Prioritizing risks with composition of probabilistic preferences and weighting of FMEA criteria for fast decision-making in complex scenarios

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fábio Henrique de Souza ◽  
Luiz Octávio Gavião ◽  
Annibal Parracho Sant'Anna ◽  
Gilson B.A. Lima
Keyword(s):  
Decision Making ◽  
Oil And Gas ◽  
Virus Disease ◽  
Fast Response ◽  
Practical Case ◽  
Weighted Sum ◽  
Effect Analysis ◽  
Content Type ◽  
Prioritization Process ◽  
Project Objectives

PurposeThis study aims to develop a risk prioritization process using failure mode and effect analysis (FMEA) in association with composition of probabilistic preferences (CPP) and weighting the risk analysis criteria. It seeks to develop decision-making considering the fast response necessary to achieve project objectives in complex scenarios, such as the pandemic of COrona VIrus Disease 19 (COVID-19).Design/methodology/approachAfter identifying the risks, the prioritization process was applied to a project in the oil and gas area, in which a focus group assessed these risks. This evaluation took place employing traditional FMEA, FMEA with CPP by axes considering four points of view and FMEA with CPP by weighted sum with the use of a multicriteria method to weight the criteria. These approaches were compared to understand their differences and benefits, with a flow chart being developed, consolidating the procedure.FindingsThe methodologies that showed the greatest benefits were FMEA with CPP by axes PO (progressive-optimistic) and by weighted sum. Essentially, this was mainly related to the interrelationship between risks and to the importance of prioritization.Originality/valueThis procedure can consider company's views on what is critical and the interrelationship between risks. It provides a clear segmentation of what should and should not be prioritized. It was also developed in a practical case, showing a possible alternative to support fast responses in decision-making.

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.

Multi-objective mathematical model based on fuzzy hybrid multi-criteria decision-making and FMEA approach for the risks of oil and gas projects

2020 ◽  
Vol 18 (6) ◽  
pp. 1997-2016
Author(s):  
Mohammad Khalilzadeh ◽  
Rose Balafshan ◽  
Ashkan Hafezalkotob
Keyword(s):  
Decision Making ◽  
Oil And Gas ◽  
Programming Model ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Multi Objective ◽  
Response Strategies ◽  
Fuzzy Environment ◽  
Comprehensive Framework ◽  
Grey Relational

Purpose The purpose of this study is to provide a comprehensive framework for analyzing risk factors in oil and gas projects. Design/methodology/approach This paper consists of several sections. In the first section, 19 common potential risks in the projects of Pars Oil and Gas Company were finalized in six groups using the Lawshe validation method. These factors were identified through previous literature review and interviews with experts. Then, using the “best-worst multi-criteria decision-making” method, the study measured the weights associated with the performance evaluation indicators of each risk. Consequently, failure mode and effects analysis (FMEA) and the grey relational analysis (GRA)-VIKOR mixed method were used to rank and determine the critical risks. Finally, to assign response strategies to each critical risk, a zero-one multi-objective mathematical programming model was proposed and developed Epsilon-constraint method was used to solve it. Findings Given the typical constraints of projects which are time, cost and quality, of the projects that companies are often faced with, this study presents the identified risks of oil and gas projects to the managers of the oil and gas company in accordance with the priority given in the present research and the response to each risk is also suggested to be used by managers based on their organizational circumstances. Originality/value This study aims at qualitative management of cost risks of oil and gas projects (case study of Pars Oil and Gas Company) by combining FMEA, best worst and GRA-VIKOR methods under fuzzy environment and Epsilon constraints. According to studies carried out in previous studies, the simultaneous management of quantitative and qualitative cost of risk of oil and gas projects in Iran has not been carried out and the combination of these methods has also been innovated.

