Gaming the System: An Agent-Based Model of Estimation Strategies and their Effects on System Performance

Author:

Meluso John1,Austin-Breneman Jesse2

Affiliation:

1. Global Design Laboratory, Design Science Program, University of Michigan, Ann Arbor, MI 48109 e-mail:

2. Global Design Laboratory, Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109 e-mail:

Abstract

Parameter estimates in large-scale complex engineered systems (LaCES) affect system evolution, yet can be difficult and expensive to test. Systems engineering uses analytical methods to reduce uncertainty, but a growing body of work from other disciplines indicates that cognitive heuristics also affect decision-making. Results from interviews with expert aerospace practitioners suggest that engineers bias estimation strategies. Practitioners reaffirmed known system features and posited that engineers may bias estimation methods as a negotiation and resource conservation strategy. Specifically, participants reported that some systems engineers “game the system” by biasing requirements to counteract subsystem estimation biases. An agent-based model (ABM) simulation which recreates these characteristics is presented. Model results suggest that system-level estimate accuracy and uncertainty depend on subsystem behavior and are not significantly affected by systems engineers' “gaming” strategy.

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

Reference52 articles.

1. Bloebaum, C. L., and McGowan, A.-M. R., 2012, “The Design of Large-Scale Complex Engineered Systems: Present Challenges and Future Promise,” AIAA Paper No. 2012-5571.10.2514/6.2012-5571

2. A Socio-Technical Perspective on Interdisciplinary Interactions During the Development of Complex Engineered Systems;Procedia Comput. Sci.,2013

3. McGowan, A.-M. R., 2014, “Interdisciplinary Interactions During R & D and Early Design of Large Engineered Systems,” Ph.D. thesis, University of Michigan, Ann Arbor, MI.https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20140004579.pdf

4. Complex Concurrent Engineering and the Design Structure Matrix Method;Concurrent Eng. Res. Appl.,2003

5. Model-Based Approaches to Managing Concurrent Engineering;J. Eng. Des.,1991

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