جستجوی مقالات مرتبط با کلیدواژه « FMEA » در نشریات گروه « مدیریت »

In the digital age, blockchain technology is recognized as an operational innovation that is rapidly joining the field of supply chain and humanitarian logistics. Hence, blockchain technology has the potential to fundamentally change the field of humanitarian aid, but still relatively little research has been published aimed at improving understanding of the various barriers to blockchain adoption in humanitarian logistics. The aim of this research is to provide an integrated framework for evaluating the barriers to blockchain adoption in the field of humanitarian logistics. To assess the barriers, integrated approach has been applied in three phases. In the first phase of this approach, based on the literature, 10 barriers to the adoption of blockchain in humanitarian logistics are identified and evaluated using the FMEA method. In the second phase, using the opinions of experts, the weights of the three factors are calculated. Then, in the third phase and according to the outputs of the previous phases, obstacles are prioritized using the proposed Z-ARAS method. In addition to assigning different weights to the three factors considering uncertainty and reliability in barriers is also considered in this approach through the theory of Z numbers. The proposed approach of current study was implemented in the evaluation of blockchain adoption barriers in humanitarian logistics. According to the results, the most critical barriers concern with integrating issues, risk of cyber-attacks, and technology risks. The results shown the capability and superiority of the proposed approach compared to other traditional methods such as FMEA and Fuzzy ARAS.

In the context of the Fourth Industrial Revolution, advanced technologies are reshaping production and business models across various industries, offering new opportunities for enhanced competitiveness but also introducing challenges in terms of adoption and optimization (Wong et al., 2020; Khan et al., 2021). Notably, the convergence of advanced technology and humanitarian logistics is crucial, especially in addressing natural and man-made disasters (Ar et al., 2020; Dubey et al., 2020). This necessitates effective management and the combination of humanitarian logistics with blockchain technology, although this integration comes with multifaceted challenges (Baharmand et al., 2021).
To address these challenges, we explore the Failure Modes and Effects Analysis (FMEA) method as a systematic approach to identify and assess barriers and risks. Traditional FMEA approaches rely on subjective evaluations, which introduce uncertainty into the results. In this context, our research aims to introduce an innovative approach that addresses these limitations by integrating the ARAS method and Z-numbers theory. This approach allows for more reliable prioritization of barriers related to blockchain technology adoption in humanitarian logistics, enhancing the robustness and effectiveness of decision-making processes. In this extended abstract, we present our method and compare its outcomes with traditional approaches to prioritize barriers and risks in blockchain technology adoption within humanitarian logistics. Also, the barriers to blockchain technology adoption in humanitarian logistics and how to prioritize these barriers are among the main research questions.

Blockchain technology is gaining traction in supply chains due to its diverse applications and unique advantages. As supply chains face increasing disruptions, blockchain technology adoption can address challenges and enhance performance (Akhavan & Philsoophian, 2022; Hald & Kinra, 2019). Blockchain structures data into interconnected blocks, ensuring the security and transparency of transactions (Akhavan & Namvar, 2021; Azizi et al., 2021). Blockchain technology is appealing for supply chains due to four main characteristics: encouraging data sharing, minimizing fraudulent transactions, ensuring data immutability, and providing asset security (Babich & Hilary, 2020; Cole, Stevenson, & Aitken, 2019; Rahimi, Akhavan, Philsofian, & Darabi, 2022).
Research on blockchain applications in humanitarian logistics primarily focuses on motivations, such as improved collaboration, transparency, trust, cost reduction, intermediary removal, and shared participation (Baharmand, Maghsoudi, et al., 2021; Seyedsayamdost & Vanderwal, 2020). However, more research is needed in this area (Sahebi, Masoomi, & Ghorbani, 2020). Existing studies have identified barriers to blockchain adoption in humanitarian supply chains, including financial constraints, senior management support, organizational readiness, technological complexity, infrastructure, technology compatibility, and regulatory issues (Baharmand & Comes, 2019).
Multi-criteria decision-making methods (MCDM) have been used to improve FMEA's performance (Ghoushchi et al., 2021; Ghoushchi et al., 2022). These approaches often combine FMEA with methods like GRA, BWM, TOPSIS, and AHP in various fuzzy environments. Such integrated methods have been proposed for barrer identification in the context of blockchain adoption (Li, Li, Sun, & Wang, 2018; Lo & Liou, 2018; Kolios, Umofia, & Shafiee, 2017; Carpitella, Certa, Izquierdo, & La Fata, 2018; Sayyadi Tooranloo & Ayatollah, 2017). Additionally, unified methods like MOORA have been applied to address specific challenges in different contexts (Jafarzadeh Ghoushchi, Memarpour Ghiaci, et al., 2022).
The literature indicates a gap in research on blockchain applications in humanitarian logistics, as most studies focus on business supply chains. Using insights from business supply chains to inform decisions in humanitarian logistics can be misleading, given their fundamental differences (Baharmand, Saeed, Comes, & Lauras, 2021). Consequently, this study aims to address these gaps by proposing an extended FMEA approach based on MCDM methods to identify and prioritize barriers to blockchain adoption in humanitarian logistics, using Z-numbers theory.

