Risk attitudes in risk-based design: Considering risk attitude using utility theory in risk-based design

Author(s):  
Douglas Van Bossuyt ◽  
Chris Hoyle ◽  
Irem Y. Tumer ◽  
Andy Dong

AbstractEngineering risk methods and tools account for and make decisions about risk using an expected-value approach. Psychological research has shown that stakeholders and decision makers hold domain-specific risk attitudes that often vary between individuals and between enterprises. Moreover, certain companies and industries (e.g., the nuclear power industry and aerospace corporations) are very risk-averse whereas other organizations and industrial sectors (e.g., IDEO, located in the innovation and design sector) are risk tolerant and actually thrive by making risky decisions. Engineering risk methods such as failure modes and effects analysis, fault tree analysis, and others are not equipped to help stakeholders make decisions under risk-tolerant or risk-averse decision-making conditions. This article presents a novel method for translating engineering risk data from the expected-value domain into a risk appetite corrected domain using utility functions derived from the psychometric Engineering Domain-Specific Risk-Taking test results under a single-criterion decision-based design approach. The method is aspirational rather than predictive in nature through the use of a psychometric test rather than lottery methods to generate utility functions. Using this method, decisions can be made based upon risk appetite corrected risk data. We discuss development and application of the method based upon a simplified space mission design in a collaborative design-center environment. The method is shown to change risk-based decisions in certain situations where a risk-averse or risk-tolerant decision maker would likely choose differently than the expected-value approach dictates.

Author(s):  
Douglas Van Bossuyt ◽  
Chris Hoyle ◽  
Irem Y. Tumer ◽  
Andy Dong ◽  
Toni Doolen ◽  
...  

Design projects within large engineering organizations involve numerous uncertainties that can lead to unacceptably high levels of risk. Practicing designers recognize the existence of risk and commonly are aware of events that raise risk levels. However, a disconnect exists between past project performance and current project execution that limits decision-making. This disconnect is primarily due to a lack of quantitative models that can be used for rational decision-making. Methods and tools used to make decisions in risk-informed design generally use an expected value approach. Research in the psychology domain has shown that decision-makers and stakeholders have domain-specific risk attitudes that often have variations between individuals and between companies. Risk methods used in engineering such as Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and others are often ill-equipped to help stakeholders make decisions based upon risk-tolerant or risk-averse decision-making conditions. This paper focuses on the specific issue of helping stakeholders make decisions under risk-tolerant or risk-averse decision-making conditions and presents a novel method of translating engineering risk data from the domain of expected value into a domain corrected for risk attitude. This is done by using risk utility functions derived from the Engineering-Domain-Specific Risk-Taking (E-DOSPERT) test. This method allows decisions to be made based upon data that is risk attitude corrected. Further, the method uses an aspirational measure of risk attitude as opposed to existing lottery methods of generating utility functions that are based upon past performance. An illustrative test case using a simplified space mission designed in a collaborative design center environment is included. The method is shown to change risk-informed decisions in certain situations where a risk-tolerant or risk-averse decision-maker would likely choose differently than the dictates of the expected value approach.


2015 ◽  
Vol 6 ◽  
Author(s):  
Joshua A. Weller ◽  
Andrea Ceschi ◽  
Caleb Randolph

2013 ◽  
Author(s):  
Andreas Wilke ◽  
Amanda Sherman ◽  
Bonnie Curdt ◽  
Sumona Mondal ◽  
Carey Fitzgerald ◽  
...  

2014 ◽  
Vol 8 (3) ◽  
pp. 123-141 ◽  
Author(s):  
Andreas Wilke ◽  
Amanda Sherman ◽  
Bonnie Curdt ◽  
Sumona Mondal ◽  
Carey Fitzgerald ◽  
...  

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Randula L. Hettiarachchi ◽  
Pisut Koomsap ◽  
Panarpa Ardneam

PurposeAn inherent problem on risk priority number (RPN) value duplication of traditional failure modes and effect analysis (FMEA) also exists in two customer-oriented FMEAs. One has no unique value, and another has 1% unique values out of 4,000 possible values. The RPN value duplication has motivated the development of a new customer-oriented FMEA presented in this paper to achieve practically all 4,000 unique values and delivering reliable prioritization.Design/methodology/approachThe drastic improvement is the result of power-law and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). By having all three risk factors in a power-law form, all unique values can be obtained, and by applying VIKOR to these power-law terms, the prioritization is more practical and reliable.FindingsThe proposed VIKOR power law-based customer-oriented FMEA can achieve practically all 4,000 unique values and is tested with two case studies. The results are more logical than the results from the other two customer-oriented FMEAs.Research limitations/implicationsThe evaluation has been done on two case studies for the service sector. Therefore, additional case studies in other industrial sectors will be required to confirm the effectiveness of this new customer-oriented RPN calculation.Originality/valueAchieving all 1,000 unique values could only be done by having experts tabulate all possible combinations for the traditional FMEA. Therefore, achieving all 4,000 unique values will be much more challenging. A customer-oriented FMEA has been developed to achieve practically all 4,000 unique risk priority numbers, and that the prioritization is more practical and reliable. Furthermore, it has a connection to the traditional FMEA, which helps explain the traditional one from a broader perspective.


Author(s):  
Michael Barclift ◽  
Timothy W. Simpson ◽  
Maria Alessandra Nusiner ◽  
Scarlett Miller

Additive manufacturing (AM) provides engineers with nearly unlimited design freedom, but how much do they take advantage of that freedom? The objective is to understand what factors influence a designer’s creativity and performance in Design for Additive Manufacturing (DFAM). Inspired by the popular Marshmallow Challenge, this exploratory study proposes a framework in which participants apply their DFAM skills in sketching, CAD modeling, 3D-Printing, and a part testing task. Risk attitudes are assessed through the Engineering Domain-Specific Risk-Taking (E-DOSPERT) scale, and prior experiences are captured by a self-report skills survey. Multiple regression analysis found that the average novelty of the participant’s ideas, engineering degree program, and risk seeking preference were statistically significant when predicting the performance of their ideas in AM. This study provides a common framework for AM educators to assess students’ understanding and creativity in DFAM, while also identifying student risk attitudes when conducting an engineering design task.


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