Benchmarking the risk assessment in green supply chain using fuzzy approach to FMEA

Risk management in humanitarian supply chain based on FMEA and grey relational analysis

The COVID-19 pandemic has disrupted the humanitarian supply chain management (HSCM) necessary for delivering emergency items during the disaster. The combined effects of climate change and the pandemic uncover the vulnerabilities of humanitarian supply chain operations and highlight the importance of risk management. This study aimed to identify priority risk factors and proposed mitigating risk strategies of a local government that is at the forefront of relief operations. It used Grey Relational Analysis (GRA) method to validate the Failure Mode and Effect Analysis (FMEA) approach in identifying priority issues relating to the supply chain risks. This paper reveals that the results of FMEA and GRA are almost similar.

Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications

The year 2020 can be earmarked as the year of global supply chain disruption owing to the outbreak of the coronavirus (COVID-19). It is however not only because of the pandemic that supply chain risk assessment (SCRA) has become more critical today than it has ever been. With the number of supply chain risks having increased significantly over the last decade, particularly during the last 5 years, there has been a flurry of literature on supply chain risk management (SCRM), illustrating the need for further classification so as to guide researchers to the most promising avenues and opportunities. We therefore conduct a bibliometric and network analysis of SCRA publications to identify research areas and underlying themes, leading to the identification of three major research clusters for which we provide interpretation and guidance for future work. In doing so we focus in particular on the variety of parameters, analytical approaches, and characteristics of multi-criteria decision-making techniques for assessing supply chain risks. This offers an invaluable synthesis of the SCRA literature, providing recommendations for future research opportunities. As such, this paper is a formidable starting point for operations researchers delving into this domain, which is expected to increase significantly also due to the current pandemic.

Barriers to circular economy implementation in designing of sustainable medical waste management systems using a new extended decision-making and FMEA models

The idea of the circular economy (CE) has gained prominence in the policies of the European Union (EU), commerce, and academic studies. Basically, CE is capable of achieving the best value and resolving many of the systemic challenges in the society and commerce of a country, thus leading to sustainable development and preventing irreparable damage to the environment. Medical waste management has proved a daunting challenge with the increase in the global population and the demand for medical services. Fuzzy multi-criteria decision-making approaches try to cover the different and uncertain views of decision-makers (DMs). The present study suggests a novel strategy based on multi-objective optimization using the ratio analysis (MOORA) in the area of spherical fuzzy sets (SFSs) to counterbalance the disadvantages of the failure modes and effects analysis (FMEA) method, such as the lack of weight assignment for risk factors and consideration of uncertainty. In the proposed method, first, the barriers are identified using the FMEA method, and the risk factors are given values. Then, the barriers identified using MOORA are prioritized in the spherical fuzzy (SF) area. The computational procedure of the proposed methodology is established through a case study of the barriers to circular economy implementation in designing sustainable medical waste management systems problems under an SF environment. The proposed approach was compared with IF-MOORA and was found that the results are more reliable using the proposed method, also the ranking in the MOORA method was compared with the TOPSIS method in terms of degree of correlation.

Supply chain risk factor assessment of Indian pharmaceutical industry for performance improvement

Purpose

The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.

Design/methodology/approach

An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.

Findings

The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.

Practical implications

The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.

Originality/value

There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

Risk-based human capital management in the ICT companies in Isfahan: A mixed-method approach

PURPOSE: This study aims to bridge the literature gap and provide a comprehensive and clear vision of managing Human Capital risk through an easy-to-apply risk management methodology. In addition, to provide an integrated process to manage Human Capital risks. METHODOLOGY: This paper conducted a mixed-method approach; risks were gathered by analyzing 14 semi-structured interviews with corporate leaders and HR expertise in 14 ICT companies in Isfahan. In the quantitative phase, variables were assessed by two methods; FMEA and Fuzzy analysis in 14 companies. FINDINGS: Results show that despite realizing the importance of human capital in achieving goals and competitiveness, companies are not ready to mitigate the Human Capital risks. Detected Risks are divided into behavioural and attitudinal risks. The Employees’ demotivation, Leaving work after receiving the required training, and Lack of commitment to the delivery time or quality are the most urgent risks that should be mitigated as prior in the ICT companies in Isfahan. ORIGINALITY: This paper is one of the few studies that holistically dealt with Human Capital risks by providing practical and managerial strategies and recommendations to mitigate the risk exposure. This paper is also one of the leading studies in introducing the FMEA method in measuring this type of risk.