The proposed approach of this research is presented, utilizing FMEA and Z-ARAS methods for barrier assessment. The proposed approach consists of three phases. In the first phase, barriers are identified, and the values of the criteria are scored by the FMEA team using linguistic variables from Z-number theory. In the second phase, considering the differences in the importance of criteria, the weight of each criterion is determined based on expert opinions as triangular fuzzy numbers. In the third phase, based on the results of the first and second phases, barrier prioritization is performed while taking into account the criterion weights, using the Z-ARAS method. Unlike the conventional fuzzy ARAS method, the Z-ARAS method can consider uncertainty and reliability for each criterion concerning the options. In this method, after determining the decision matrix, which comprises fuzzy numbers and reliability values (Z-numbers), these values are transformed into triangular fuzzy numbers, and then the Z-ARAS method is executed.

Humanitarian logistics is a relatively new area of research. The impact of humanitarian logistics is crucial, as it saves lives and improves conditions. Research has shown that effective humanitarian logistics is a key driver for the performance of humanitarian organizations. Currently, there exists a significant gap in humanitarian logistics research, particularly in developing countries, between theoretical research and practical implementation.
The adoption of blockchain technology will play a pivotal role in the future development of humanitarian logistics. Therefore, the identification and prioritization of barriers to adopting blockchain technology in humanitarian logistics have gained increasing importance. In this study, an enhanced approach to FMEA is proposed using the Z-ARAS method. Based on the results obtained, "Integration Issues," "Cybersecurity Risks," and "Technology Risks" have been chosen as critical barriers to blockchain technology adoption in humanitarian logistics and are given priority for mitigation and resource allocation. The use of this enhanced approach has addressed some of the limitations of the conventional FMEA method, such as not providing a complete ranking of options. While the developed FMEA approach using the Z-ARAS method is a promising and reliable method, it has limitations. This model may be complex for decision-makers, and it is expected that software tools will be developed to assist decision-makers using this enhanced approach. Additionally, the interaction and impact of barriers were not discussed in this study. Future work can analyze the interplay between barriers to identify critical barriers. Furthermore, researchers can consider multi-criteria decision-making methods like PIPRECIA, SWARA, BWM, and others to determine the importance and weights of criteria. Developing the FMEA method using multi-criteria decision-making methods such as MARCOS, EDAS, CoCoSo, and others for ranking barriers in uncertain environments, including pythagorean, q-rung, and spherical fuzzy scenarios, is also suggested for future studies. Regardless of the issue used for implementing the proposed approach in this research, this approach can be applied to identify and analyze risks and failure modes in various scenarios.

Part of the success in implementing policies goes back to the capacity to implement the policy because capacity is the ability to do so.

In this research, the factors leading to the improvement of the capacity to implement policies and the cause and effect relationship between them have been identified.

This research is applied and the research population is15 HSE policy experts in Kerman who have been selected through non-random and purposeful sampling. Data collection tools were interviews and questionnaires and FMEA and fuzzy dimmetel techniques were used to analyze the data.

The index of organizational support in formulating and implementing HSE policies has the highest and the index of creating organizational structure integration in relation to HSE has the least impact on other indicators to improve the capacity to implement these policies.

Efforts to improve the capacity to implement HSE policies should be accompanied by more investment to improve the quality of the organization's support index in the development and implementation of HSE policies to strengthen other indicators. Focusing on the continued presence of effective HSE experts in the organization and creating management stability can enhance the capacity to implement HSE policies

Development and implementation of safety and health policy is one of the necessities of the organization to reduce accidents and occupational diseases. Policy means the decisions and politics and the purpose of implementing the policy are the activities that it performs directly. Numerous factors lead to the failure to implement occupational safety and health policies. In this study, these factors have been identified and ranked. This research is applied and strategic in terms of survey. The research population consisted of 15 HSE managers in Kerman province who were selected through non-random and purposeful sampling. Data collection tools are interviews and questionnaires and FMEA technique and integrated approach of AHP and fuzzy TOPSIS have been used to analyze the data. Based on the findings, important factors influencing the failure to implement safety and health policies are: Lack of proper organizational structure and lack of funding for implementation. According to the research findings, it is necessary that organizations pay more attention to creating and strengthening the structure of safety and health units and monitor the implementation of safety and health policies by estimating and allocating the necessary budget.

