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Risk, Resilience and Reliability Analysis for ‎Sustainable Management

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 28919

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Special Issue Editors

Dr. Esmaeil Zarei

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Guest Editor

Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada
Interests: system safety and risk engineering; human factor analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Samuel Yousefi

E-Mail Website
Guest Editor

School of Engineering, University of British Columbia, Okanagan Campus, Kelowna, BC V1V 1V7, Canada
Interests: risk assessment; supply chain management; operations management; decision analytics; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Dr. Mohsen Omidvar

E-Mail Website
Guest Editor

Department of Health, Safety, and Environment Engineering (HSE), Faculty of Health, ‎Safety, Environment, and Environmental medicine (HSEEM), Bushehr University of Medical ‎Sciences, Bushehr, Iran
Interests: process safety; risk management; resilience engineering; human error ‎analysis; deterministic and probabilistic risk analysis; graph theory; bayesian network; multiple-criteria decision-making (MCDM) analysis

Special Issue Information

Dear Colleagues,

Emerging and existing risks and threats pose a substantial future challenge to sustainably management in critical systems (e.g., oil and gas, healthcare, aviation, manufacturing, and the power industry). They may significantly contribute to the deterioration of the degree to which the system maintains long-term service levels while strengthening sustainable development's economic, social, and environmental dimensions. It is expected that sociotechnical systems design and operate in a reliable perspective that can deliver great adaptive, absorptive, and transformative capacities most of the time. Meanwhile, complex systems should pursue sustainability while meeting the operational goals and not compromising economic, environmental, and social objectives. Furthermore, sociotechnical systems working with complex operations represent dynamic complexity, relative ignorance, and intractability, which entail interactive and dependent social elements and organizational and human activities. Hence, investigating the influence of and the relationship between the operational concerns such as risk, reliability, and resilience and strategic concerns such as sustainability is of paramount importance to make a successful decision in a wide range of engineering and social systems now and in the future. However, limited knowledge is available concerning the extent and quality of such interactions and how one can ensure that reliability and resilience, which is vital for sustainability, are maintained over dynamic conditions to achieve a sustainable operation. Under these conditions, most infrastructures should be required to undergo adaptive improvements to become more resilient to potential future typical or extraordinary circumstances.

This Special Issue focuses on developing a collection of original research papers demonstrating the recent development of this research stream, "Risk, Resilience and Reliability Analysis for ‎Sustainable Management", and shed light on the challenges and future directions which the research community should focus on to develop more sustainable solutions in both engineering and social systems now and in the future. We welcome analytical and application-oriented papers dealing with the below topics, but the scope of the Special Issue is not limited to them.

Advances in risk, reliability, resilience (3Rs) analysis methods of sustainable ‎systems;
Risk, uncertainty, and sustainability management challenges in sociotechnical systems; ‎
Sustainability management of sociotechnical systems;
Optimization and sustainable risk management;
Decision and data analytics for risk assessment;
Uncertainty analysis and sustainable operations management;
Risk and reliability analysis of engineering systems in sustainable management;
Probabilistic and deterministic approaches for modeling risk and reliability in ‎sustainable operations;
Artificial intelligence, reliability engineering, and sustainability of critical infrastructure;
Complexity management in the reliable and sustainable systems;
Crisis management in sustainable systems;
Resilience engineering and sustainable systems; ‎
Systems modeling and simulation for resilience engineering;
Multi-disciplinary resilience in sustainable systems;
Occupational and process safety and risk engineering;
Human factor and error modeling in sustainable operations;
Sustainable economic growth concerning accident and loss prevention;
Evaluation of adaptive, absorptive, and transformative capacities of sustainable ‎systems;
Other topics that bridge risk, resilience, and reliability with the sustainability concept.

