DETC98/DAC-5604 Using Robust Design Techniques To Model The Effects Of Multiple Decision Makers In A Design Process

In this paper we introduce a methodology to reduce the effects of uncertainty in the design of a complex engineering system involving multiple decision makers. We focus on the uncertainty that is created when a disciplinary designer or design team must try and predict or model the behavior of other disciplinary subsystems. The design of a complex system is performed by many different designers and teams, each of which only have control over a small portion of the entire system. Modeling the interaction among these decision makers and reducing the uncertainty caused by the lack of global control is the focus of this paper. We use well developed concepts from the field of game theory to describe the interactions taking place, and concepts from robust design to reduce the effects of one decision-maker on another. Response Surface Methodology (RSM) is also used to reduce the complexity of the interaction analysis while preserving behavior of the systems. The design of a passenger aircraft is used to illustrate the approach, and some encouraging results are discussed.

[1]  Jian Su,et al.  Automatic Differentiation in Robust Optimization , 1997 .

[2]  George E. P. Box,et al.  Empirical Model‐Building and Response Surfaces , 1988 .

[3]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[4]  Farrokh Mistree,et al.  A STUDY OF OPTIMAL DESIGN UNDER CONFLICT USING MODELS OF MULTI-PLAYER GAMES , 1997 .

[5]  Kemper Lewis,et al.  Modeling interactions in multidisciplinary design - A game theoretic approach , 1996 .

[6]  Timothy W. Simpson,et al.  On the Use of Statistics in Design and the Implications for Deterministic Computer Experiments , 1997 .

[7]  Louis B. Rall,et al.  Automatic differentiation , 1981 .

[8]  Farrokh Mistree,et al.  THE COMPROMISE DECISION SUPPORT PROBLEM AND THE ADAPTIVE LINEAR PROGRAMMING ALGORITHM , 1998 .

[9]  Farrokh Mistree,et al.  Integration of the Response Surface Methodology with the Compromise Decision Support Problem in Developing a General Robust Design Procedure , 1994 .

[10]  J. R. Jagannatha Rao,et al.  A Study of Concurrent Decision-Making Protocols in the Design of a Metal Cutting Tool Using Monotonicity Arguments 1 , 1994 .

[11]  Kemper Lewis,et al.  Collaborative, sequential, and isolated decisions in design , 1997 .

[12]  Genichi Taguchi System Of Experimental Design: Engineering Methods To Optimize Quality And Minimize Costs , 1987 .

[13]  T. L. Vincent,et al.  Game Theory as a Design Tool , 1983 .

[14]  Donald R. Houser,et al.  A ROBUST OPTIMIZATION PROCEDURE WITH VARIATIONS ON DESIGN VARIABLES AND CONSTRAINTS , 1995 .

[15]  Computer Staff,et al.  The Machine That Changed the World , 1992 .

[16]  Rudi Cartuyvels,et al.  NORMAN/DEBORA: a Powerful CAD-Integrating Automatic Sequencing System Including Advanced DOE/RSM Techniques for Various Engineering Optimization Problems , 1993, DIISM.

[17]  G. Hazelrigg Systems Engineering: An Approach to Information-Based Design , 1996 .

[18]  Singiresu S Rao,et al.  Efficient strategy for the robust optimization of large scale nonlinear design problems , 1994 .

[19]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .