Time-varying FMEA method based on interval-valued spherical fuzzy theory

This paper proposes a time-varying failure mode and effect analysis (FMEA) method based on interval-valued spherical fuzzy theory, which not only improves the limitations in evaluating, weighting, and ranking but also considers the effect of time change. The process of distinguishing time changes enables the FMEA to have dynamic recognition capability, enabling it to identify critical failure modes more accurately. The interval-valued spherical fuzzy theory is used to deal with the uncertainty of intuitionistic linguistic evaluations. The advantages of two traditional approaches are combined to improve the weight determined method. Risk factors are divided into subjective and objective types. In the subjective risk factors, which are severity (S) and detection (D), the consistency of judgment is used as the acceptance standard. In the objective risk factors, which are occurrence (O), the time-varying characteristics are considered. The occurrence in a certain period is expressed as the integral of failure intensity in the time period. Interval-valued spherical fuzzy exponential risk priority number is proposed as the criterion for measuring the priority of failure modes. The effectiveness of the proposed method is verified using an example of spindle.     

集成鱼骨分析与进化法则的产品失效预测及问题求解

 基于传统FMEA在失效问题分析与解决方面的不足,提出了一种集成鱼骨图、FMEA和进化法则的创新设计方法．利用鱼骨图层次化分析辅助FMEA全面挖掘可能发生的失效模式,按照FMEA的规范表达分析失效模式并确定风险优先指数RPN,然后运用进化法则针对失效问题进行有效的解决,提高了解决问题的效率．最后通过铁路减振的示例验证了该集成方法的可行性．     

A new hybrid MCDM approach for RPN evaluation for a medical device prototype

The Failure Mode and Effect Analysis (FMEA) is a useful instrument born in the aerospace industry and widely used to improve a process or product's efficiency. Over the years, this instrument has been adopted in increasingly different contexts, such as HealthCare. This paper proposes an approach aimed at improving the defects typical of the classic FMEA in the design phase, that is, in a scenario full of uncertainties and with little information available, using a new hybrid Multiple-criteria decision-making (MCDM) method in order to obtain a priority index more performant than Risk Priority Number (RPN). In the proposed method, the three assessment criteria have a different weighting in the index's final computation, differently from the classical RPN. These weights are obtained with a scientific technique, thus avoiding that excessive subjectivity influences the final result. A more efficient priority index is obtained through a new hybrid approach that solves some classical RPN gaps. A case study concerning an endoscope Ear Nose Throat Entropy (ENT) prototype is examined to illustrate the proposed method. FMEA analysis in HealthCare is increasingly used for its flexibility and reliability. This study focuses on using new techniques to eliminate certain defects or exploit some qualities better. The use of a robust and elastic innovative MCDM method to calculate a new priority index and a scientific technique to obtain the weight of the selection are the interesting insights proposed in this paper.     

Risk evaluation and mitigation of sustainable road freight transport operation: a case of trucking industry

Road freight transportation sustainability is gaining increasing importance due to an ever-increasing freight movement, globalisation and operational flexibility. The transport managers across the globe are finding it difficult to manage the increasing risks in its operation and implementation of risk-mitigation strategies under economical sustainability. However, very few literatures have examined the impact of sustainable risk management practices on road freight transportation. Our study addresses this important gap in the literature by proposing an integrated fuzzy failure mode and effects analysis (FMEA) approach in the selection of risk-mitigation strategy on the trucking industry. Our findings direct to the managers that risk-mitigation strategies must be selected considering the criticality of risks along with the limited budget. In addition, we find that considering subjective evaluations of expert’s judgment and cost benefit justification gives a convincing outcome while calculating of risk-mitigation number in FMEA approach. Proposed approach provides supportive guidelines to the manager to improve the decision-making process.     

Contribution to development of risk analysis methods by application of artificial intelligence techniques

During the life cycle of technical systems, precise and detail failure risk analysis gives suitable input elements for taking appropriate actions, which allows reducing of unwanted uncertainty and occurrences. Traditional method for risk analysis, which is applied for many years, especially in analysis of functionality of technical systems, is Failure Mode and Effects Analysis (FMEA) method. However, in many cases, this method shows weaknesses related to the inconsistency, which is a result of insecure subjectivity during the determination of values for parameters that gives Risk Priority Number (RPN), as well as other weaknesses. This paper shows contribution to the development of failure risk analysis based on FMEA method. Contribution of the development of risk analysis methods is given through modification of traditional FMEA method by integration of artificial intelligence techniques, in this case, by integration of fuzzy logic and by including a few principles based on special classification of recognized failures. Thus, it is minimized effect of methodological inconsistency and some of other identified weaknesses of traditional FMEA method. FMEA method is improved, which provides more precise failure risk evaluation and thus better prediction and minimizing of unwanted occurrences (failures of elements, subsystems, components, etc., of technical systems). It was proved by comparative analysis of applied traditional FMEA method as well as modified FMEA method, hereinafter called “intelligent” FMEA method (IFMEA) on system of tires for city busses.     

Improved FMEA based on IVF and fuzzy VIKOR method: A case study of workpiece box system of CNC gear milling machine

Failure mode and effect analysis (FMEA) is a tool used to define, identify, and prevent known or unknown potential risks. An improved FMEA based on interval triangular fuzzy numbers (IVF) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is proposed in this study to solve problems of expression and processing of uncertain information, weights of risk factors, and ranking of failure modes in traditional FMEA. Linguistic variables are used to evaluate failure modes level and relative importance of risk factors and are expressed via interval-valued triangular fuzzy number. Determining the subjective weights of risk factors using fuzzy AHP, calculating the objective weights of risk factors using the extended VIKOR method, and obtaining the comprehensive weights of risk factors via ICWGT are proposed for solving the weight problem of risk factors. Finally, the fuzzy VIKOR method is used to rank risk priority of failure modes. The proposed method is used to evaluate workpiece box system of CNC gear milling machine and the results are compared with the findings of other methods to verify effectiveness and rationality of the proposed method.     

Failure mode and effect analysis using the hesitant intuitionistic fuzzy hybrid GRP approach with ordered comprehensive weights

Failure mode and effect analysis (FMEA), a multidisciplinary reliability analysis tool based on team evaluations, has been widely used in various industries. There are three critical issues in FMEA: the conversion of linguistic evaluations, the weights of risk factors, and the ranking mechanism of failure modes. Scholars have used various fuzzy theories and multi-attribute decision-making (MADM) methods to improve traditional FMEA, but there are still deficiencies. In this paper, the hesitant intuitionistic fuzzy set (HIFS), a concept that combines the intuitionistic fuzzy set (IFS) and the hesitant fuzzy set (HFS), is introduced into FMEA to convert linguistic evaluations. Some operators based on HIFS are proposed to process the converted data. Among them, a hesitant intuitionistic fuzzy comprehensive weighted Hamming distance (HIFCWHD) operator is proposed to compute the ordered comprehensive weight, effectively weakening the effect of extreme scores on results. The gray relational projection (GRP) method is adopted to determine the risk priority order of the failure modes. Finally, we give an illustrative case to demonstrate the effectiveness of the proposed FMEA method.     

基于SHERPA和FMEA的老年人医疗APP交互设计研究

目的 关爱老年人身体健康,设计适合老年人使用的医疗APP。方法 提出基于SHERPA和失效模式与效应分析（FMEA）的方法,先成立专家小组绘制医疗APP层次任务分析图,进行SHERPA分析,随后运用失效模式与效应分析找出APP潜在失效模式,计算风险优先数值,然后针对需要改善的失效模式进行设计改良,最终对改良后的APP进行结果验证。结论 将SHERPA和FMEA方法应用于老年人医疗APP,可以对任务的每一步骤进行错误预测,尽早发现问题,采取改善措施,体现了对老年人的人性化关怀,使他们在操作过程中获得良好的交互体验。     