Health and safety policies are implemented in the organizations to reduce occupational accidents and diseases and prevent waste of resources. Policy means the decisions and implementing the policy means the activities that help implementation directly. Numerous measures will reduce the failure to implement occupational safety and health policies. In this research, these factors are identified and ranked.This research is applied and adopts survey as its strategy. The research population consists of 15 HSE managers in Kerman province who are selected through non-random and purposive sampling. Data collection tools are interviews and questionnaires and FMEA technique and integrated approach of AHP and fuzzy TOPSIS are used to analyze the data. Based on the findings, important and effective measures to reduce the failure of safety and health policies implementationinclude reducing the change of managers and requiring new managers to implement safety and health policies, developing scientific programs in accordance with the organization's capabilities and creating an appropriate organizational structure. According to the research findings, it is necessary for organizations to pay more attention to creating and strengthening the structure of safety and health units by carefully planning and changing the approach of managers.

In most execution schemes with various contractual patterns, changes in design and execution have become one of the main problems of project implementation, as many project management theorists have identified as one of the major risks affecting project success. Thus, providing a changes management model can play a key role in a more holistic approach to reducing risk and achieving project goals. For this purpose, unlike other conventional methods of risk assessment and modification, in this study, changes identified by four criteria: probability of occurrence, severity of effect, probability of detection and probability of determining appropriate response using Fuzzy FMEA fuzzy environment technique, The identified changes were prioritized and critical cases identified. Then, to evaluate the impact of other components on project objectives and to consider the interplay of these criteria with each other, it was combined with TOPSIS hierarchical structure method. The results show that engineering design changes are one of the most important factors contributing to the failure of EC projects. Also, poor planning risk is the most effective risk of planning and construction projects when planning ahead is delayed. Given that there are many EC projects currently underway in the Iranian oil industry that are at risk of changes, Using the results of this research can be useful in reducing the effects of unwanted changes and achieving project goals.

Today, more than 60% of the world’s energy resources are oil and gas. Transportation of crude oil, gas andits products is done in different ways, of which the largest share of transmission is borne by transmissionpipes. Gas transmission projects have always been one of the most environmentally hazardous projects,which necessitates project risk assessment and mitigation as one of the important requirements of the projectteam. In this study, the environmental risks of the gas transmission project in Guilan province have beenstudied. By dividing the project into different activities, it tries to minimize the problem and also identifiesthe project risks through the Delphi method, and then the project risks were assessed and ranked in terms ofrisk using FMEA method. AHP method has also been used to monitor FMEA. The project is divided into 15activities involving 29 risks. Analysis and the results of these two methods have shown that the risks related todrilling and piping activities, destruction of agricultural lands and riverbeds, noise pollution, pollution causedby heavy vehicle traffic, as well as pressure reduction activities at the station are among the priority risks ofthe project. The results of the RPN values obtained from the risks show that 28% of the risks have higher thanaverage RPNs which are within the risk range. Finally, methods for identifying and controlling of the high riskactivities have been presented to reduce the environmental risk of the project. The results also indicate that implementationof these methods can reduce up to 90% of the environmental risks associated with the high risks.

Failure modes and effects analysis )FMEA( is a powerful tool for identifying and assessing potential failures in products. Generally risk assessment in FMEA is carried out by using risk priority numbers )RPNs(. As a design and development of new products, this method has many shortcomings and ambiguities, therefore the applying of fuzzy numbers for the calculation of RPNs, is proposed that computational complexity is also encompassed. In this research, examining the kind of ambiguities and uncertainties that exist in the traditional FMEA as well as solutions to overcome the problems have been addressed in other research. Also we developed the software in excel application. This software is successfully tested with real data on the design and development of the “internal ventilation system” of a submarine.

