Failure modes, effects and criticality analysis (FMECA) is a popular methodology among the safety, reliability, and risk engineers, which can identify the potential failure modes of a system, process, or design, evaluate their cause(s), and rank them according to their criticality. The traditional risk priority number (RPN)-based risk ranking approach has multiple limitations, and researchers have been employing multi-criteria decision making (MCDM) methods to address those drawbacks. In this work, a novel integrated framework is proposed with threefold contributions. Firstly, to minimize the associated linguistic uncertainties during the evaluations of failure modes with respect to the risk factors, the concept of interval type-2 fuzzy sets (IT2FSs) is used. Secondly, to portray the causal dependencies among the risk factors and to compute their weights, an extended IT2F-DEMATEL (Decision Making Trial and Evaluation Laboratory) method is proposed for the group decision-making scenario. Thirdly, the risk ranking results of failure modes are calculated by proposing the concepts of IT2F-MAIRCA (Multi-Attributive Ideal Real Comparative Analysis), IT2F-MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) methods, and modified IT2F-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods. Further, after observing that each of the proposed method calculates different ranking results of failure modes, the concept of half-quadratic (HQ) minimization is used to calculate the aggregated ranking results along with the consensus index and trust level. The potential of the integrated framework is highlighted by considering a benchmark FMECA example of a process plant gearbox. Finally, sensitivity analyses are carried out to observe the robustness of the proposed framework, and each of the developed method.

故障模式，影响和关键度分析（FMECA）是安全，可靠性和风险工程师中流行的方法，可以识别系统，过程或设计的潜在故障模式，评估其原因并对其进行排名根据他们的关键程度。传统的基于风险优先级数字（RPN）的风险排序方法具有多个局限性，研究人员一直在采用多准则决策（MCDM）方法来解决这些缺陷。在这项工作中，提出了一个具有三方面贡献的新颖的集成框架。首先，为了最小化在评估故障模式下与风险因素有关的语言不确定性，使用了区间2型模糊集（IT2FSs）的概念。第二，为了描述风险因素之间的因果关系并计算其权重，针对小组决策场景，提出了扩展的IT2F-DEMATEL（决策试验和评估实验室）方法。第三，通过提出IT2F-MAIRCA（多属性理想真实比较分析），IT2F-MARCOS（根据康普罗姆斯解决方案进行选择和排名测量）方法以及改进的IT2F-TOPSIS的概念来计算故障模式的风险等级结果（类似于理想解决方案的优先顺序技术）方法。此外，在观察到每种提出的方​​法计算出不同的故障模式排序结果之后，使用半二次（HQ）最小化的概念来计算汇总的排序结果以及共识指数和信任级别。通过考虑过程工厂变速箱的基准FMECA示例，突出了集成框架的潜力。最后，进行敏感性分析以观察所提出框架和每种已开发方法的鲁棒性。