Fuzzy logic-based FMEA robust design: a quantitative approach for robustness against groupthink in group/team decision-making

Group/team decision-making is an integral part of almost all failure mode and effects analysis (FMEA) projects. A dysfunctional aspect of this decision-making fashion in fuzzy FMEA is that group/team members’ designs for membership functions and IF-THEN rules may be overshadowed by a member’s design. This problem is caused by groupthink, a pitfall known by the Organisational Behaviour science. This study aims to develop a fuzzy FMEA approach which is robust to the problem. We applied the Taguchi’s robust parameter design and investigated the effects of various control parameters namely Defuzzification, Aggregation, And and Implication operators for the fuzzy inference system (FIS). Our experiments illustrate that the control parameters, in the above-mentioned order, have the most effect on the signal-to-noise ratio (SNR). These factors’ optimal setting consists of the Centroid, Sum, Minimum and Minimum levels, respectively.     

An alternative evaluation of FMEA: Fuzzy ART algorithm

Failure Mode and Effects Analysis (FMEA) is a technique used in the manufacturing industry to improve production quality and productivity. It is a method that evaluates possible failures in the system, design, process or service. It aims to continuously improve and decrease these kinds of failure modes. Adaptive Resonance Theory (ART) is one of the learning algorithms without consultants, which are developed for clustering problems in artificial neural networks. In the FMEA method, every failure mode in the system is analyzed according to severity, occurrence and detection. Then, risk priority number (RPN) is acquired by multiplication of these three factors and the necessary failures are improved with respect to the determined threshold value. In addition, there exist many shortcomings of the traditional FMEA method, which affect its efficiency and thus limit its realization. To respond to these difficulties, this study introduces the method named Fuzzy Adaptive Resonance Theory (Fuzzy ART), one of the ART networks, to evaluate RPN in FMEA. Copyright © 2008 John Wiley & Sons, Ltd.     

A Dynamic Maintenance Planning Framework Based on Fuzzy TOPSIS and FMEA: Application in an International Food Company

A maintenance planning framework is developed in this study to reduce and stabilize the maintenance costs of the manufacturing companies. The framework is based on fuzzy technique for order preference by similarity to ideal solution(TOPSIS) and failure mode and effects analysis (FMEA) techniques and supports maintenance planning decisions in a dynamic way. The proposed framework is general and can easily be adapted to a host of manufacturing environments in a variety of sectors. To determine the maintenance priorities of the machines, fuzzy TOPSIS technique is employed. In this regard, ‘risk priority number’ obtained by FMEA and ‘current technology’, ‘substitutability’, ‘capacity utilization’, and ‘contribution to profit’ are used as the criteria. Performance of the resulting maintenance plan is monitored, and maintenance priorities of the machines are updated by the framework. To confirm the viability of the proposed framework, a real‐world implementation in an international food company is presented. The results of the application reveal that the proposed maintenance planning framework can effectively and efficiently be used in practice. Copyright © 2015 John Wiley & Sons, Ltd.     

Applying UGF Concept to Enhance the Assessment Capability of FMEA

The purpose of this paper is to propose a modified version of Failure Mode and Effects Analysis (FMEA) to alleviate its drawbacks. FMEA is an important tool in risk evaluation and finding the priority of potential failure modes for corrective actions. In the proposed method, the Universal Generating Function (UGF) approach has been used to improve the assessment capability of the conventional Risk Priority Number (RPN) in ranking. The new method is named as URPN. It generates the most number of unique values in comparison with the previous methods and considers relative importance for the parameters while it is easy to compute. More unique numbers help to avoid from having the same priority level for different failure modes which represent various risk levels. A case study has been employed to demonstrate that the URPN not only can improve the shortcomings but also is able to provide accurate values for risk assessment. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS

Risk is inherent in almost every activity of supply chain management. With the ever-increasing push for efficiency, supply chains today are getting more and more risky. Adding to the difficulty of dealing with these risks is the amount of subjectivity and uncertainty involved. This makes analytical examination of the situation very difficult, especially as the amount of information available at a particular time is not sufficient for such an analysis. Thus a supply chain risk index, which captures the level of risk faced by a supply chain in a given situation, is the need of the hour. This study is an effort towards quantifying the risks in a supply chain and then consolidating the values into a comprehensive risk index. An integrated approach, with a fuzzy analytical hierarchy process (AHP) and a fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) as its important elements, has been used for this purpose. Fuzzy values in this study help in capturing the subjectivity of the situation with a final conversion to a crisp value which is much more comprehensible. A case study is used to illustrate the proposed methodology.     

An interval probability-based FMEA model for risk assessment: A real-world case

Failure mode and effect analysis (FMEA) is an effective quality tool to eliminate the risks and enhance the stability and safety in the fields of manufacturing and service industry. Nevertheless, the conventional FMEA has been criticized for its drawbacks in the evaluation process of risk factors or the determination of risk priority number (RPN), which may lead to inaccurate evaluation results. Therefore, in this paper, we develop a novel FMEA method based on rough set and interval probability theories. The rough set theory is adopted to manipulate the subjectivity and uncertainty of experts' assessment and convert the evaluation values of risk factors into interval numbers. Meanwhile, the interval exponential RPN (ERPN) is used to replace the traditional RPN due to its superior properties, eg, solving the problems of duplicate numbers and discontinuity of RPN values. Furthermore, an interval probability comparison method is proposed to rank the risk priority of each failure mode for avoiding the information loss in the calculation process of RPN. Finally, a real case study is presented, and the comparison analysis among different FMEA methods is conducted to demonstrate the reliability and effectiveness of the proposed FMEA method.     

一种综合赋权的改进FMEA风险评估方法

针对传统故障模式和影响分析(failure mode and effects analysis, FMEA)方法中的未考虑风险因子权重以及风险因子权重难确定这一问题,提出一种综合赋权的改进FMEA风险评估方法。该方法首先通过FMEA团队明确评估对象和FMEA范围,然后列出所有潜在故障模式,对故障模式进行打分,得到所有的专家打分评估表,再通过语言变量转化为直觉模糊数。由层次分析法确定主观权重,由数据本身确定客观权重,使用直觉模糊混合加权算子(intuitionistic fuzzy hybrid weighted, IFHW)算子集结评价信息,得到所有的故障模式的得分函数,最后基于风险最大化选取每个故障模式的最大分数,进行排名,得到最终的故障模式风险顺序。通过对静电纺丝设备进行FMEA分析,并与其他方法进行比较,验证了所提方法的可行性。     

An improved FMEA method based on the linguistic weighted geometric operator and fuzzy priority

Using the group linguistic information aggregation method, this research improved upon conventional failure mode and effect analysis (FMEA), which had the problems of the inevitable subjectivity of expert evaluations, and of the difficulty of determining the weights of experts' evaluations. First, this research treated the three risk factors of FMEA evaluation as linguistic variables and introduced a linguistic weighted geometric (LWG) operator to implement algebraic operations on the results of expert evaluations. This treatment overcame the disadvantage of fuzzy theory-based methods in which decision-making information could be lost due to the twice conversion process. Second, the weights of experts' evaluations were calculated based on the consistency of experts' ranking using a fuzzy priority method. This method placed a lower weight for the experts whose evaluation departed from group consensus, and therefore decreased the impact of the unfairness of experts on evaluation results. Finally, this article demonstrated the effectiveness and applicability of this method by an example of failure-mode analysis on the grinding wheel system of a numerical control machine.     