"Engineering, Procurement, and Construction" (EPC) is a particular form of contracting arrangement used in some industries where the EPC Contractor is made responsible for all the activities from design, procurement, construction, to commissioning and handover of the project to the End-User or Owner. In this method of execution, the employer transfers the risk of the operation to the contractor by transferring all the project activities, including the design, procurement and provision of equipment. As a result, identifying and prioritizing risks in these projects is very important for contractors in order to properly manage these risks. One of the most widely used techniques in the risk priority is FMEA. In this paper, we identify and prioritize the risks of an EPC project by combining this technique with the Analytical Network Process (ANP), which is one of the most commonly, used methods in multi criteria decision-making. The FMEA-ANP method, taking into account the cross-risk relationships, evaluates the priority of risk as compared to the FMEA method in a different way, which has a better and higher sensitivity than FMEA scores.

One of the most important risks of organizations is technology risk. In gas companies, due to the expansion of activities, increase in the number of subscribers, and increase share of gas in energy basket, technology has a very important role in delivering appropriate service. Risk assessment in gas technology development projects is very vital. In fact, the existence of numerous risks in the gas industry is one of the main obstacles to the technology development in the country's gas industry. In other words, the implementation of plans and projects of the gas industry are highly risky due to the uncertainty of the specific elements of this industry. The purpose of this study is to provide a suitable framework for identifying and ranking the risks of gas companies using the integrative technique of FMEA and TOPSIS. The distinguished aspect of this paper compared to previous studies is the new method developed based on failure modes and effects analysis (FMEA), Shannon Entropy approach, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for ranking technological risks of the gas company.

In this paper, technology risks in gas distribution have been determined based on literature and expert’s viewpoints. Then, the identified risks were sent to 33 of the company's experts via the FMEA worksheet. After rating the risks by the experts in the FMEA worksheet, instead of obtaining the Risk Priority Number (RPN) number for each risk, the risks were prioritized using the TOPSIS technique. The FMEA method considers three kinds of attributes, namely, occurrence, detection rate, and severity. Occurrence is the probability of the risk, detection rate is the ability of detecting risk, and severity is applied as severity of the effect of risk. The judgment about determination of indicators has been proposed by experts. In this paper, TOPSIS has been used instead of applying an RPN to assess potential failure modes by multiplying indicators of occurrence, detection rate, and severity. TOPSIS is a ranking method with the aim of selecting alternatives that simultaneously have the shortest and farthest distances from the positive and negative ideal solutions, respectively.

Findings indicated that the most important technology risks in gas distribution are i) variation in macroeconomics index (exchange and inflation rate) in country; ii) inability to access required equipment and machinery; iii) inability to access manufacturing technologies; and iv) limited financing for technology development. Research limitations/implications: One of the limitations of this study was separate access to the projects of this industry. In this study, the gas distribution project was defined generally and included all projects in the gas distribution industry. In fact, it was not possible to individually access the gas distribution projects. Analyzing and presenting solutions for each risk separately was another limitation of this study. In other words, considering each risk separately according to the structure of the industry was another limitation of this study.

The results were valid based on the reasonable method and experts’ confirmation and could be suitable for this industry. The technique presented in this study was based on information obtained from the Chaharmahal and Bakhtiari Province Gas Company, while due to the similar structure of provincial gas companies in gas technology and distribution, the method and results obtained in this study can be applied in all gas companies in the field of gas distribution.

The results of this study could decrease the cost of gas distribution industry by determining the most important technological risks of the gas company.

The aim of this study was to propose a new method of FMEA for ranking technological risks of the gas company by integrating Shannon Entropy approach and TOPSIS. The contribution of this study was the investigation of the technological risks of the gas company. In addition, in this paper, a new method was applied by the integration of FMEA and TOPSIS.

The widespread use of medical technology required a considerable amount of resources to be purchased for equipment. Obviously, if the process of purchasing is not properly managed the quantity and quality of these items will not be coordinated with the actual needs of the hospital. Therefore, to avoid wasting resources, money and time, the present article seeks to provide a fuzzy system to evaluate and prioritize the risks involved in purchasing of BUALI hospital. In the present study, a list of possible failures was first identified by studying the subject literature and interviewing experienced experts. Then by more interviewing and examining the experts, the most critical failures were extracted from the list of failures in terms of their importance and their impact. The RPN of each failure was calculated based on the FMEA approach in both classic and fuzzy ways. In fuzzy method, the fuzzy expert system was used to provide a failure risk assessment model. According to the results, the most important failures in the BUALI hospital purchase process, which should be considered more than once, are: "lack of marketable goods", "delayed delivery of goods" and "instant goods deficit". Applying the fuzzy inference system, despite the risk rating of the purchasing process, can provide a clear understanding of each of the risks due to the degree of membership associated with the fuzzy RPN. Therefore, considering the sensitivity of the purchasing process in hospitals, it can be considered for better shopping management.

