Capturing and communicating risk and uncertainty for NASA’s low-volume high-cost exploration missions have become the subject of intensive research in the past few years. As a result, a variety of quantitative and qualitative methodologies were developed, some of which have been adopted and implemented by various NASA centers in the form of risk management tools, procedures, or guidelines. Most of these methodologies, however, aim at the later stages of the design process or during the operational phase of the mission and therefore, are not applicable to the earlier stages of design. In practice, however, uncertainties in the decisions made during the early stages of design introduce a significant amount of risk to the concepts that are being evaluated. In this paper, we aim to capture and quantify uncertainty and risk due to the lack of knowledge as well as those associated with potential system failures. We present an information exchange tool (X-Change) that enables various subsystem designers to capture, quantify, and communicate the uncertainties due to their lack of knowledge as well as those due to failures that might not be readily available or easily-quantifiable. A key piece in this work is to incorporate risk and uncertainty due to the lack of knowledge during the early design phase, and combining it with the potential failure modes. The challenges we face in accomplishing this goal are: 1) lack of a unified ontology defining risk, uncertainty and failure in order to enable their use on common grounds; 2) difficulty in expressing and capturing risk and uncertainty due to the designers’ lack of knowledge at the early stages of design; 3) difficulty in accounting for potential failure modes and their associated risks at the functional design level, before a form or solution has been determined. In order to address these challenges, this paper first attempts to provide a definition for risk and uncertainty. Then, we present the results of an ongoing effort to develop a risk-based design tool for the concurrent mission design environment at NASA. We propose a framework that enables multiple subsystems to capture and communicate the relevant risk and uncertainty in their decisions. The application of the proposed framework is further elaborated using a satellite design example.

1.
Backman, B., (2000). “Design Innovation and Risk Management: A Structural Designer’s Voyage into Uncertainty,” ICASE Series on Risk-based Design, November 2000.
2.
Choi, K K., (2001), “Advances in Reliability-Based Design Optimization and Probability Analysis - PART II,” ICASE Series on Risk-based Design, December 2001.
3.
Chao, L.P., Tumer, I.Y., Ishii, K., (2004), “Design process error proofing. Engineering peer review lessons from NASA.” ASME Design for Manufacturing Conference/IDETC 2004. Salt Lake City, UT. September 2004.
4.
Chao, L.P., Turner, I.Y., Ishii, K. (2005), “Design process error proofing: Benchmarking of the NASA development cycle.” IEEE Aerospace Conference. Big Sky, MN. March 2005.
5.
Du
X.
and
Chen
W.
, (
2002
). “
Efficient Uncertainty Analysis Methods for Multidisciplinary Robust Design
,”
AIAA Journal
,
40
(
3
),
545
552
, 2002.
6.
Greenfield, M. A. (2000). NASA’s Use of Quantitative Risk Assessment for Safety Upgrades. Proceedings of the IAA Symposium, Rio de Janeiro, Brazil, Univelt, Inc.
7.
Heidt, H., Puig-Suari, Y, Moore, A. S., Nakasuka, S, and Twiggs, R.J. (2000). “CubeSat: A new Generation of Picosatellite for Education and Industry Low-Cost Space Experimentation,” Proceedings of the 14th AIAA/USU Conf. on Small Satellites, Logan, Utah, Paper number SSCOO-V-5.
8.
Mahadevan, S., Smith, L., (2003), “System Risk Assessment and Allocation in Conceptual Design,” NASA/CR, May 2003.
9.
Mehr, F. A., Tumer, I., “A New Approach to Probabilistic Risk Analysis in Concurrent and Distributed Design of Aerospace Systems,” Proceedings of ASME International Design Engineering Technical (DETC), Design Automation Conference (DAC) Long Beach, CA, 2005
10.
Orr, J., “Accord: Secret Weapon for Engineering Professionals,” Engineering Automation Report, January 2001.
11.
Stone
R. B.
,
Tumer
I. Y.
,
VanWie
M.
The function-failure design method
.”
Journal of Mechanical Design
, Vol.
127
(
3
), pp.
397
407
,
2005
.
12.
Ullman
D.
, “
What to do Next: Letting the Problem Status Determine the Course of Action
,”
Research in Engineering Design
,
1997
(
9
), p.
214
227
.
13.
Zang, T.A., Michael J. Hemsch, Mark W. Hilburger, Sean P. Kenny, James M. Luckring, Peiman Maghami, Sharon L. Padula, W. Jefferson Stroud, (2002), “Needs and Opportunities for Risk-Based Multidisciplinary Design Technologies for Vehicles,” NASA TM, July 2002.
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