Improving risk evaluation in FMEA with a hybrid multiple criteria decision making method

2015 ◽  
Vol 32 (7) ◽  
pp. 763-782 ◽  
Author(s):  
Hu-Chen Liu ◽  
Jian-Xin You ◽  
Xue-Feng Ding ◽  
Qiang Su
Keyword(s):  
Decision Making ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Analytic Hierarchy ◽  
Effect Analysis ◽  
Maintenance Strategies ◽  
Content Type ◽  
Safety And Reliability ◽  
Hierarchy Process

Purpose – The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes. Design/methodology/approach – A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes. Findings – A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies. Practical implications – The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method. Originality/value – This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

scholarly journals Perceived organizational politics and quitting plans: an examination of the buffering roles of relational and organizational resources

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dirk De Clercq ◽  
Renato Pereira
Keyword(s):  
Decision Making ◽  
Peer Relationships ◽  
Oil And Gas ◽  
Turnover Intentions ◽  
Organizational Leaders ◽  
Environment Change ◽  
Organizational Decision Making ◽  
Content Type ◽  
Decision Making Processes ◽  
Oil And Gas Sector

PurposeThe goal of this research is to examine the link between employees' beliefs that organizational decision-making processes are guided by self-serving behaviors and their own turnover intentions, as well as how this link may be buffered by four distinct resources, two that speak to the nature of peer exchanges (knowledge sharing and relationship informality) and two that capture critical aspects of the organizational environment (change climate and forgiveness climate).Design/methodology/approachQuantitative survey data were collected among 208 employees who work in the oil and gas sector in Mozambique.FindingsThe results indicate that employees' beliefs about dysfunctional political games stimulate their plans to quit. Yet this translation is less likely to occur to the extent that their peer relationships are marked by frequent and informal exchanges and that organizational leaders embrace change and forgiveness.Practical implicationsFor organizations, these findings offer pertinent insights into different circumstances in which decision-related frustrations are less likely to escalate into quitting plans. In particular, such escalation can be avoided to the extent that employees feel supported by the frequency and informal nature of their communication with colleagues, as well as the extent to which organizational leaders encourage change and practice forgiveness.Originality/valueThis study adds to extant research by explicating four unexplored buffers that diminish the risk that frustrations with politicized decision-making translate into enhanced turnover intentions.

Including decision-makers preferences in the cost-deprivation trade-off during disaster interventions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Diehlmann ◽  
Patrick Siegfried Hiemsch ◽  
Marcus Wiens ◽  
Markus Lüttenberg ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Humanitarian Logistics ◽  
Decision Makers ◽  
Weighted Sum ◽  
Trade Off ◽  
Content Type ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
The Cost

Purpose In this contribution, the purpose of this study is to extend the established social cost concept of humanitarian logistics into a preference-based bi-objective approach. The novel concept offers an efficient, robust and transparent way to consider the decision-maker’s preference. In principle, the proposed method applies to any multi-objective decision and is especially suitable for decisions with conflicting objectives and asymmetric impact. Design/methodology/approach The authors bypass the shortcomings of the traditional approach by introducing a normalized weighted sum approach. Within this approach, logistics and deprivation costs are normalized with the help of Nadir and Utopia points. The weighting factor represents the preference of a decision-maker toward emphasizing the reduction of one cost component. The authors apply the approach to a case study for hypothetical water contamination in the city of Berlin, in which authorities select distribution center (DiC) locations to supply water to beneficiaries. Findings The results of the case study highlight that the decisions generated by the approach are more consistent with the decision-makers preferences while enabling higher efficiency gains. Furthermore, it is possible to identify robust solutions, i.e. DiCs opened in each scenario. These locations can be the focal point of interest during disaster preparedness. Moreover, the introduced approach increases the transparency of the decision by highlighting the cost-deprivation trade-off, together with the Pareto-front. Practical implications For practical users, such as disaster control and civil protection authorities, this approach provides a transparent focus on the trade-off of their decision objectives. The case study highlights that it proves to be a powerful concept for multi-objective decisions in the domain of humanitarian logistics and for collaborative decision-making. Originality/value To the best of the knowledge, the present study is the first to include preferences in the cost-deprivation trade-off. Moreover, it highlights the promising option to use a weighted-sum approach to understand the decisions affected by this trade-off better and thereby, increase the transparency and quality of decision-making in disasters.

scholarly journals Predicting performance – a dynamic capability view

2018 ◽  
Vol 38 (11) ◽  
pp. 2192-2213 ◽  
Author(s):  
Marcus F. Hasegan ◽  
Sai Sudhakar Nudurupati ◽  
Stephen J. Childe
Keyword(s):  
Decision Making ◽  
Tacit Knowledge ◽  
Dynamic Capabilities ◽  
Hybrid Approach ◽  
Performance Measurement System ◽  
Decision Making Process ◽  
Effect Analysis ◽  
Content Type ◽  
Cause And Effect ◽  
Cause And Effect Analysis

