| Summary: | In order to contribute to the research and development of adhesives for the footwear industry, this paper aims to develop a model capable to predict and optimise the peel strength from the composition of adhesives. The proposed approach is based on three stages: experimental planning of measurements, analysis of uncertainty propagation and optimisation procedure. Considering the experimental results obtained forTaguchi design points as input/output patterns, an Artificial Neural Network is developed based on supervised evolutionary learning. After, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the structural response of adhesive joint based on global sensitivity analysis is studied. An approach based on the optimal design of adhesive composition to achieve the target of maximum peel strength is proposed. (c) 2015 Taylor & Francis Group, London.
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