Risk-Based Decision-Making for Managing Resources During the Design of Complex Space Exploration Systems

Author:

Farhang Mehr Ali1,Tumer Irem Y.2

Affiliation:

1. QSS Group, NASA Ames Research Center, M/S 269, Moffett Field, CA 94035

2. NASA Ames Research Center, M/S 269, Moffett Field, CA 94035

Abstract

Abstract Complex space exploration systems are often designed in collaborative engineering environments where requirements and design decisions by various subsystem engineers have a great impact on the overall risk of the mission. As a result, the system-level management should allocate risk mitigation resources (e.g., capital to place additional sensors or to improve the current technology) among various risk elements such that the main objectives of the system are achieved as closely as possible. Minimizing risk has been long accepted as one of the major drivers for system-level decisions and particularly resource management. In this context, Risk-Based Decision Making refers to a process that allocates resources in such a way that the expected risk of the overall system is minimized. This paper presents a new risk-based design decision-making method, referred to as Risk and Uncertainty Based Concurrent Integrated Design Methodology or RUBIC Design Methodology for short. The new approach is based on concepts from portfolio optimization theory and continuous resource management, extended to provide a mathematical rigor for risk-based decision-making during the design of complex space exploration systems. The RUBIC design method is based on the idea that a unit of resource, allocated to mitigate a certain risk in the system, contributes to the overall system risk reduction in the following two ways: (1) by mitigating that particular risk; and (2) by impacting other risk elements in the system (i.e., the correlation among various risk elements). RUBIC then provides a probabilistic framework for reducing the expected risk of the final system via optimal allocation of available risk-mitigation resources. The application of the proposed approach is demonstrated using a satellite reaction wheel example.

Publisher

ASME International

Subject

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

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3. Clawson, J. F., and Oberhettinger, D., 2001, “The Lessons Learned Process: An Effective Countermeasure Against Avoidable Risk,” in Annual Reliability and Maintainability Symposium, Philadelphia, PA, United States, pp. 94–97.

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