Design optimization for resilience for risk-averse firms

Giahi, Ramin; MacKenzie, Cameron A.; Hu, Chao

doi:10.1016/j.cie.2019.106122

Cited by 17 publications

(8 citation statements)

References 62 publications

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“…From an engineering perspective, quantifying resilience typically involves measuring the performance of an engineered system over time with a particular focus on the system performance during and after the disruptive event [3,5,32]. Several different approaches have been taken to quantify resilient behavior in this context, including assessing resilience as a time-dependent measure of the ratio of restored performance to total lost performance [33,34], and assessing uncertainty by modeling multiple possible performance trajectories [35][36][37][38]. Network resilience has also been explored in the context of understanding interdependencies among infrastructure components, in order to measure loss of functionality following a disruption and/or the time until the entire network recovers [34,39].…”

Section: Measuring Resiliencementioning

confidence: 99%

Establishing a frame of reference for measuring disaster resilience

Zobel

MacKenzie

Baghersad

et al. 2021

Decision Support Systems

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Due to the increasing occurrence of disruptions across our global society, it has become critically important to understand the resilience of different socio-economic systems, i.e., to what extent those systems exhibit the ability both to resist a disruption and to recover from one once it occurs. In order to characterize this ability, however, one must be able to quantitatively measure the relative level of resilience that a given system displays in response to a disruptive event. Such a measurement should be easily understandable and straightforward to implement, but it should also utilize a consistent frame of reference so that one can properly compare the relative performance of different systems and assess the relative effectiveness of different resilience investments. With this in mind, this paper presents an improved approach for measuring system resilience that supports better decision making by providing both consistency and flexibility across different contexts. The theoretical basis for the approach is developed first, and then its advantages and limitations are illustrated in the context of several different practical examples.

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Section: Measuring Resiliencementioning

confidence: 99%

Establishing a frame of reference for measuring disaster resilience

Zobel

MacKenzie

Baghersad

et al. 2021

Decision Support Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…Bruneau et al (2003) initially proposed the idea of using the area above such a response curve as a measure of the loss of resilience in a system, or the total loss experienced by the system over time, with a larger area corresponding to a less resilient system. Similar ideas are used to evaluate the resilience of systems across a number of different contexts (Adams, Bekkem, & Toledo-Durán, 2012;Giahi, MacKenzie, & Hu, 2020;Mackenzie & Zobel, 2016;Sahebjamnia, Torabi, & Mansouri, 2015;Thekdi & Santos, 2019). Zobel (2010Zobel ( , 2011Zobel ( , 2014 specifically argues that a single measure for resilience cannot sufficiently capture the tradeoffs between the actual loss of performance due to the impact of a disruption and the subsequent length of time needed for the system to recover.…”

Section: Organizational Resiliencementioning

confidence: 99%

Organizational Resilience to Disruption Risks: Developing Metrics and Testing Effectiveness of Operational Strategies

Baghersad

Zobel

2021

Risk Analysis

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This study draws from the system resilience literature to propose three different metrics for evaluating the resilience performance of organizations against disruptions: the initial loss due to the disruption, the maximum loss, and the total loss over time. In order to show the usefulness of the developed metrics in practice, we deploy these metrics to study the effectiveness of two resilience strategies: maintaining operational slack and broadening operational scope, by empirically analyzing the performance of manufacturing firms that experienced a disruption during the period from 2005 to the end of 2014. The results show that maintaining certain aspects of operational slack and broadening business scope and geographic scope can affect these different metrics in different ways. Our results help decisionmakers in risk management to gain a better understanding of the conditions under which the recommended strategies actually improve organizations’ resilience, as well as the ways in which they may do so.

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“…Further, we did not examine other resilience factors such as, product restoration, which can be added to the proposed model in future works. Giahi et al [29] also revealed that product restoration can be considered as a resilience factor. Since the present study focused on reliability factors, considering other significant factors warrants another research.…”

Section: Limitations and Directions For Future Researchmentioning

confidence: 99%

A hybrid approach to investigate the relationship between design factors and sustainability

et al. 2021

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Factors considered in product design have a significant impact on future cost and sustainability. Some factors such as materials, dimensions, and tolerances are crucial in the design process of many products. At the macro scale, this can give rise to environmental effects and influence the reliability and sustainability of the product. In this research, a hybrid system dynamics simulation-optimization approach has been proposed for tolerance design. In this approach, first, the optimal values of tolerance and price are determined by conjoint analysis. These values are entered into a system dynamics model to evaluate the relationships among sustainability, reliability, and customer satisfaction. Then, the impact of tolerance and other factors of product design on sustainability, reliability, and customer satisfaction are investigated. This approach can help decision-makers better understand the trade-off between design factors, resilience, sustainability, and customer satisfaction and make more informed decisions. The proposed method is illustrated for computer assembly step by step. The results show that lower sustainability and higher customer satisfaction are directly associated with tighter tolerances. Besides, lower sustainability, higher reliability, and higher customer satisfaction are associated with lower quality of materials. The validity of the model was examined using a boundary-adequacy test.

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Design optimization for resilience for risk-averse firms

Cited by 17 publications

References 62 publications

Establishing a frame of reference for measuring disaster resilience

Establishing a frame of reference for measuring disaster resilience

Organizational Resilience to Disruption Risks: Developing Metrics and Testing Effectiveness of Operational Strategies

A hybrid approach to investigate the relationship between design factors and sustainability

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