Complex Engineered Systems Design Verification Based on Assume-Guarantee Reasoning

2016 ◽  
Vol 19 (6) ◽  
pp. 461-476 ◽  
Author(s):  
Hoda Mehrpouyan ◽  
Dimitra Giannakopoulou ◽  
Guillaume Brat ◽  
Irem Y. Tumer ◽  
Chris Hoyle
Keyword(s):  
Systems Design ◽  
Design Verification ◽  
Complex Engineered Systems ◽  
Engineered Systems

Toward a Value-Driven Design Approach for Complex Engineered Systems Using Trade Space Exploration Tools

2014 ◽  
Author(s):  
Simon W. Miller ◽  
Timothy W. Simpson ◽  
Michael A. Yukish ◽  
Gary Stump ◽  
Bryan L. Mesmer ◽  
...  
Keyword(s):  
Data Visualization ◽  
Space Exploration ◽  
Systems Design ◽  
Design Decision ◽  
Value Functions ◽  
Complex Engineered Systems ◽  
A Value ◽  
Trade Offs ◽  
Engineered Systems ◽  
Trade Space Exploration

Design decision-making involves trade-offs between many design variables and attributes, which can be difficult to model and capture in complex engineered systems. To choose the best design, the decision-maker is often required to analyze many different combinations of these variables and attributes and process the information internally. Trade Space Exploration (TSE) tools, including interactive and multi-dimensional data visualization, can be used to aid in this process and provide designers with a means to make better decisions, particularly during the design of complex engineered systems. In this paper, we investigate the use of TSE tools to support decision-makers using a Value-Driven Design (VDD) approach for complex engineered systems. A VDD approach necessitates a rethinking of trade space exploration. In this paper, we investigate the different uses of trade space exploration in a VDD context. We map a traditional TSE process into a value-based trade environment to provide greater decision support to a design team during complex systems design. The research leverages existing TSE paradigms and multi-dimensional data visualization tools to identify optimal designs using a value function for a system. The feasibility of using these TSE tools to help formulate value functions is also explored. A satellite design example is used to demonstrate the differences between a VDD approach to design complex engineered systems and a multi-objective approach to capture the Pareto frontier. Ongoing and future work is also discussed.

Multidisciplinary Design Optimization for Complex Engineered Systems Design: State of the Research and State of the Practice—Report From a National Science Foundation Workshop

2011 ◽  
Author(s):  
Timothy W. Simpson ◽  
Joaquim R. R. A. Martins
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Systems Design ◽  
The State ◽  
Multidisciplinary Design ◽  
Research Center ◽  
Future Research ◽  
Government Agencies ◽  
Complex Engineered Systems ◽  
Engineered Systems

Multidisciplinary design optimization (MDO) has evolved remarkably since its inception 25 years ago. Despite these advances, the design of complex engineered systems remains a challenge, and many large-scale engineering projects are routinely plagued by exorbitant cost overruns and delays. To gain insight into these challenges, 48 people gathered from industry, academia, and government agencies to examine MDO’s current and future role in designing complex engineered systems. This paper summarizes the views of five distinguished speakers on the “state of the research” along with the discussions from an industry panel of representatives from Boeing, Caterpillar, Ford, NASA Glenn Research Center, and United Technologies Research Center on the “state of the practice”. This paper also summarizes the future research topics identified by breakout groups in five key areas: (1) modeling and the design space; (2) metrics, objectives, and requirements; (3) coupling in complex engineered systems; (4) dealing with uncertainty; and (5) people and workflow. Finally, five over-arching themes are offered to advance MDO. First, we need to engage more disciplines outside of engineering and look for opportunities to use MDO outside of its traditional areas. Second, MDO problem formulations must evolve to encompass a wider range of design criteria. Third, we need effective strategies for putting designers “back in the loop” during MDO. Fourth, we need to do a better job of publicizing the successful examples of MDO so that we can improve the “buy in” that is needed to advance MDO in academia, industry, and government agencies. Fifth, we need to better educate our students and practitioners on systems design, optimization, and MDO along with their benefits and drawbacks.

Multidisciplinary Design Optimization for Complex Engineered Systems: Report From a National Science Foundation Workshop

2011 ◽  
Vol 133 (10) ◽  
Author(s):  
Timothy W. Simpson ◽  
Joaquim R. R. A. Martins
Keyword(s):  
Design Optimization ◽  
Systems Engineering ◽  
Multidisciplinary Design Optimization ◽  
Systems Design ◽  
The State ◽  
Multidisciplinary Design ◽  
Research Center ◽  
Government Agencies ◽  
Complex Engineered Systems ◽  
Engineered Systems

Complex engineered systems are typically designed using a systems engineering framework that is showing its limitations. Multidisciplinary design optimization (MDO), which has evolved remarkably since its inception 25 years ago, offers alternatives to complement and enhance the systems engineering approach to help address the challenges inherent in the design of complex engineered systems. To gain insight into these challenges, a one-day workshop was organized that gathered 48 people from industry, academia, and government agencies. The goal was to examine MDO’s current and future role in designing complex engineered systems. This paper summarizes the views of five distinguished speakers on the “state of the research” and discussions from an industry panel comprised of representatives from Boeing, Caterpillar, Ford, NASA Glenn Research Center, and United Technologies Research Center on the “state of the practice.” Future research topics to advance MDO are also identified in five key areas: (1) modeling and the design space, (2) metrics, objectives, and requirements, (3) coupling in complex engineered systems, (4) dealing with uncertainty, and (5) people and workflow. Finally, five overarching themes are offered to advance MDO practice. First, MDO researchers need to engage disciplines outside of engineering and target opportunities outside of their traditional application areas. Second, MDO problem formulations must evolve to encompass a wider range of design criteria. Third, effective strategies are needed to put designers “back in the loop” during MDO. Fourth, the MDO community needs to do a better job of publicizing its successes to improve the “buy in” that is needed to advance MDO in academia, industry, and government agencies. Fifth, students and practitioners need to be better educated on systems design, optimization, and MDO methods and tools along with their benefits and drawbacks.