Dr. Esmaeil Zarei
Dr. Samuel Yousefi
Dr. Mohsen Omidvar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

uncertainty analysis
reliability analysis
resilience engineering
system safety
sustainable management
soft computing
probabilistic and deterministic risk analysis

Published Papers (11 papers)

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Research

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25 pages, 1788 KiB

Open AccessArticle

The Relationship between Distance and Risk Perception in Multi-Tier Supply Chain: The Psychological Typhoon Eye Effect

by Ming-Xing Xu, Shu Li, Li-Lin Rao and Lei Zheng

Sustainability 2023, 15(9), 7507; https://doi.org/10.3390/su15097507 - 04 May 2023

Viewed by 1970

Abstract

Previous research has shown that an individual’s proximity to the epicenter can influence their perception and response to risk. However, this aspect has been largely overlooked in the supply chain risk literature. This paper aims to fill this gap by investigating the impact of distance on the perception and response to supply chain disruption risk. An online survey was conducted with 1055 managers working within the supply chain of ZTE, a Chinese multinational company providing integrated communications and information solutions. The survey aimed to examine how their distance from the disruption epicenter (i.e., ZTE) affected their risk perception and subsequent managerial responses. The findings indicate that those closer to the epicenter perceive a lower risk of disruption compared to those farther away, resulting in a reduced likelihood of taking management action. This phenomenon is referred to as the “psychological typhoon eye” (PTE) effect in supply chain disruption risk. Further analysis revealed that risk information quality mediated the relationship between distance and risk perception, while an individual’s job position level moderated the relationship between risk information quality and disruption risk perception. To mitigate the PTE effect in the multi-tier supply chain, the focal firm must prioritize high-quality information synchronization, extending beyond single-company initiatives. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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15 pages, 329 KiB

Open AccessArticle

Occupational Risk Assessment in Native Rainforest Management (MIAR^forest)—Parameters Definition and Validation

by Killian Lima, Ana C. Meira Castro and João Santos Baptista

Sustainability 2023, 15(8), 6794; https://doi.org/10.3390/su15086794 - 18 Apr 2023

Cited by 1 | Viewed by 796

Abstract

Maintaining native rainforests as a sustainable ecosystem and their resilience to external pressures involves their economic profitability as a natural resource of unique and renewable products. For this purpose, new approaches have been developed and refined. This work seeks to contribute in this direction in the context of occupational safety and health (OSH) by presenting a new method for integrated assessment of risks for rainforests (MIAR^forest). The MIAR^forest is based on the MIAR, a method that has shown promising results in occupational risk assessment in different industrial sectors. Its parameters were discussed and assessed to improve their relevance, wording and risk assessment through the Delphi methodology by a panel of 62 experts in forestry and OSH who responded independently to questionnaires made available through Google Forms. A consensus of over 79% among the experts was reached in two rounds. This result highlights the high objectivity and the low percentage of dubious possible interpretations of the parameters and sub-parameters of this occupational risk assessment method. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

20 pages, 3266 KiB

Open AccessArticle

Flight Training Risk Identification and Assessment Based on the HHM-RFRM Model

by Hong Sun, Fangquan Yang, Peiwen Zhang and Yunxiang Zhao

Sustainability 2023, 15(2), 1693; https://doi.org/10.3390/su15021693 - 16 Jan 2023

Cited by 1 | Viewed by 1915

Abstract

Due to the unavoidable operational risks and insufficient risk management capabilities of beginner pilots in flight training, the challenge of risk control in aviation schools has become increasingly prominent. To ensure the safety of flight training in aviation schools and to reduce costs and increase revenue, the essential prerequisite for improving efficiency is risk management. Therefore, it is necessary to explore risk identification and assessment methods. This paper adopts the holographic modeling (HHM) method and risk filtering, rating and management (RFRM) theory. First, the HHM idea is used to construct a risk identification framework (HHM-PAVE) for flight training. Second, based on the dual criteria, multiple criteria and cloud model (CM) in the RFRM approach, an improved risk assessment matrix-cloud model (IPC-CM) is proposed and combined with the N-K model and Bayes’ theorem to propose a coupled risk scenario hazard measurement model (CR-HM) based on the HHM-RFRM approach in risk assessment. In the assessment process, the impact of risk factors on system stability as well as the uncertainty problem and coupling–risk quantification problem in expert assessment are considered to obtain scientific and objective quantitative assessment results. Finally, the risk identification and assessment experiments were conducted using HHM-RFRM on the flight training. The results show that the method can more accurately identify critical risk factors in a flight training system and provide a new perspective for risk prevention and control. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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27 pages, 1365 KiB

Open AccessArticle

Safety Risks Analysis: Moderating Effect of Risk Level on Mitigation Measures Using PLS-SEM Technique

by Wong Chin Yew, Mal Kong Sia and Own QianYi Janet

Sustainability 2023, 15(2), 1090; https://doi.org/10.3390/su15021090 - 06 Jan 2023

