Abstract
Quality function deployment (QFD) is a planning tool and organizes data in a logical and systematic way, but it is a rather a qualitative method. The union of QFD with quantitative methods will yield even greater benefits from its applications. Fuzzy logic takes linguistic variables as its input, and outputs either crisp or fuzzy numbers, providing a more quantitative method in determining the relationship matrix in QFD. The Taguchi method has been proposed to help benchmark in the House of Quality: QFD identifies the direction of improvement for certain design parameters, but cannot give exact figures for improvements. A machine learning approach, using artificial neural networks (ANNs), has been suggested to deal with the large amounts of input data.
Original language | English |
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Pages (from-to) | 249-254 |
Number of pages | 6 |
Journal | Manufacturing Engineer |
Volume | 78 |
Issue number | 6 |
DOIs | |
Publication status | Published - Dec 1999 |