Benchmarking ISO Risk Management Systems to Assess Efficacy and Help Identify Hidden Organizational Risk

The overall aim of this article is to contribute to the further development of the area of benchmarking in risk management. The article introduces a two-step benchmarking model to assess the efficacy of ISO risk management systems. It furthermore aims at verifying its usefulness in terms of finding hidden risk issues and improvement opportunities. The existence of all key elements of an ISO 31000-based risk management system is examined at the beginning of this study. Then, the quality in terms of efficacy of important aspects of the risk management system is examined in more detail with special benchmarks. The application of the model to six ISO-certified organizations follows and reinforces the novelty of this study, which is to combine risk science knowledge with benchmarking theory in the application of ISO risk management standards in organizations. The results show that the benchmarking model developed in this study provides rigor when assessing and evaluating the efficacy of an ISO risk management system. By applying the model, risk issues and risk factors can be found that had not previously been identified. The findings are of importance for risk management, the benchmarking science, and for the development of ISO risk management standards.

Evaluating the impacts of COVID-19 outbreak on supply chain risks by modified failure mode and effects analysis: a case study in an automotive company

Supply chains have been facing many disruptions due to natural and man-made disasters. Recently, the global pandemic caused by COVID-19 outbreak, has severely hit trade and investment worldwide. Companies around the world faced significant disruption in their supply chains. This study aims to explore the impacts of COVID-19 outbreak on supply chain risks (SCRs). Based on a comprehensive literature review on supply chain risk management, 70 risks are identified and listed in 7 categories including demand, supply, logistics, political, manufacturing, financial and information. Then, a modified failure mode and effects analysis (FMEA) is proposed to assess the identified SCRs, which integrates FMEA and best-worst method to provide a double effectiveness. The results demonstrate the efficiency of the proposed method, and according to the main findings, "insufficient information about demand quantities", "shortages on supply markets", "bullwhip effect", "loss of key suppliers", "transportation breakdowns", "suppliers", "on-time delivery", "government restrictions", "suppliers' temporary closure", "market demand change" and "single supply sourcing" are the top 10 SCRs during the COVID-19 outbreak, respectively. Finally, the practical implications are discussed and useful managerial insights are recommended.

Supply chain sustainability risk assessment model using integration of the preference selection index (PSI) and the Shannon entropy

Purpose

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

Design/methodology/approach

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

Findings

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

Research limitations/implications

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

Practical implications

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Originality/value

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

Reverse logistics models for the collection of plastic waste: A literature review

To support the understanding of recycling models applied to plastics, the main objective of this work is to offer a literature review of the different reverse logistics (RL) models for collecting plastic waste (PW). The methodology used for processing the scientific literature was content analysis, using the google scholar search engine. The main keywords used were RL and PW. This article is divided into two parts: the first part discusses the development of circular economy models and RL networks and raises the conceptual framework of the research, and the second part presents mathematical models and exploratory studies, proposed as a solution for RL problems of PW. Articles published between years 2014 and 2019 were reviewed. In total, 102 references were used, 70 of them are part of the literature review. According to our findings, we can state that the most widely used solution method for mathematical modeling is mixed-integer linear programming, and for exploratory studies, it was evaluations. About 93% of studies evaluated raw materials related to PW; only 13% of studies had models with stochastic processes; and 88% of the investigations used continuous variables, being the multiobjective functions one of the most used to provide solutions to RL problems. Regarding the mathematical models, 49% were evaluations, 9% corresponded to multicriteria analysis, 29% to linear and nonlinear programming, and 4% to another type of evaluation or model.