Viewed by 1904

Abstract

The Malaysian construction sector registers higher fatal accidents than the manufacturing sector even though the latter has the highest cases of accidents. There is a need to implement effective safety risk management. The main objective of this study is to explore the moderating effect of risk level of accidents on mitigation measures implemented. For this purpose, the factors causing safety risks and the practical measures taken by contractors to mitigate these risks were identified, in addition to the operationalization of the likelihood and severity of accidents using suitable rating scales. Descriptive analysis shows that a fall-related accident is the most likely and the most severe safety risk at high risk level. Results from multivariate analysis using SmartPLS 4 show that safety risks have a significant positive relationship with mitigation measures, and risk level actually heightens this relationship. As a result, the practical measures implemented on construction sites to mitigate the impacts of accidents may be inadequate unless the moderating effect of risk level is considered during the planning, design, and management of construction safety. Therefore, mitigation measures taken by the contractors must take into account the types of factors causing safety risks, as well as the likelihood and severity of these factors. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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19 pages, 4454 KiB

Open AccessArticle

New Approaches to Project Risk Assessment Utilizing the Monte Carlo Method

by Andrea Senova, Alica Tobisova and Robert Rozenberg

Sustainability 2023, 15(2), 1006; https://doi.org/10.3390/su15021006 - 05 Jan 2023

Cited by 7 | Viewed by 3225

Abstract

An environment of turbulence in the market in recent years and increasing inflation, mainly as a result of the post-COVID period and the ongoing military operation in Ukraine, represents a significant financial risk factor for many companies, which has a negative impact on managerial decisions. A lot of enterprises are forced to look for ways to effectively assess the riskiness of the projects that they would like to implement in the future. The aim of the article is to present a new approach for companies with which to assess the riskiness of projects. The basis of this is the use of the new Crystal Ball software tool and the effective application of the Monte Carlo method. The article deals with the current issues of investment and financial planning, which are the basic pillars for effective management decisions with the goal of sustainability. The article has verified a methodology that allows companies to make effective investment decisions based on assessing the level of risk. For practical application, the Monte Carlo method was chosen, as it uses sensitivity analysis and simulations, which were evaluated for two types of projects. Both simulations were primarily carried out based on a deterministic approach through traditional mathematical models. Subsequently, stochastic modeling was performed using the Crystal Ball software tool. As a result of the sensitivity analysis, two tornado graphs were created, which display risk factors according to the degree of their influence on the criterion value. The output of this article is the presentation of these new approaches for financial decision-making within companies. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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20 pages, 709 KiB

Open AccessArticle

Analyzing Health, Safety, and Environmental Risks of Construction Projects Using the Fuzzy Analytic Hierarchy Process: A Field Study Based on a Project Management Body of Knowledge

by Ahmad Soltanzadeh, Mohsen Mahdinia, Alireza Omidi Oskouei, Ehsan Jafarinia, Esmaeil Zarei and Mohsen Sadeghi-Yarandi

Sustainability 2022, 14(24), 16555; https://doi.org/10.3390/su142416555 - 09 Dec 2022

Cited by 5 | Viewed by 2926

Abstract

Due to their unique nature, construction projects are considered one of the world’s most hazardous and incident-prone industrial sectors. The present study aimed to analyze health, safety and environmental (HSE) risks relating to construction projects based on the project management body of knowledge (PMBOK) and sustainability approach. This study was conducted with the participation of 30 experts, using the semi-quantitative risk assessment technique, in nine areas of the project management’s body of knowledge, based on the fuzzy analytic hierarchy process. Risk, in this study, was estimated using a two-dimensional matrix of incident probability and severity, each of which has four sub-parameters. The HSE risks pertaining to each of the nine areas of PMBOK were identified. After that, the two dimensions of risk, including incident probability and severity, were measured. Thirty-seven risk sources associated with nine areas of the PMBOK were identified. Risk analysis revealed that 20 sources were at an unacceptable risk level, and 17 risks were at a tolerable risk level. Identifying HSE-related risk sources in accordance with the nine areas of PMBOK, and using FAHP to assess the risk of these hazards in construction projects, can lead to a more realistic estimate of risk in construction projects. The presented method in the current study can create a novel perspective in terms of the construction industry’s risk management and assessment. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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22 pages, 2206 KiB

