Abstract
Abstract Owing to high development and acquisition costs, production systems require very detailed analysis for pre-design specifications, and an adjustment in operating philosophies. Detailed simulation models are one of the most important instruments to achieve this goal; normally the simulator must be custom-built, based on an accurate study of the specific industrial problem. The proposed management and economical analysis uses mathematical meta-models obtained from experimental designs produced by the simulator; today the detail level and precision required is very high, so these kinds of meta-model operate very close to their limit. Here we present a new methodology based on artificial neural networks that produces new types of meta-models which can correctly represent complex industrial systems. In this work we propose an application of this methodology together with a detailed analysis of the model development phase to highlight the potential of this instrument.
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