Tian Hailong, Sun Yuzhi, Chen Chuanhai, Zhang Zeyi, Liu Tianyi, Zhang Tianyu, He Jialong, Yu Lijuan
School of Mechanical and Aerospace Engineering, Jilin University, Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, 130022, Jilin Province, People's Republic of China.
China FAW Motor Corporation Limited, Changchun, 130022, Jilin Province, People's Republic of China.
Sci Rep. 2024 Nov 4;14(1):26596. doi: 10.1038/s41598-024-77920-7.
Failure Modes, Effects, and Criticality Analysis (FMECA) is a commonly used method for analyzing system reliability. It is frequently applied in identifying weak points in the reliability of CNC machine tools. However, traditional FMECA has issues such as vague descriptions of risk factors, equal treatment of risk factors, and unclear directions for improving weak points. In response to the issue of vague descriptions of risk factors, this paper further expands severity (S) into machine hazard (M) and personal hazard (P), and subdivides detectability (D) into functional structural complexity (D) and detection cost (D). In addressing the issue of treating risk factors equally, this paper integrates Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA). Subsequently, based on the D-GRA method, the weights of each risk factor were determined by comprehensively considering expert system scores and actual economic loss indicators. In response to the issue of unclear improvement directions for weak points, this paper introduces the BCC model. It treats common failure modes of CNC machine tools as decision-making units within the BCC model, refines risk factors as input indicators, and evaluates the efficiency values of each decision-making unit based on various actual losses as output indicators. Through efficiency value analysis, it proposes improvement directions for weak points. Then, based on the weights of risk factors and the efficiency values of failure modes, a modified calculation method for the new Risk Priority Number (RPN) is proposed to amend the traditional RPN, This paper takes the electric spindle system of a certain machining center as an example, applies the proposed method to rank common failure modes with the new RPN, and compares it with other RPN calculation methods to verify the rationality of the proposed approach. Finally, it presents improvement directions for reliability enhancement.
故障模式、影响及危害性分析（FMECA）是一种常用的系统可靠性分析方法。它经常被用于识别数控机床可靠性方面的薄弱环节。然而，传统的FMECA存在诸如风险因素描述模糊、对风险因素一视同仁以及改进薄弱环节的方向不明确等问题。针对风险因素描述模糊的问题，本文进一步将严重度（S）扩展为机器危害（M）和人员危害（P），并将可检测性（D）细分为功能结构复杂性（D）和检测成本（D）。在解决对风险因素一视同仁的问题时，本文将距离分析方法（DAM）和灰色关联分析（GRA）相结合，提出了距离 - 灰色关联分析（D - GRA）。随后，基于D - GRA方法，通过综合考虑专家系统评分和实际经济损失指标来确定各风险因素的权重。针对薄弱环节改进方向不明确的问题，本文引入了BCC模型。它将数控机床的常见故障模式视为BCC模型中的决策单元，将细化后的风险因素作为输入指标，并基于各种实际损失作为输出指标来评估各决策单元的效率值。通过效率值分析，提出薄弱环节的改进方向。然后，基于风险因素的权重和故障模式的效率值，提出了一种新的风险优先数（RPN）的修正计算方法来修正传统的RPN。本文以某加工中心的电主轴系统为例，应用所提出的方法用新的RPN对常见故障模式进行排序，并与其他RPN计算方法进行比较，以验证所提方法的合理性。最后，给出了可靠性提升的改进方向。