scholarly journals Forensic Engineering Use Of Fault Tree Analysis

2006 ◽  
Vol 23 (2) ◽  
Author(s):  
Frank H. Johnson ◽  
DeWitt William E.
Keyword(s):  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis ◽  
Complex Engineered Systems ◽  
Track Record ◽  
Forensic Engineering ◽  
Fire And Explosion ◽  
Engineered Systems ◽  
Analytical Tools

Analytical Tools, Like Fault Tree Analysis, Have A Proven Track Record In The Aviation And Nuclear Industries. A Positive Tree Is Used To Insure That A Complex Engineered System Operates Correctly. A Negative Tree (Or Fault Tree) Is Used To Investigate Failures Of Complex Engineered Systems. Boeings Use Of Fault Tree Analysis To Investigate The Apollo Launch Pad Fire In 1967 Brought National Attention To The Technique. The 2002 Edition Of Nfpa 921, Guide For Fire And Explosion Investigations, Contains A New Chapter Entitled Failure Analysis And Analytical Tools. That Chapter Addresses Fault Tree Analysis With Respect To Fire And Explosion Investigation. This Paper Will Review The Fundamentals Of Fault Tree Analysis, List Recent Peer Reviewed Papers About The Forensic Engineering Use Of Fault Tree Analysis, Present A Relevant Forensic Engineering Case Study, And Conclude With The Results Of A Recent University Study On The Subject.

scholarly journals Design of Complex Engineered Systems

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
Christina L. Bloebaum ◽  
Anna-Maria R. McGowan
Keyword(s):  
Complex Engineered Systems ◽  
Engineered Systems

Quantifying the Resilience-Informed Scenario Cost Sum: A Value-Driven Design Approach for Functional Hazard Assessment

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Daniel Hulse ◽  
Christopher Hoyle ◽  
Kai Goebel ◽  
Irem Y. Tumer
Keyword(s):  
Functional Model ◽  
Scoring Function ◽  
Modeling Languages ◽  
Concept Selection ◽  
Complex Engineered Systems ◽  
Propagation Behavior ◽  
Engineered Systems ◽  
Selection Framework ◽  
And Function ◽  
Probability Information

Complex engineered systems can carry risk of high failure consequences, and as a result, resilience—the ability to avoid or quickly recover from faults—is desirable. Ideally, resilience should be designed-in as early in the design process as possible so that designers can best leverage the ability to explore the design space. Toward this end, previous work has developed functional modeling languages which represent the functions which must be performed by a system and function-based fault modeling frameworks have been developed to predict the resulting fault propagation behavior of a given functional model. However, little has been done to formally optimize or compare designs based on these predictions, partially because the effects of these models have not been quantified into an objective function to optimize. The work described herein closes this gap by introducing the resilience-informed scenario cost sum (RISCS), a scoring function which integrates with a fault scenario-based simulation, to enable the optimization and evaluation of functional model resilience. The scoring function accomplishes this by quantifying the expected cost of a design's fault response using probability information, and combining this cost with design and operational costs such that it may be parameterized in terms of designer-specified resilient features. The usefulness and limitations of using this approach in a general optimization and concept selection framework are discussed in general, and demonstrated on a monopropellant system design problem. Using RISCS as an objective for optimization, the algorithm selects the set of resilient features which provides the optimal trade-off between design cost and risk. For concept selection, RISCS is used to judge whether resilient concept variants justify their design costs and make direct comparisons between different model structures.

Evaluation of System Reconfigurability Based on Usable Excess

2014 ◽  
Author(s):  
Jeffrey D. Allen ◽  
Jason D. Watson ◽  
Christopher A. Mattson ◽  
Scott M. Ferguson
Keyword(s):  
Communication Systems ◽  
Assembly Line ◽  
Assembly Lines ◽  
Automated Assembly ◽  
Complex Engineered Systems ◽  
Future Needs ◽  
Key Factor ◽  
Long Time ◽  
Engineered Systems ◽  
Over Time

The challenge of designing complex engineered systems with long service lives can be daunting. As customer needs change over time, such systems must evolve to meet these needs. This paper presents a method for evaluating the reconfigurability of systems to meet future needs. Specifically we show that excess capability is a key factor in evaluating the reconfigurability of a system to a particular need, and that the overall system reconfigurability is a function of the system’s reconfigurability to all future needs combined. There are many examples of complex engineered systems; for example, aircraft, ships, communication systems, spacecraft and automated assembly lines. These systems cost millions of dollars to design and millions to replicate. They often need to stay in service for a long time. However, this is often limited by an inability to adapt to meet future needs. Using an automated assembly line as an example, we show that system reconfigurability can be modeled as a function of usable excess capability.

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