A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry

The growing competitiveness in the automotive industry and the strict standards to which it is subject, require high quality standards. For this, quality tools such as the failure mode and effects analysis (FMEA) are applied to quantify the risk of potential failure modes. However, for qualitative defects with subjectivity and associated uncertainty, and the lack of specialized technicians, it revealed the inefficiency of the visual inspection process, as well as the limitations of the FMEA that is applied to it. The fuzzy set theory allows dealing with the uncertainty and subjectivity of linguistic terms and, together with the expert systems, allows modeling of the knowledge involved in tasks that require human expertise. In response to the limitations of FMEA, a fuzzy FMEA system was proposed. Integrated in the design, measure, analyze, improve and control (DMAIC) cycle, the proposed system allows the representation of expert knowledge and improves the analysis of subjective failures, hardly detected by visual inspection, compared to FMEA. The fuzzy FMEA system was tested in a real case study at an industrial manufacturing unit. The identified potential failure modes were analyzed and a fuzzy risk priority number (RPN) resulted, which was compared with the classic RPN. The main results revealed several differences between both. The main differences between fuzzy FMEA and classical FMEA come from the non-linear relationship between the variables and in the attribution of an RPN classification that assigns linguistic terms to the results, thus allowing a strengthening of the decision-making regarding the mitigation actions of the most “important” failure modes.

Product deletion and supply chain repercussions: risk management using FMEA

Purpose

Product portfolio management is a strategic concern. Product portfolio management includes decisions associated with adding new products, maintaining existing products and deleting or phasing out problematic products. This paper first introduces a framework to identify risks of product deletion along supply chain activities. It utilizes failure mode and effects analysis (FMEA) to identify, analyse and evaluate product deletion risks on supply chains and proposes managerial implications for risk management in dynamic business scenarios. It is meant to build upon and address a gap in the product deletion and supply chain linkage literature.

Design/methodology/approach

FMEA is utilized in this study to structure and manage potential risks in product deletion decision-making on supply chains. FMEA is based on an analysis of severity, occurrence and detectability of failure modes. FMEA provides methods to help identify managerial preventive solutions to avoid and mitigate risk consequences of such decisions.

Findings

Ten top product deletion risks are identified in this study; discussions of their negative impact on supply chain performance, and possible managerial recommendations are followed for risk control, monitor and elimination.

Practical implications

Findings help managers to predict, avoid and mitigate risk consequences of product deletion decisions; especially those related to the supply chain. A framework to structure various risks of product deletion in the supply chain can be useful to both practitioners and researchers.

Originality/value

This study advances product portfolio management through enhanced understanding of product deletion decision-making in organizations; and especially contributes to a broader investigation of such decisions in supply chain management. It also structures the factors that play a role in identifying risks.

Risk management in Halal supply chain: an integrated fuzzy Delphi and DEMATEL approach

Purpose

In a globalised environment, market volatility makes risk management an essential component of the supply chain. Similar to conventional supply chains, a Halal supply chain (HSC) is also affected by several factors making it vulnerable to risks. Therefore, the purpose of this study is to identify and analyse the elements of Halal supply chain management (HSCM) and their significant risk dimensions.

Design/methodology/approach

In total, 72 risk elements of HSCM are identified through a review of contemporary scientific literature along with news items and official websites related to risk management of conventional supply chain management, HSC and sustainable supply chain. Further, 42 risk elements are finalised using fuzzy Delphi and then these risk elements are categorised into 7 dimensions. The interrelationships among the risk dimensions as well as risk elements are developed using fuzzy DEMATEL.

Findings

Results suggest that production, planning, logistic & outsourcing and information technology-related risk are prominent risk dimensions. The causal relationships among the significant risk dimensions and elements related to the HSCM may help managers and policy planners.

Research limitations/implications

This study faces a challenge due to inadequate availability of the literature related to risk management in the area of HSCM. Further, this study has used inputs from experts, which can be biased.

Originality/value

To the best of the author's knowledge, it is the first comprehensive study towards investigating the interrelationships among the risks in the context of the HSCM.

Decision-making for risk evaluation: integration of prospect theory with failure modes and effects analysis (FMEA)

Purpose

The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation.

Design/methodology/approach

Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the prospect-theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their risk priority numbers (RPNs). In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts.

Findings

The results are very much in line with prospect theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm's attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure and operator failure, respectively.

Originality/value

The originality of this paper consists in integrating prospect theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA's RPNs.