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
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
Original language | English |
---|---|
Pages (from-to) | 604-624 |
Number of pages | 23 |
Journal | International Journal of Modeling, Simulation, and Scientific Computing |
Volume | 18 |
Publication status | Published - 17 Apr 2023 |