Open AccessArticle

Occupational Risk Assessment for Flight Schools: A 3,4-Quasirung Fuzzy Multi-Criteria Decision Making-Based Approach

by Muhammet Gul and Muhammet Fatih Ak

Sustainability 2022, 14(15), 9373; https://doi.org/10.3390/su14159373 - 31 Jul 2022

Cited by 5 | Viewed by 1707

Abstract

The concept of occupational risk assessment is related to the analysis and prioritization of the hazards arising in a production or service facility and the risks associated with these hazards; risk assessment considers occupational health and safety (OHS). Elimination or reduction to an acceptable level of analyzed risks, which is a systematic and proactive process, is then put into action. Although fuzzy logic-related decision models related to the assessment of these risks have been developed and applied a lot in the literature, there is an opportunity to develop novel occupational risk assessment models depending on the development of new fuzzy logic extensions. The 3,4-quasirung fuzzy set (3,4-QFS) is a new type of fuzzy set theory emerged as an extension of the Pythagorean fuzzy sets and Fermatean fuzzy sets. In this approach, the sum of the cube of the degree of membership and the fourth power of the degree of non-membership must be less than or equal to 1. Since this new approach has a wider space, it can express uncertain information in a more flexible and exhaustive way. This makes this type of fuzzy set applicable in addressing many problems in multi-criteria decision making (MCDM). In this study, an occupational risk assessment approach based on 3,4-quasirung fuzzy MCDM is presented. Within the scope of the study, the hazards pertaining to the flight and ground training, training management, administrative and facilities in a flight school were assessed and prioritized. The results of existing studies were tested, and we considered both Pythagorean and Fermatean fuzzy aggregation operators. In addition, by an innovative sensitivity analysis, the effect of major changes in the weight of each risk parameter on the final priority score and ranking of the hazards was evaluated. The outcomes of this study are beneficial for OHS decision-makers by highlighting the most prioritized hazards causing serious occupational accidents in flights schools as part of aviation industry. The approach can also be suggested and adapted for production and service science environments where their occupational health & safety are highly required. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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19 pages, 2218 KiB

Open AccessArticle

Analysis of Factors Affecting Human Reliability in the Mining Process Design Using Fuzzy Delphi and DEMATEL Methods

by Iraj Mohammadfam, Ali Asghar Khajevandi, Hesam Dehghani, Mohammad Babamiri and Maryam Farhadian

Sustainability 2022, 14(13), 8168; https://doi.org/10.3390/su14138168 - 04 Jul 2022

Cited by 12 | Viewed by 2119

Abstract

Design errors have always been recognized as one of the main factors affecting safety and health management and sustainable development in surface mines. Unfortunately, scant attention is paid to design errors and the factors causing them. Therefore, based on expert opinions, this study aimed to identify, rank, and investigate cause-and-effect relationships among variables influencing human error in surface mine design in Iran. The study variables were identified by reviewing previous literature on “latent human errors” and “design errors.” After specifying effective variables, two rounds of the Fuzzy Delphi study were carried out to reach a consensus among experts. Nineteen variables with an influencing score of 0.7 and higher were screened and given to the experts to be analyzed for cause-and-effect relationships by the fuzzy DEMATEL method. The results of the study revealed that the following variables were the major factors affecting human error as root causes: poor organizational management (0.62), resource allocation (0.30), training level (0.27), and experience (0.25). Moreover, self-confidence (−0.29), fatigue (−0.28), depression (−0.25), and motive (−0.23) were found to be effect (dependent) variables. Our findings can help organizations, particularly surface mines, to opt for effective strategies to control factors affecting design errors and consequently reduce workers’ errors, providing a good basis for achieving sustainable development. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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22 pages, 6891 KiB

Open AccessArticle

Sustainable Food Production: An Intelligent Fault Diagnosis Framework for Analyzing the Risk of Critical Processes

by Hamzeh Soltanali, Mehdi Khojastehpour, José Edmundo de Almeida e Pais and José Torres Farinha

Sustainability 2022, 14(3), 1083; https://doi.org/10.3390/su14031083 - 18 Jan 2022

