Evaluation of risks in foodgrains supply chain using failure mode effect analysis and fuzzy VIKOR

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rishabh Rathore ◽  
J. J. Thakkar ◽  
J. K. Jha
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supply Chain ◽  
Failure Mode ◽  
Risk Mitigation ◽  
Supply Chain System ◽  
Effect Analysis ◽  
Content Type ◽  
Fuzzy Vikor ◽  
Multiple Attribute

PurposeThis paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.Design/methodology/approachThis paper used failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.FindingsThe findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.Practical implicationsThe outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.Originality/valueSpecifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.

A risk-based integrated decision-making model for green supplier selection

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1229-1252 ◽  
Author(s):  
Morteza Yazdani ◽  
Prasenjit Chatterjee ◽  
Dragan Pamucar ◽  
Manuel Doval Abad
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supplier Selection ◽  
Potential Contribution ◽  
Effect Analysis ◽  
Content Type ◽  
Green Supplier Selection ◽  
Construction Company ◽  
Green Suppliers ◽  
Decision Making Model

Purpose Supply chain (SC) environment is surrounded by risk variables. This issue is regarded as an emerging and strategic problem which must be resolved by SC executives. The ability to measuring green supplier’s performance and affecting risk variables to demonstrating effective suppliers list has a potential contribution to be investigated. This paper aims to develop a decision-making model to assess green suppliers under legislation and risk factors. This leads to fewer disruptions in managing the SC and its impact to further improvement. It also presents research concepts forming a new approach for identification, prediction and understating relationship of supply risk. Design/methodology/approach At primal stage, different risk factors that influence green suppliers’ performance are indicated and their relationship is analyzed using decision-making trial and evaluation laboratory (DEMATEL) method. At the same time, failure mode and effect analysis is used to determine risk rating of each supplier. Finally, the evaluation based on distance from average solution (EDAS) method ranks suppliers and several comparisons and analysis are performed to test the stability of the results. The approaches include comparison to technique for order performance by similarity to ideal solution, multi-attributive border approximation area comparison, Vlse Kriterijumska Optimizacija I Kompromisno Resenje and complex proportional assessment methods, followed by analysis of rank reversal, weight sensitivity analysis and effect of dynamic metrics. Findings A real-time case study on green supplier selection (GSS) problem of a reputed construction company of Spain has been presented to demonstrate the practical aspects of the proposed method. In practice, though organizations are aware of various risks from local and global suppliers, it is difficult to incorporate these risk factors for ranking the suppliers. This real-case application shows the evaluation and incorporation of risk factors into the supplier selection model. Practical implications The proposed multi-criteria decision model quantitatively aids managers in selecting green suppliers considering risk factors. Originality/value A new model has been developed to present a sound mathematical model for solving GSS problems which considers the interaction between the supplier selection risk factors by proposing an integrated analytical approach for selecting green suppliers strategically consisting of DEMATEL, FMEA and EDAS methods.

scholarly journals Reverse logistics risk management: identification, clustering and risk mitigation strategies

2020 ◽  
Vol 58 (7) ◽  
pp. 1449-1474 ◽  
Author(s):  
Hamidreza Panjehfouladgaran ◽  
Stanley Frederick W.T. Lim
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Supply Chain ◽  
Reverse Logistics ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Content Type ◽  
Risk Mitigation Strategies

PurposeReverse logistics (RL), an inseparable aspect of supply chain management, returns used products to recovery processes with the aim of reducing waste generation. Enterprises, however, seem reluctant to apply RL due to various types of risks which are perceived as posing an economic threat to businesses. This paper draws on a synthesis of supply chain and risk management literature to identify and cluster RL risk factors and to recommend risk mitigation strategies for reducing the negative impact of risks on RL implementation.Design/methodology/approachThe authors identify and cluster risk factors in RL by using risk management theory. Experts in RL and supply chain risk management validated the risk factors via a questionnaire. An unsupervised data mining method, self-organising map, is utilised to cluster RL risk factors into homogeneous categories.FindingsA total of 41 risk factors in the context of RL were identified and clustered into three different groups: strategic, tactical and operational. Risk mitigation strategies are recommended to mitigate the RL risk factors by drawing on supply chain risk management approaches.Originality/valueThis paper studies risks in RL and recommends risk management strategies to control and mitigate risk factors to implement RL successfully.

scholarly journals An Empirical Study of Supply Chain Frangibility and Risk Management in Indian Automobile Industry

2021 ◽  
Author(s):  
Arora Ankit ◽  
Rajagopal Rajesh
Keyword(s):  
Risk Factors ◽  
Supply Chain ◽  
Automobile Industry ◽  
Lead Time ◽  
Risk Mitigation ◽  
Transportation Network ◽  
Demand Forecasting ◽  
Bullwhip Effect ◽  
Effect Analysis ◽  
Supply Chain Efficiency

Abstract The automobile sector in India is one the key segment of Indian economy as it contributes to 4% of India’s GDP and 5% of India’s Industrial production. The supply chain of any firm is generally dependent on six driving factors out of which three are functional (information, inventory, and facilities) and 3 are logistic (sourcing, pricing, and transportation). The risk causing factors in supply chains consists of various levels of sub-factors under them. Say for instance, under supply risk, the sub-factors can be poor logistics at supplier end, poor material quality etc., under demand risk, the sub-factors can be inaccurate demand forecasting, fluctuating demand, bullwhip effect, and under logistics risk, the sub-factors can be poor transportation network, shorter lead time, stock outs. Through this study, we observe to find the effect of these factors in the supply chain. We use Failure Mode and Effect Analysis (FMEA) technique to prioritize the various types of risk into zones namely high, medium and low risk factors. Also, we use the Best Worst Method (BWM), a multi-criteria decision-making technique to find out the overall weightings of different risk factors. The combination of these methods can help an organization to prioritize various risk factors and proposing a proper risk mitigation strategy leading to increase in overall supply chain efficiency and responsiveness.

