To determine the critical component in an industry is one of the most important tasks performed by maintenance personnel to choose the best maintenance policy. Therefore, the purpose of the current paper is to develop a methodology based on integrated cloud model and extended preference ranking organization method for enrichment evaluation (PROMETHEE) method for finding the most critical component of the framework by ranking the failure causes of the system from multiple decision maker perspective. For this purpose, ranking of failure causes is performed by taking into account five factors namely chances of occurrence of failure (F₀), non-detection probability (N_d), downtime duration (D_d), spare part criticality (S_pc) and safety risk (S_r). In this paper, first the primary and secondary weight of decision makers are calculated based on the uncertainty degree and divergence degree, respectively, to determine overall weight using cloud model theory by converting the uncertain linguistic evaluation matrix into interval cloud matrix, and then ranking of the steam handling subunit of paper making unit in a paper mill using extended PROMETHEE. The effectiveness of the proposed methodology is explained by considering steam handling subunit of paper making unit to find the critical component.

确定行业中的关键组件是维护人员选择最佳维护策略的最重要任务之一。因此，本论文的目的是开发一种基于集成云模型和扩展优先级排序的组织评估方法（PROMETHEE）的方法，该方法通过从多个方面对系统的故障原因进行排序来查找框架的最关键组件。决策者的观点。为此，通过考虑以下五个因素来对故障原因进行排名：即发生故障的机会（F ₀），未检测到的概率（N _d），停机时间（D _d），备件关键性（S _pc）和安全风险（S _r）。本文首先根据不确定度和发散度分别计算决策者的主要权重和次要权重，然后利用云模型理论将不确定性语言评估矩阵转换为区间云矩阵，然后对排名进行排序，从而确定整体权重。使用扩展的PROMETHEE在造纸厂中制造造纸单元的蒸汽处理子单元。通过考虑造纸单元的蒸汽处理子单元来查找关键组件来说明所提出方法的有效性。