PurposeProduction planning and resource allocation are ongoing issues that organisations face on a day-to-day basis. The purpose of this paper is to address these issues by developing a dynamic performance measurement system (DPMS) to effectively re-deploy manufacturing resources, thus enhancing the decision-making process in optimising performance output. The study also explores the development of dynamic capabilities through exploitation of the organisational tacit knowledge.Design/methodology/approachThe study was conducted using six-stage action research for developing DPMS with real-time control of independent variables on the production lines to study the impact. The DPMS was developed using a hybrid approach of discrete event simulation and system dynamics by using the historical as well as live data from the action case organisation.FindingsThrough the development of DPMS and by combining the explicit and tacit knowledge, this study demonstrated an understanding of using cause and effect analysis in manufacturing systems to predict performance. Such a DPMS creates agility in decision making and significantly enhances the decision-making process under uncertainty. The research also explored how the resources can be developed and maintained into dynamic capabilities to sustain competitive advantage.Research limitations/implicationsThe present study provides a starting-point for further research in other manufacturing organisations to generalise findings.Originality/valueThe originality of the DPMS model comes from the approach used to build the cause and effect analysis by exploiting the tacit knowledge and making it dynamic by adding modelling capabilities. Originality also comes from the hybrid approach used in developing the DPMS.

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.

scholarly journals What drives inter-organisational knowledge management? The cause and effect analysis using a multi-layer multi-criteria decision-making framework

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hannan Amoozad Mahdiraji ◽  
Moein Beheshti ◽  
Vahid Jafari-Sadeghi ◽  
Alexeis Garcia-Perez
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Literature Review ◽  
Influential Factors ◽  
Extensive Literature ◽  
Sustainable Competitive Advantage ◽  
Effect Analysis ◽  
Content Type ◽  
Expert Opinions ◽  
Managerial Implications

Purpose Knowledge management seeks collaborative practices among organisations to generate technical, adapt and share knowledge to obtain a sustainable competitive advantage in cross-border business activities. This paper aims to disentangle the crucial determinants of knowledge management in inter-organisational arrangements settings. Design/methodology/approach In the first stage, after an in-depth literature review, the main knowledge management drivers are identified. In the second stage, based on the identified drivers, the importance and relationship between the drivers are evaluated by expert opinions from academic and executive activists. Eventually, in the last stage, a multi-layer decision-making approach has been proposed and used to determine the relationship and the importance of the drivers. Findings The findings of this paper assess the ranking of the different elements from experts’ opinions and discuss important theoretical and managerial implications. The influential factors were identified through an extensive literature review, which combined with the views of experts from academia and industry (international firms). Furthermore, the ranking of factors based on the experts’ overall opinion was used to discuss theoretical and managerial contributions. Originality/value This research provides a better understanding of the interrelationships between the key drivers of knowledge management, which helps management draw more effective strategies to address the cultural differences between firms. Moreover, understanding of the importance of the systems and structures that define the nature of the collaboration in inter-organisational settings, as well as the risks related to those are presented in this research.

scholarly journals An integrated grey-based multi-criteria decision-making approach for supplier evaluation and selection in the oil and gas industry

Kybernetes ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 406-441 ◽  
Author(s):  
Mohamad Amin Kaviani ◽  
Amir Karbassi Yazdi ◽  
Lanndon Ocampo ◽  
Simonov Kusi-Sarpong
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supplier Selection ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Supplier Evaluation ◽  
Multi Criteria Decision Making ◽  
Gas Industry ◽  
Content Type ◽  
Delphi Approach

PurposeThe oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.Design/methodology/approachTo address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.FindingsTo exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.Research limitations/implicationsThe proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.Originality/valueThis study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

East African oil ambitions will face challenges

2019 ◽  
Keyword(s):  
Decision Making ◽  
Oil And Gas ◽  
East African ◽  
Content Type ◽  
Left Behind

Subject Outlook for East African oil and gas developments. Significance Governments and industry players are looking to make progress on oil and gas projects, but their schemes still face a range of challenges. Impacts Tullow Oil seeks a partner to share costs and risks in Kenya, but industry players are likely to want more certainty before stepping in. Clarification on which of the region’s pipeline and refinery projects will progress to development would ease decision-making for investors. Regional political tensions will be stoked if Uganda and Tanzania are left behind as Kenya’s oil and Mozambique’s gas projects move ahead.

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