Abstract
Technical innovation in industry can massively benefit from an investigation strategy which properly combines experiments in the field with experiments on a simulation model of the product or the process. However, a methodological frame-work for the effective integration of the two kinds of investigation is still missing. On the one hand, simulation and lab tests are routinely used together in R&D activities of hi-tech companies, although generally not in the form of statistically designed experiments. On the other hand, design of experiments and computer experiments are sound methodologies for running experiments in physical and numerical settings, respectively, but they have practically disregarded the integration issue so far. This chapter outlines a broad approach to running a sequence of physical and simulation experiments from the viewpoint of incremental system innovation. Although the approach is still qualitative, it introduces all of the elements (system innovation, model calibration, model validation and modification, building of mechanistic models) needed to tackle a new and industrially relevant problem. The approach is demonstrated through its application to the design of an engineering system and the improvement of a production process.
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Romano, D. (2009). Product and Process Innovation by Integrating Physical and Simulation Experiments. In: Erto, P. (eds) Statistics for Innovation. Springer, Milano. https://doi.org/10.1007/978-88-470-0815-1_7
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DOI: https://doi.org/10.1007/978-88-470-0815-1_7
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