A Framework for Building Dimensionless Behavioral Models to Aid in Function-Based Failure Propagation Analysis

Coatanéa, Éric; Nonsiri, Sarayut; Ritola, Tuomas; Tumer, Irem Y.; Jensen, David C.

doi:10.1115/1.4005230

Cited by 10 publications

(8 citation statements)

References 22 publications

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“…Based on the taxonomy by Tomiyama et al [16], a baseline design concept can be created using procedures (or part of procedures) that either help generate new design solutions like Pahl and Beitz [31], enrich functional and attributive information of design solutions like axiomatic design [32], or manage the design process and represent design knowledge, as for concurrent design [33]. Recent efforts not covered in this review but also structuring the conceptual design process include Concept-Knowledge (C-K) theory [34], function-based failure analysis [35,36], and architecture generation using Bayesian network [37,38]. The outcome of this phase is a set of baseline concepts that represent the starting point for further analysis.…”

Section: Phase 1: Baseline Designmentioning

confidence: 99%

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Enabling Flexibility in Engineering Systems: A Taxonomy of Procedures and a Design Framework

Cardin

2013

Journal of Mechanical Design

109

106

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This paper presents a five-phase taxonomy of systematic procedures to enable flexibility in the design and management of engineering systems operating under uncertainty. The taxonomy integrates contributions from surveys, individual articles, and books from the literature on engineering design, manufacturing, product development, and real options analysis obtained from professional e-index search engines. Thirty design procedures were classified based on the kind of early conceptual activities they support: baseline design, uncertainty recognition, concept generation, design space exploration, and process management. Each procedure is evaluated based on ease of use to enable flexibility analysis, whether it can be used directly in collaborative design activities, and has a proven applicability record in industry and research. The organizing principles integrate the procedures into a cohesive and systematic design framework. Demonstration applications on engineering systems case studies show that it helps designers select relevant procedures in different phases of the design process, depending on the context, available analytical resources, and objectives. In turn, the case studies show that the design framework helps generate concepts with improved lifecycle performance compared to baseline concepts. The taxonomy provides guidance to organize ongoing research efforts, and highlights potential contribution areas in this field of engineering design research.

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Section: Phase 1: Baseline Designmentioning

confidence: 99%

“…The outcome of this phase is a set of baseline concepts that represent the starting point for further analysis. Such concepts may or may not have been generated considering uncertainty explicitly, unless using recently proposed methods [35][36][37][38].…”

Section: Phase 1: Baseline Designmentioning

confidence: 99%

Enabling Flexibility in Engineering Systems: A Taxonomy of Procedures and a Design Framework

Cardin

2013

Journal of Mechanical Design

109

106

View full text Add to dashboard Cite

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“…To overcome this restriction and to enable the designer to consider multiple function failures effect, the Function Failure Identification and Propagation (FFIP) method was presented [38][39][40][41][42][43][44][45][46][47]. The FFIP method identifies failure propagation paths by defining states of function health.…”

Section: Failure Analysismentioning

confidence: 99%

Failure Analysis in Conceptual Phase toward a Robust Design: Case Study in Monopropellant Propulsion System

Keshavarzi

Goebel

Tumer

et al. 2018

IJRE

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As a system becomes more complex, the uncertainty in the operating conditions increases. In such a system, implementing a precise failure analysis in early design stage is vital. However, there is a lack of applicable methodology that shows how to implement failure analysis in the early design phase to achieve a robust design. The main purpose of this paper is to present a framework to design a complex engineered system resistant against various factors that may cause failures, when design process is in the conceptual phase and information about detailed system and component is unavailable. Within this framework, we generate a population of feasible designs from a seed functional model, and simulate and classified failure scenarios. We also develop a design selection function to compare robust score for candidate designs, and produce a preference ranking. We implement the proposed method on the design of an aerospace monopropellant propulsion system.

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“…To overcome this restriction and to enable the designer to investigate the effects of multiple function failures, the Function Failure Identification and Propagation (FFIP) method was developed [38][39][40][41][42][43][44][45][46][47]. The FFIP method identifies failure propagation paths by mapping component failure states to function health.…”

Section: Failure Analysis and Functional Modelsmentioning

confidence: 99%

Resilient System Design Using Cost-Risk Analysis With Functional Models

Keshavarzi

McIntire

Goebel

et al. 2017

Volume 2A: 43rd Design Automation Conference

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This paper presents a framework to compare the resiliency of different designs during the conceptual design, when information about implementation details is unavailable. We apply the Inherent Behavioral Functional Model (IBFM) tool to develop an initial functional model for a system and simulate the failure behavior. The simulated failure scenarios provide us the information on the unique failure propagation paths and the end state/final behavior of the system assigned to each failure. Each failure path is caused by injecting one or multiple simultaneous faults into the functional model. Within this framework, we generate a population of functional models from a baseline seed model, and evaluate its potential failure scenarios. We also develop a cost-risk model to compare resiliency of different designs, and produce a preference ranking. select the most resilient one, based upon the cost-risk objective. The risk is calculated based on the probability of having an undesired end state for each design, and a consequential cost is assigned to each failure to quantify the cost-risk for a given design. In this paper, we implement and demonstrate the proposed method on the design of a resilient mono-propellant system.

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A Framework for Building Dimensionless Behavioral Models to Aid in Function-Based Failure Propagation Analysis

Cited by 10 publications

References 22 publications

Enabling Flexibility in Engineering Systems: A Taxonomy of Procedures and a Design Framework

Enabling Flexibility in Engineering Systems: A Taxonomy of Procedures and a Design Framework

Failure Analysis in Conceptual Phase toward a Robust Design: Case Study in Monopropellant Propulsion System

Resilient System Design Using Cost-Risk Analysis With Functional Models

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