A grey based approach for assessment of risk associated with facility location in global supply chain

2015 ◽  
Vol 5 (3) ◽  
pp. 419-436 ◽  
Author(s):  
Surya Prakash ◽  
Gunjan Soni ◽  
Ajay Pal Singh Rathore
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supply Chain ◽  
Facility Location ◽  
Global Supply Chain ◽  
Final Decision ◽  
Extensive Literature ◽  
Risk Minimization ◽  
Strategic Decisions ◽  
Content Type

Purpose – Facility location decisions are critical and should be taken after strategic evaluations. Globalization and integration of economies make such decisions further complex and risk prone. The purpose of this paper is to identify and assess the risk factors to be considered while taking new facility location decision associated with global supply chain and device the methodology. A grey-based multi-criteria decision-making (MCDM) approach is used for this purpose, which also takes in to account the uncertainty in decision making. Such approach enables final decision to be more real and practical. The paper also highlighted and discussed the criteria on the basis of which the management can select the best suitable site. Design/methodology/approach – The risk factors related to facility location for a global firm are identified. To select the location of a global facility with least risk, grey-based MCDM approach is formulated. This grey-based MCDM is demonstrated using the hypothetical case of an industrial valve manufacturing global firm. The grey approach is used to analyse location alternatives based on various decision criteria for extracting comparative ranking. Findings – The paper presents a tool for strategic and planning level. It helps supply chain managers to identify the risks related to a candidate location. Then it guides the supply chain manager at strategic level to find the least risky location for a manufacturing facility. Practical implications – This paper demonstrates the grey-based MCDM approach for determining less risky location to locate a new manufacturing unit so that practitioners can use this approach for taking other strategic decisions. The supply chain configuration can be decided subsequently which will yield more practical results and the decision taken will be more fruitful for firm. Originality/value – The extensive literature review reveals that there are many models in the literature that addressed the issue of risk minimization in supply chain, but it was also noticed that there are limited number of models that minimize risk in locating a global facility considering the uncertainty of data in decision making. This is the first time that grey-based MCDM approach is formulated and used to find most suitable facility location under risk.

A novel FMEA model based on fuzzy multiple-criteria decision-making methods for risk assessment

2020 ◽  
Vol 33 (5) ◽  
pp. 881-904 ◽  
Author(s):  
Reza Fattahi ◽  
Reza Tavakkoli-Moghaddam ◽  
Mohammad Khalilzadeh ◽  
Nasser Shahsavari-Pour ◽  
Roya Soltani
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Decision Making ◽  
Failure Mode ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Content Type ◽  
Proposed Model ◽  
Priority Weights

PurposeRisk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.Design/methodology/approachIn this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.FindingsTo show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.Originality/valueTo the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.

scholarly journals Modeling Supply Chain Sustainability-Related Risks and Vulnerability: Insights from the Textile Sector of Pakistan

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Muhammad Hashim ◽  
Muhammad Nazam ◽  
Muhammad Zia-ur-Rehman ◽  
Muhammad Abrar ◽  
Sajjad Ahmad Baig ◽  
...  
Keyword(s):  
Risk Factors ◽  
Supply Chain ◽  
Large Scale ◽  
Risk Mitigation ◽  
Sustainable Manufacturing ◽  
Manufacturing Industries ◽  
Sustainable Supply Chain ◽  
Effect Analysis ◽  
Pareto Analysis ◽  
Textile Supply Chain

Abstract Sustainability-related risk and vulnerability management have attained significant attention from academia and industry. Manufacturing industries in developing countries such as Pakistan are under severe economic pressure and striving to boost sustainable supply chain practices for achieving business excellence. In this context, the objectives of the present research are to examine the critical supply chain risks associated with sustainable development goals, namely social, economic, and environmental factors. The failure mode and effect analysis (FMEA) technique is employed for categorizing the risk factors and Pareto analysis for highlighting the more crucial and risky factors. For this purpose, a large-scale survey was carried out in the textile industries of Pakistan to develop a risk mitigation model for sustainability-related risks and vulnerability in a textile supply chain (TSC). It captures the input expressions of experts for risk factors, namely severity (s), occurrence (o), and detection (d) for calculating the risk priority numbers (RPNs) of identified alternatives. The results depict that endogenous environmental risks categorize as the most significant for the textile manufacturing industries, and the interfaces between the various risks associated with sustainability-related are also found very high. This study would be a toolkit for the industrial managers and policy-makers for creating sustainable manufacturing culture on organizational premises.

A multiple-attribute decision-making method based on the mean value of grey number weight optimisation and its application in supply-chain management

2017 ◽  
Vol 7 (2) ◽  
pp. 297-307 ◽  
Author(s):  
Chuanmin Mi ◽  
Lin Xiao ◽  
Sifeng Liu ◽  
Xiaoyan Ruan
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Mean Value ◽  
Decision Makers ◽  
Content Type ◽  
Multiple Attribute ◽  
Subjective Preference ◽  
Weight Value ◽  
The Mean ◽  
Grey Number

Purpose With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues. Design/methodology/approach First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives. Findings This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective. Practical implications This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value. Originality/value Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

Fuzzy risk assessment for electro-optical target tracker

2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Linear Equations ◽  
Mode Analysis ◽  
Failure Behavior ◽  
Membership Functions ◽  
Design And Development ◽  
Effect Analysis ◽  
Content Type ◽  
Criticality Analysis

Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

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