Applying risk assessment approaches to improve quality in enterprises is of great importance especially for sectors that are labor-intensive and thus frequently encountered failures. One of the methods frequently used to take precautions against failures caused by high variability in this type of sector is failure mode and effects analysis (FMEA). In this study, a hybrid FMEA approach is proposed so as to take measures against failures in the textile sector where there are high-quality differences due to its structure and failures frequently occurred. Since the different combinations of risk parameters’ scores may produce the same risk degree based on the function of the FMEA’s basis, misleading results for the risk analysis in the practical risk management can be occurred. Moreover, the risk priority number (RPN) function has a limitation in the weight determining process, since it assigns the equal weight for each risk parameter in the classical FMEA. To overcome these shortcomings in the RPN calculation for the risks in the FMEA approach, a multi-criteria decision-making (MCDM) approach is applied under the framework of fuzzy logic. Through that, in this study, we aimed to prove an expert system based on the rules that specifically focusing on the risk sources of the woven fabric industry. To create such a rule-based system, inputs are generated using fuzzy AHP and modified fuzzy TOPSIS. A case study is carried out with the method proposed in a textile mill, and it is determined which risks arising from failures are higher. For the validation of the results, a comparative analysis is conducted. Moreover, for the robustness of the decisions, one-at-a-time sensitivity analysis with respect to different scenarios are applied. As a result of the analyses, it is shown that our proposed model can be used as an efficient proactive risk calculator for the managers or researchers to make useful inferences, judgments, and decisions of the production processes for eliminating the shortcomings of the traditional FMEA.

应用风险评估方法来提高企业质量非常重要，特别是对于劳动密集型，因此经常遇到失败的行业。故障类型和影响分析（FMEA）是经常用于预防此类类型的高可变性导致的故障的方法之一。在这项研究中，提出了一种混合FMEA方法，以便针对由于结构和经常发生故障而存在高质量差异的纺织部门的故障采取措施。由于基于FMEA基础的功能，风险参数得分的不同组合可能会产生相同的风险程度，因此在实际风险管理中可能会产生误导性结果。此外，风险优先级数字（RPN）功能在权重确定过程中存在局限性，因为它为传统FMEA中的每个风险参数分配了相等的权重。为了克服RMEA计算中FMEA方法风险的这些缺点，在模糊逻辑框架下应用了多准则决策（MCDM）方法。通过该研究，我们旨在基于专门针对机织物行业风险源的规则证明专家系统。为了创建这样的基于规则的系统，使用模糊AHP和改进的模糊TOPSIS生成输入。用纺织厂提出的方法进行了案例研究，确定了由故障引起的风险更高。为了验证结果，进行了比较分析。此外，为了确保决策的鲁棒性，针对不同情况应用了一次敏感性分析。分析的结果表明，我们提出的模型可以用作管理人员或研究人员进行生产过程的有用推论，判断和决策的有效主动风险计算器，以消除传统FMEA的缺点。