Using Hierarchical Probability Models to Evaluate Robust Parameter Design Methods

• Autores: Daniel D. Frey, Xiang Li
• Localización: Journal of quality technology: A quarterly journal of methods applications and related topics, ISSN 0022-4065, Vol. 40, Nº. 1, 2008, págs. 59-77
• Idioma: inglés
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• Resumen

  • A hierarchical probability model is proposed for evaluating the effectiveness of robust parameter design (RPD) models. The model is used to create responses to which alternative robust parameter design methods published in the literature are applied. The approach enables assumptions about RPD, such as effect hierarchy and sparsity, to be quantified and openly expressed. The simulations reveal outcomes that cannot be deduced without computers, demonstrating that model-based assessment of RPD can fill the gap between theoretical conjectures and practical field experience.