ABSTRACT

The manufacturing of electric motors is a complex process involving deformable materials and wet processes. When faults are created during the manufacturing process, they tend to accumulate, creating a downstream effect affecting the overall product quality. To detect the faults early in the process, it is crucial to understand how critical process parameters and the interdependencies between them influence the occurrence of faults. This paper proposes a computational framework to model process interdependencies in anelectric motor manufacturing process involving copper wire as a deformable material. A Discrete Event Simulation model was developed to capture process interdependencies and their influence on the generation of faults, in a linear coil winding process. The model simulated the behaviour of the copper wire during every turn in the coil-winding process. The applied tension in the wire, winding speed, the shape of the bobbin, and the diameter of the wire were identified as key input parameters that had maximum influence on the occurrence of faults. The model captured electrical and geometrical faults in the wound coil and was able to calculate accumulated faults in the final wound coil highlighting any hotspot regions. The results from the model were validated by conducting experiments using a lab-based linear coil-winding machine. The validation process also included presenting the results from the model to experts from the electrical machine manufacturing industry and obtaining their feedback..

摘要

电动机的制造是一个复杂的过程，涉及可变形材料和湿法工艺。当在制造过程中产生故障时，它们往往会累积，从而产生影响整体产品质量的下游效应。要在流程早期检测到故障，了解关键流程参数以及它们之间的相互依存关系如何影响故障的发生至关重要。本文提出了一个计算框架，用于对涉及铜线作为可变形材料的电动机制造过程中的过程相互依赖性进行建模。开发了离散事件仿真模型，以捕获线性线圈绕组过程中的过程相互依赖性及其对故障生成的影响。该模型模拟了铜线在线圈绕制过程中每一圈的行为。导线中施加的张力、绕线速度、线轴形状和导线直径被确定为对故障发生影响最大的关键输入参数。该模型捕获绕线线圈中的电气和几何故障，并能够计算最终绕线线圈中的累积故障，突出显示任何热点区域。通过使用基于实验室的线性线圈绕线机进行实验来验证模型的结果。验证过程还包括向电机制造行业的专家展示模型的结果并获得他们的反馈。线径被确定为对故障发生影响最大的关键输入参数。该模型捕获绕线线圈中的电气和几何故障，并能够计算最终绕线线圈中的累积故障，突出显示任何热点区域。通过使用基于实验室的线性线圈绕线机进行实验来验证模型的结果。验证过程还包括向电机制造行业的专家展示模型的结果并获得他们的反馈。线径被确定为对故障发生影响最大的关键输入参数。该模型捕获绕线线圈中的电气和几何故障，并能够计算最终绕线线圈中的累积故障，突出显示任何热点区域。通过使用基于实验室的线性线圈绕线机进行实验来验证模型的结果。验证过程还包括向电机制造行业的专家展示模型的结果并获得他们的反馈。该模型捕获绕线线圈中的电气和几何故障，并能够计算最终绕线线圈中的累积故障，突出显示任何热点区域。通过使用基于实验室的线性线圈绕线机进行实验来验证模型的结果。验证过程还包括向电机制造行业的专家展示模型的结果并获得他们的反馈。该模型捕获绕线线圈中的电气和几何故障，并能够计算最终绕线线圈中的累积故障，突出显示任何热点区域。通过使用基于实验室的线性线圈绕线机进行实验来验证模型的结果。验证过程还包括向电机制造行业的专家展示模型的结果并获得他们的反馈。