framework commonly adopted by statisticians has to be altered here to take account of factors continuously changing in time and/or space (e.g., temperature, pressure). Synergy of different methodologies opens up new perspectives for dealing with the complex settings to which the classical optimum experimental design methodology is not fit.
The workshop meets the urgent need of cross-fertilization between the engineering areas and DOE experts. Specific domains which constitute its main topics are: input profile design in control engineering, design subject to correlated observations, design for geographical surveys, design of observation networks, ill-posed inverse problems, and decentralized approaches to optimum experimental design.
We plan invited and contributed talks from international speakers, a poster session, as well as a lot of time for informal discussion.