Product Attribute Function Deployment (PAFD) for Decision-Based Conceptual Design

The critical product planning phase, early in the product development cycle, requires a design tool to establish engineering priorities, select the preferred design concept, and set target levels of engineering performance while considering the needs of both the consumer and producer. The quality function deployment (QFD) method was developed as a design process tool to translate customer needs into engineering characteristics; however, limitations have been identified in using the QFD method for product planning. In this paper, a new design tool called product attribute function deployment (PAFD), based on the principles of decision-based design (DBD), is introduced as a decision-theoretic, enterprise-level process tool to guide the conceptual design phase. The PAFD method extends the qualitative matrix principles of QFD while utilizing the quantitative decision-making processes of DBD. The PAFD method is built upon established methods in engineering, marketing, and decision analysis to eliminate the need for the user ratings and rankings of performance, priority, and attribute coupling in the QFD method. The differences between the QFD and the PAFD processes are compared and contrasted, and the conceptual design of an automotive manifold absolute pressure sensor is used as a case study to demonstrate the features and benefits of the PAFD method.

[1]  Alice M. Agogino,et al.  An Intelligent Real Time Design Methodology for Component Selection: An Approach to Managing Uncertainty , 1994 .

[2]  Jeremy J. Michalek,et al.  Linking Marketing and Engineering Product Design Decisions via Analytical Target Cascading , 2005 .

[3]  Larry A. Stauffer,et al.  A Taxonomy for Design Requirements from Corporate Customers , 1999 .

[4]  Jie Cheng,et al.  An Integrated Latent Variable Choice Modeling Approach for Enhancing Product Demand Modeling , 2004 .

[5]  Ibo van de Poel,et al.  Methodological problems in QFD and directions for future development , 2007 .

[6]  H. Li,et al.  Product Design Selection Under Uncertainty and With Competitive Advantage , 2000 .

[7]  Gerald W. Evans,et al.  Fuzzy multicriteria models for quality function deployment , 2000, Eur. J. Oper. Res..

[8]  Brian Everitt,et al.  An Introduction to Latent Variable Models , 1984 .

[9]  Kristin L. Wood,et al.  Development of a Functional Basis for Design , 2000 .

[10]  Hui Dong,et al.  Integrating computational synthesis and decision-based conceptual design , 2004 .

[11]  Biren Prasad,et al.  A concurrent function deployment technique for a workgroup-based engineering design process , 2000 .

[12]  Kenneth A. Small,et al.  Fundamentals of Economic Demand Modeling: Lessons from Travel Demand Analysis , 2005 .

[13]  Susan Carlson Skalak House of Quality , 2002 .

[14]  Xiaoyu Gu,et al.  Decision-Based Collaborative Optimization , 2002 .

[15]  G. Altshuller Creativity as an exact science : the theory of the solution of inventive problems , 1984 .

[16]  Deepak Kumar,et al.  Product Attribute Function Deployment (PAFD) for decision-based conceptual design , 2006 .

[17]  Wei Chen,et al.  Decision Making in Engineering Design , 2006 .

[18]  George A. Hazelrigg,et al.  A Framework for Decision-Based Engineering Design , 1998 .

[19]  George A. Hazelrigg,et al.  The Implications of Arrow’s Impossibility Theorem on Approaches to Optimal Engineering Design , 1996 .

[20]  M. M. Kilgo,et al.  Statistics and Data Analysis: From Elementary to Intermediate , 2001 .

[21]  Ming-Lu Wu,et al.  Quality function deployment: A literature review , 2002, Eur. J. Oper. Res..

[22]  Ruichen Jin,et al.  Analytical Variance-Based Global Sensitivity Analysis in Simulation-Based Design Under Uncertainty , 2005, DAC 2004.

[23]  Kristin L. Wood,et al.  Functional Interdependence and Product Similarity Based on Customer Needs , 1999 .

[24]  Michael A. Mullens,et al.  AN AHP FRAMEWORK FOR PRIORITIZING CUSTOMER REQUIREMENTS IN QFD: AN INDUSTRIALIZED HOUSING APPLICATION , 1994 .

[25]  M. Ben-Akiva,et al.  Discrete choice analysis , 1989 .

[26]  Karl T. Ulrich,et al.  Special Issue on Design and Development: Product Development Decisions: A Review of the Literature , 2001, Manag. Sci..

[27]  Steve Caplin,et al.  Principles Of Design , 2011 .

[28]  Joffre Swait,et al.  Stated Choice Methods: Relaxing the IID assumption – introducing variants of the MNL model , 2000 .

[29]  J. Hauser,et al.  The House of Quality , 1988 .

[30]  Deborah L Thurston,et al.  Transforming the House of Quality to a multiobjective optimization formulation , 1998 .

[31]  George A. Hazelrigg,et al.  Validation of engineering design alternative selection methods , 2003 .

[32]  Gülçin Büyüközkan,et al.  A fuzzy optimization model for QFD planning process using analytic network approach , 2006, Eur. J. Oper. Res..

[33]  Hsing-Pei Kao,et al.  Rating the importance of customer needs in quality function deployment by fuzzy and entropy methods , 1999 .

[34]  David G. Ullman,et al.  The Mechanical Design Process , 1992 .

[35]  David E. Goldberg,et al.  The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .

[36]  John Terninko,et al.  Step by Step Qfd: Customer Driven Product Design , 1997 .

[37]  Peter E. Rossi,et al.  Bayesian Statistics and Marketing , 2005 .

[38]  Linda C. Schmidt,et al.  Viewing Product Development as a Decision Production System , 2002 .

[39]  Peter Hauptmann,et al.  Sensors: Principles and Applications , 1993 .

[40]  S. French,et al.  An Introduction to Latent Variable Models. Monographs on Statistics and Applied Probability , 1985 .

[41]  Wei Chen,et al.  Enhancing Discrete Choice Demand Modeling for Decision-Based Design , 2003 .

[42]  Russell R. Barton,et al.  The Virtual Integrated Design Method , 2003 .

[43]  Peter E. Rossi,et al.  Bayesian Statistics and Marketing: Rossi/Bayesian Statistics and Marketing , 2006 .

[44]  Wei Chen,et al.  An Approach to Decision-Based Design With Discrete Choice Analysis for Demand Modeling , 2003 .

[45]  C Loehlin John,et al.  Latent variable models: an introduction to factor, path, and structural analysis , 1986 .

[46]  Andrew T. Olewnik,et al.  On Validating Engineering Design Decision Support Tools , 2005, Concurr. Eng. Res. Appl..