ASQ - Electronics and Communications Division

Developmental Space-System Elicitation Techniques for Risk-Informed Design Practices

Abstract: 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must first be obtained from the IEEE.

The environment designers must conquer to realize crewed space-exploration initiatives presents a heavily mass constrained design space coupled with immense consequences given hardware failures. The balance of these two highly dependent design elements throughout the design process requires insights provided through reliability and risk assessments at early stages of system concept development. If reliability impacts are not analyzed, designers often apply too much redundancy to ensure crew safety or apply too little redundancy or failure mitigation hardware to ensure they meet mass requirements imposed by mission designers.

Understanding what the addition of mass to a design is buying you, from a performance as well as reliability perspective, can ensure design trades are being made with a risk-informed perspective. The technique discussed in this paper conveys a method of risk-informed design that is guided by system design documents and based heavily on face-to-face designer interaction and elicitation. This approach proved very efficient, as designers were closely engaged early in design cycles and forced to focus on reliability strategies that were heavily influenced and implemented by the designer’s own expertise. The application of this method of risk-informed design was performed in support of the NASA Lunar Surface System Project Office to design a lunar campaign of missions to buildup a lunar outpost. Working to design habitation, mobility, power, and communications systems to optimally achieve mission objectives while also conforming to mission constraints requires a balance of mass, performance, and reliability metrics. Rapid iteration and reliance on face-to face interaction with designers is essential to quickly explore the massive design space. The main reliability risk issues/driving issues for these systems and how they construct the base and overall campaign can be tailored to mitigate these risks for both elements relative to mass/performance and for the campaign, which will assess the synergistic effects improving one elements reliability will have on achieving overarching objectives. The conceptual nature of many of the elements included in these preliminary designs requires an adaptive analysis approach that can draw from multiple techniques to assess element reliabilities or hazards.

Following preliminary data gathering, the application of a Monte Carlo simulation to assess high-level designs provides sensitivity analyses on ranges of inputs. These sensitivity analyses help the designers formalize design concepts and develop an intuitive feel for reliability impacts. In this way, designers are adopting a proactive approach towards mitigating risks, rather than merely assessing the risk of their design post-creation. The elicitation technique for building an accurate and useful lunar surface risk model includes gathering data from designers on the system structure, planned use, sparing configuration, and maintenance strategy. Most vital for developing a strong understanding of risk-informed design is the cost/benefit trade for how sparing configurations and maintenance strategies can affect reliability. This process engages the designers as an integral part of the risk model through brief inputs with quick iterations. With so many surface systems and campaign scenarios, data can quickly become too complicated to use. Therefore, data must be collected at the available level (i.e. one element system) and simplified to allow trade studies to be performed on a more holistic level (i.e. one campaign).

Keywords: RAMS 2010 Proceedings - Risk Assessment - Failure Analysis - Monte Carlo Analysis

Already a member? Access this Content

You will need Adobe Reader to view this PDF document.
Download the free Reader from Adobe

  • Print this page
  • Save this page

Average Rating

Rating

Out of 0 Ratings
Rate this item

View comments
Add comments
Comments FAQ

ASQ News

 

RAMS 2019