Equipment fault is a major factor that affects the reliability of manufacturing systems. Fault source identification and propagation path search are primary means to reduce and eliminate equipment faults. To this end, this paper proposed a two‐layer model of equipment fault propagation in a manufacturing system. One layer, modeled by a small‐world network, is a network of parts for a single equipment device. The other, represented by the production relationships of the manufacturing process, is a network of equipment devices for a manufacturing system. Hence, the propagation path of an equipment fault is divided into physical propagation inside a single equipment device and flow propagation within the manufacturing process. The intensity of physical propagation is given by the product of the fault load and the propagation probability between fault nodes within a single equipment device, whereas the flow propagation intensity is equivalent to the yield loss of the manufacturing system due to equipment fault. Therefore, the total intensity of fault propagation in a manufacturing system is given by the product of these two intensities. Subsequently, the ant colony algorithm is used to find the propagation paths with the maximum intensity. Finally, the proposed method is verified using an example of a camshaft manufacturing system.

中文翻译：

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制造系统中设备故障传播的两层模型

设备故障是影响制造系统可靠性的主要因素。故障源识别和传播路径搜索是减少和消除设备故障的主要手段。为此，本文提出了制造系统中设备故障传播的两层模型。由小型世界网络建模的一层是单个设备设备的零件网络。由制造过程的生产关系表示的另一个是制造系统的设备设备网络。因此，设备故障的传播路径分为单个设备设备内部的物理传播和制造过程中的流传播。物理传播的强度由故障负载与单个设备设备内的故障节点之间的传播概率的乘积给出，而流的传播强度等于由于设备故障而导致的制造系统的产量损失。因此，制造系统中故障传播的总强度由这两个强度的乘积给出。随后，使用蚁群算法找到强度最大的传播路径。最后，以凸轮轴制造系统为例验证了所提出的方法。制造系统中故障传播的总强度由这两个强度的乘积给出。随后，使用蚁群算法找到强度最大的传播路径。最后，以凸轮轴制造系统为例验证了所提出的方法。制造系统中故障传播的总强度由这两个强度的乘积给出。随后，使用蚁群算法找到强度最大的传播路径。最后，以凸轮轴制造系统为例验证了所提出的方法。