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    An integrated approach for enhancing the quality of the product by combining robust design and customer requirements

    , Article Quality and Reliability Engineering International ; Vol. 30, Issue. 8 , 2014 , pp. 1285-1292 ; ISSN: 07488017 Shahriari, H ; Haji, M. J ; Eslamipoor, R ; Sharif University of Technology
    Enhancing the quality of the product has always been one considerable concern of production process management, and this subject gave way to implementing so many methods including robust design. In this paper, robust design utilizes response surface methodology (RSM) considering the mean and variance of the response variable regarding system design, parameter design, and tolerance design. In this paper, customer requirements and robust design are regarded simultaneously to achieve enriched quality. Subsequently, with a non-linear programming, a novel method for integrating RSM and quality function deployment has been proposed to achieve robustness in design. The customer requirements are... 

    An enhanced neural network model for predictive control of granule quality characteristics

    , Article Scientia Iranica ; Volume 18, Issue 3 E , 2011 , Pages 722-730 ; 10263098 (ISSN) Neshat, N ; Mahloojifl, H ; Kazemi, A ; Sharif University of Technology
    An integrated approach is presented for predicting granule particle size using Partial Correlation (PC) analysis and Artificial Neural Networks (ANNs). In this approach, the proposed model is an abstract form from the ANN model, which intends to reduce model complexity via reducing the dimension of the input set and consequently improving the generalization capability of the model. This study involves comparing the capability of the proposed model in predicting granule particle size with those obtained from ANN and Multi Linear Regression models, with respect to some indicators. The numerical results confirm the superiority of the proposed model over the others in the prediction of granule...