Projects are planned based on estimated amounts that are the result of having little information about the future plans. According to the uncertainty of planning, time delays and costs of uncertainty are inevitable. The main objective of this study is to present a new approach based on failure mode and effects analysis and fuzzy logic to identify the affecting risks on duration of projects and ranking them using Kepland technique. In addition, in this research Shannon entropy is used for calculation of the weights of indexes. So after the study of related researches as well as through interviews and Delphi technique, some risks were identified. Then, based on three indicators of risk in the FMEA (severity, probability of occurrence, probability of detection), three questionnaire was prepared and their validity was confirmed by experts and reliability was calculated by Cronbach coefficient using SPSS software. The population of the study is 22 managers and experts that work on Debal Khazaei Company. Using triangular fuzzy numbers, the verbal variables of questionnaires became fuzzy numbers. Shannon entropy is used for calculation of weight of each index. Then, using decision making methods, ELECTRE TAXONOMY, TOPSIS and SAW, the risks are ranked. Finally, because of the relative difference of ranking in different techniques, Kapland technique is used to combine the results. TO help for developing the strategies of responding to the risks, some suggestions are presented. The contribution of this research is the simultaneous use of FMEA and Shannon's entropy to analisys the importance of risks and the ranking of them using Kepland technique.

the requirements for maintenance management have change drastically from the old concept of ‘fix-it-when-broken’ to a more complex approach, which entails adopting a maintenance strategy for a more integrated approach and alignment. This paper presents a Goal Programming (GP) approach to define the best strategies for the maintenance of some criticalpumps in a paper industry. For each pump failure mode, the model allows to take into account the maintenance policy burden in terms of inspection or repair and in terms of the manpower involved, linking them to efficiency-risk aspects quantified as in FMEA methodology through the use of the classic parameters occurrence (O), severity (S) and detectability (D), evaluated through an adequate application of the Analytic network process. (ANP) technique. An extended presentation of the data and results of the case analysed is proposed in order to show the characteristics and performance of this approach. The result is in the situation studied predictive and preventive maintenance obtain the best compromise between resource usage and reduction of failure effects. This fact is non-surprising since these policy allows failure prediction, thus providing the maintenance manager with useful information to limit the negative failure aspects.

Due to the growing trend of use of the outsourcing approach in organizations, Gas Company of Chaharmahal and Bakhtiari province, keep pace with developments in the outsourcing of Iran, implementing the most of their capital projects as the treaty. But according to the tenure of parts of operation service is still undertaking company and planning for outsourcing during the coming years in the agenda is located, in order to correct use of outsourcing approach and improvement of Performance Company’s project, correct evaluation of risks before the outsourcing seems necessary in this organization. The purpose of this study providing a useful framework for identifying risks in the company's outsourcing projects and prioritizing them uses FMEA technique. Therefore, investigating the studies conducted, major risks and their effective factors were identified and classified considering the parameters of quality, cost and delivery time. Then, using of FMEA technique and based on the priority level of acquired risk severity, occurrence and detection, attempting to quantify and prioritize identified factors and providing corrective actions to control and reduce the risks. In this study, using a questionnaire survey and interviews with seven of the top executives of companies that are directly related to the issue is performed. Based on acquiring results, structural defects, functional defects and delay in outsourcing project's implementation are more significant and currency exchange fluctuations factors, uncertainty of changing technology and customer requirements, lack of experience, expertise and knowledge in the field of outsourcing and lack of required skills for performance projects in high level and requires greater managerial control.

Proposing a New Approach for Supplier Selection Based on Kraljic’s Model Using FMEA and Integer Linear ProgrammingIn recent years, numerous methods have been proposed to deal with supplier evaluation and selection problem, but a point which has been usually neglected by researchers is the role of purchasing items. The aim of this paper is to propose an integrated approach to select suppliers and allocate orders on the basis of the nature of the purchasing items which means that this issue plays an important role in supplier selection and order allocation. Therefore, items are first categorized according to the Kraljic’s model by the use of FMEA technique. Then, suppliers are categorized and evaluated in four phases with respect to different types of purchasing items (Strategic, Bottleneck, Leverage and Routine). Finally, an integer linear programming is utilized to allocate purchasing orders to suppliers. Furthermore, an empirical example is conducted to illustrate the stage of proposed approach. Results imply that ranking of suppliers and allocation of purchasing items based on the nature of purchasing items will create more capabilities in managing purchasing items and suppliers.