Research Papers

The Impact of Process Architecture on Equilibrium Stability in Distributed Design

[+] Author and Article Information
Erich Devendorf

 Department of Mechanical and Aerospace Engineering, University at Buffalo – SUNY, Buffalo, NY 14260edd4@buffalo.edu

Kemper Lewis

 Department of Mechanical and Aerospace Engineering, University at Buffalo – SUNY, Buffalo, NY 14260kelewis@buffalo.edu

J. Mech. Des 133(10), 101001 (Sep 27, 2011) (12 pages) doi:10.1115/1.4004463 History: Received December 30, 2010; Revised June 17, 2011; Published September 27, 2011; Online September 27, 2011

In distributed design processes, individual design subsystems have local control over design variables and seek to satisfy their own individual objectives, which may also be influenced by some system level objectives. The resulting network of coupled subsystems will either converge to a stable equilibrium or diverge in an unstable manner. In this paper, we study the dependence of system stability on the solution process architecture. The solution process architecture describes how the design subsystems are ordered and can be either sequential, parallel, or a hybrid that incorporates both parallel and sequential elements. In this paper, we demonstrate that the stability of a distributed design system does indeed depend on the solution process architecture chosen, and we create a general process architecture model based on linear systems theory. The model allows the stability of equilibrium solutions to be analyzed for distributed design systems by converting any process architecture into an equivalent parallel representation. Moreover, we show that this approach can accurately predict when the equilibrium is unstable and the system divergent when previous models suggest that the system is convergent.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Nash equilibrium

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Figure 2

Potential process architectures

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Figure 3

Convergence rate—sequential

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Figure 4

Convergence rate—parallel

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Figure 5

Convergent—parallel solution process

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Figure 6

Divergent—nonparallel solution process

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Figure 7

Parallel equivalent conversion flow chart

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Figure 8

Synchronization of subsystems

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Figure 9

Design variable summary

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Figure 10

Divergent model for DV x1




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