Methodology for Determining the Final Importance Ratings of Engineering Characteristics in House of Quality Based on BSC

2010 ◽  
Vol 46 (04) ◽  
pp. 177 ◽  
Author(s):  
Yanlai LI
Keyword(s):  
House Of Quality ◽  
Engineering Characteristics ◽  
Importance Ratings

Using Genetic Algorithms to Set Target Values for Engineering Characteristics in the House of Quality

1999 ◽  
Author(s):  
Patricia Brackin ◽  
Jonathan Colton
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Penalty Functions ◽  
Preliminary Design ◽  
Test Results ◽  
House Of Quality ◽  
Design Specifications ◽  
Engineering Characteristics ◽  
Target Values

Abstract As part of a strategy for obtaining preliminary design specifications from the House of Quality, genetic algorithms were used to generate and optimize preliminary design specifications for an automotive case study. This paper describes the House of Quality for the automotive case study. In addition, the genetic algorithm chosen, the genetic coding, the methods used for mutation and reproduction, and the fitness and penalty functions are descrobed. Methods for determining convergence are examined. Finally, test results show that the genetic algorithm produces reasonable preliminary design specifications.

A Novel Web-Based Approach to Quality Function Deployment

2003 ◽  
Author(s):  
Hong-jun Wang ◽  
Xin Chen ◽  
Ping Zhang ◽  
De-tao Zheng ◽  
Jian Sun
Keyword(s):  
Quality Function Deployment ◽  
Relationship Matrix ◽  
Manufacturing Companies ◽  
Customer Requirements ◽  
Web Based ◽  
Quality Function ◽  
Engineering Characteristics ◽  
Novel Approach ◽  
Importance Ratings ◽  
The Relationship

Quality Function Deployment (QFD), as an effective tool for customer-driven product development, has been widely adopted in manufacturing companies for many years. The main difficulties in using QFD lie in capturing the actual needs of customers, and in the conflicting conclusions provided by different experts while establishing the relationship matrix between customer requirements and engineering characteristics. This paper describes a novel approach to applying QFD. Firstly, the customer requirements are captured through Web-based technology. Secondly, the relationship matrix between customer requirements and engineering characteristics is established by handling coordinately fuzzy knowledge. Thirdly, the translation of a customer’s importance ratings into engineering weightings is carried out by fuzzy mapping technology. In order to reduce the complexity of HOQ, the less important customer requirements and engineering characteristics are identified and eliminated from the model by using α-cuts. Finally, an example using a refrigerator illustrates that the proposed approach is both available and practicable.

Using Genetic Algorithms to Set Target Values for Engineering Characteristics in the House of Quality

2002 ◽  
Vol 2 (2) ◽  
pp. 106-114 ◽  
Author(s):  
Patricia Brackin ◽  
Jonathan S. Colton
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Penalty Functions ◽  
Preliminary Design ◽  
Test Results ◽  
House Of Quality ◽  
Design Specifications ◽  
Engineering Characteristics ◽  
Target Values

As part of a strategy for obtaining preliminary design specifications from the House of Quality, genetic algorithms are used to generate and optimize preliminary design specifications for an automotive case study. This paper describes the House of Quality for an automotive case study. In addition, the genetic algorithm chosen, the genetic coding, the methods used for mutation and reproduction, and the fitness and penalty functions are described. Methods for determining convergence are examined. Finally, test results show that the genetic algorithm produces reasonable preliminary design specifications.

Estimating Target Values in Preliminary Design: An Automotive Case Study

1999 ◽  
Author(s):  
Patricia Brackin ◽  
Jonathan Colton
Keyword(s):  
Fuel Economy ◽  
Preliminary Design ◽  
House Of Quality ◽  
Acceleration Time ◽  
Engineering Characteristics ◽  
Target Values ◽  
Percent Difference ◽  
Average Percent Difference

Abstract Estimation modules have been developed for use with the House of Quality. These estimation modules are used to predict the performance of a proposed design based on the values of the Engineering Characteristics. This, paper describes the development of modules for an automotive case study. Specifically, modules for weight, price, acceleration time, and fuel economy are given. Comparison of estimated values to actual values show an average percent difference of less than 10%.

Gender Differences in Importance Ratings in 360 Feedback Surveys

2006 ◽  
Author(s):  
Katherine Roberto ◽  
Celesta Taylor ◽  
Ashleigh Schwab ◽  
Lloyd Lin ◽  
Taylor Paige Drummond ◽  
...  
Keyword(s):  
Gender Differences ◽  
360 Feedback ◽  
Importance Ratings

Importance Ratings: Does Rater Age Make a Difference?

2006 ◽  
Author(s):  
Nathan A. Surley ◽  
Carlina Cinciripini ◽  
Kristin Orsak ◽  
Alison Cooper ◽  
Kristi M. Addington ◽  
...  
Keyword(s):  
Importance Ratings

APPLYING HOUSE OF QUALITY IN MALAY SARONG DESIGN

2015 ◽  
Vol 5 (4) ◽  
pp. 771-772
Author(s):  
Mardziah Md Kamal ◽  
◽  
Yi Wang ◽  
Richard Kennon
Keyword(s):  
House Of Quality
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