Cited by 10 | Viewed by 2122

Abstract

Fault diagnosis and prognosis methods are the most useful tools for risk and reliability analysis in food processing systems. Proactive diagnosis techniques such as failure mode and effect analysis (FMEA) are important for detecting all probable failures and facilitating the risk analysis process. However, significant uncertainties exist in the classical-FMEA when it comes to ranking the risk priority numbers (RPNs) of failure modes. Such uncertainties may have an impact on the food sector’s operational safety and maintenance decisions. To address these issues, this research provides a unique FMEA framework for risk analysis within an edible oil purification facility that is based on certain well-known intelligent models. Fuzzy inference systems (FIS), adaptive neuro-fuzzy inference systems (ANFIS), and support vector machine (SVM) models are among those used. The findings of the comparison of the proposed FMEA framework with the classical model revealed that intelligent strategies were more effective in ranking the RPNs of failure modes. Based on the performance criteria, it was discovered that the SVM algorithm classifies the failure modes more accurately and with fewer errors., e.g., RMSE = 7.30 and MAPE = 13.19 with that of other intelligent techniques. Hence, a sensitivity FMEA analysis based on the SVM algorithm was performed to put forward suitable maintenance actions to upgrade the reliability and safety within food processing lines. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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18 pages, 8457 KiB

Open AccessEditor’s ChoiceArticle

A Statistical Framework for Evaluating the Effectiveness of Vegetation Management in Reducing Power Outages Caused during Storms in Distribution Networks

by William O. Taylor, Peter L. Watson, Diego Cerrai and Emmanouil Anagnostou

Sustainability 2022, 14(2), 904; https://doi.org/10.3390/su14020904 - 13 Jan 2022

Cited by 6 | Viewed by 2507

Abstract

This paper develops a statistical framework to analyze the effectiveness of vegetation management at reducing power outages during storms of varying severity levels. The framework was applied on the Eversource Energy distribution grid in Connecticut, USA based on 173 rain and wind events from 2005–2020, including Hurricane Irene, Hurricane Sandy, and Tropical Storm Isaias. The data were binned by storm severity (high/low) and vegetation management levels, where a maximum applicable length of vegetation management for each circuit was determined, and the data were divided into four bins based on the actual length of vegetation management performed divided by the maximum applicable value (0–25%, 25–50%, 50–75%, and 75–100%). Then, weather and overhead line length normalized outage statistics were taken for each group. The statistics were used to determine the effectiveness of vegetation management and its dependence on storm severity. The results demonstrate a higher reduction in damages for lower-severity storms, with a reduction in normalized outages between 45.8% and 63.8%. For high-severity events, there is a large increase in effectiveness between the highest level of vegetation management and the two lower levels, with 75–100% vegetation management leading to a 37.3% reduction in trouble spots. Yet, when evaluating system reliability, it is important to look at all storms combined, and the results of this study provide useful information on total annual trouble spots and allow for analysis of how various vegetation management scenarios would impact trouble spots in the electric grid. This framework can also be used to better understand how more rigorous vegetation management standards (applying ETT) help reduce outages at an individual event level. In future work, a similar framework may be used to evaluate other resilience improvements. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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Review

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28 pages, 1935 KiB

Open AccessReview

Systems Thinking Accident Analysis Models: A Systematic Review for Sustainable Safety Management

by Mahdieh Delikhoon, Esmaeil Zarei, Osiris Valdez Banda, Mohammad Faridan and Ehsanollah Habibi

Sustainability 2022, 14(10), 5869; https://doi.org/10.3390/su14105869 - 12 May 2022

Cited by 10 | Viewed by 5231

Abstract

Accident models are mental models that make it possible to understand the causality of adverse events. This research was conducted based on five major objectives: (i) to systematically review the relevant literature about AcciMap, STAMP, and FRAM models and synthesize the theoretical and experimental findings, as well as the main research flows; (ii) to examine the standalone and hybrid applications for modeling the leading factors of the accident and the behavior of sociotechnical systems; (iii) to highlight the strengths and weaknesses of exploring the research opportunities; (iv) to describe the safety and accident models in terms of safety-I-II-III; and finally, to investigate the impact of the systemic models’ applications in enhancing the system’s sustainability. The systematic models can identify contributory factors, functions, and relationships in different system levels which helps to increase the awareness of systems and enhance the sustainability of safety management. Furthermore, their hybrid extensions can significantly overcome the limitations of these models and provide more reliable information. Applying the safety II and III concepts and their approaches in the system can also progress their safety levels. Finally, the ethical control of sophisticated systems suggests that further research utilizing these methodologies should be conducted to enhance system analysis and safety evaluations. Full article

(This article belongs to the Special Issue Risk, Resilience and Reliability Analysis for ‎Sustainable Management)

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