A linguistic risk prioritization approach for failure mode and effects analysis: A case study of medical product development

Failure mode and effects analysis (FMEA) is a widely used risk management technique for identifying the potential failures from a system, design, or process and determining the most serious ones for risk reduction. Nonetheless, the traditional FMEA method has been criticized for having many deficiencies. Further, in the real world, FMEA team members are usually bounded rationality, and thus, their psychological behaviors should be considered. In response, this study presents a novel risk priority model for FMEA by using interval two‐tuple linguistic variables and an integrated multicriteria decision‐making (MCDM) method. The interval two‐tuple linguistic variables are used to capture FMEA team members' diverse assessments on the risk of failure modes and the weights of risk factors. An integrated MCDM method based on regret theory and TODIM (an acronym in Portuguese for interactive MCDM) is developed to prioritize failure modes taking experts' psychological behaviors into account. Finally, an illustrative example regarding medical product development is included to verify the feasibility and effectiveness of the proposed FMEA. By comparing with other existing methods, the proposed linguistic FMEA approach is shown to be more advantageous in ranking failure modes under the uncertain and complex environment.     

Failure Mode Avoidance of Solid Rocket Motor Pressure Monitoring Joint Seals

The sealing joints used for pressure monitoring of solid propellant rocket motors (SRMs) of launch vehicles are very critical, as they are large in number, and leak through any of them is a single point failure mode. Identification of failure modes and its prevention is the key for reliable performance of an SRM. Failure modes are identified and the failure mechanisms of different seals in the pressure monitoring system studied through investigative tests with deliberately induced variations in the design parameters and nonconformance. Systematic analysis is carried out for the proposed designs through a failure mode effects analysis (FMEA), failure modes ranked in accordance with Risk Priority Number (RPN) and reliability of the joints worked out from the data. Design concerns are analyzed, alternate designs explored and innovative design solutions evolved. The effectiveness of the final design is brought out quantitatively by reduced RPN ratings and quantum jump in the reliability. Critical design, process and quality control parameters were identified, and procedures to ensure them evolved for failure mode avoidance.     

An integrated fuzzy approach for the selection of outsourcing manufacturing partners in pharmaceutical R&D

The selection of the outsourcing manufacturing partners (OMPs) is an important issue for research and development (R&D) in the pharmaceutical industry. The selection process considers several main criteria, as well as a few sub-criteria for each main criterion. Such problems can be formulated as hierarchical structures and can usually be resolved with multi-criteria decision-making approaches. This paper presents an integrated fuzzy approach for selecting a suitable OMP in pharmaceutical R&D. In the integrated approach, fuzzy concepts are used for decision-makers’ subjective judgments to reflect the vague nature of the selection process. Fuzzy AHP and fuzzy TOPSIS are included in the integrated approach. Fuzzy AHP is used to determine the fuzzy weights of criteria and sub-criteria because it can effectively determine various criteria's weights in a hierarchical structure. Fuzzy TOPSIS aims to find the OMP with the best performance with respect to the sub-criteria. We exemplify the integrated approach using a numerical application to demonstrate its feasibility.     

Exploring a cobot risk assessment approach combining FMEA and PRAT

Collaborative robots are an emerging technology falling within the scope of Industry 4.0 and based on the concept of Human-Robot Collaboration (HRC). Unlike traditional industrial robots, collaborative robots are used in shared workspaces with no safety fences. Hence, prospective hazardous contacts need to be avoided or mitigated through a risk assessment. The normative standards such as ISO TS 15066 suggest a list of common hazards, but do not guide the robot system user through the risk assessment process. To address this shortcoming, this paper proposes a practical eight steps risk assessment approach, resulting in a risk priority list. In order to provide an accurate, practical, quantitative and supportive tool for HRC environments, the Failure Mode and Effects Analysis (FMEA) and the Proportional Risk Assessment technique (PRAT) techniques are proposed for risk assessment. The two techniques mentioned above are combined in the suggested new methodology, highlighting both their benefits and disadvantages. The proposed methodology is applied with positive results to a collaborative brick-lifter case study.