Abstract
There is always uncertainty in all aspects of the real life problems. Deterministic optimizations do not take into account the tolerance of input parameters and also the imperfections in operation condition. These uncertainties may cause failure in product line. To produce a product with the least possible failure, the uncertainties must be considered in design and optimization process. This paper presents deterministic and robust design optimization of an outer rotor permanent magnet motor. To reduce the computational burden of finite element method (FEM) application in the optimization process of motor response surface methodology (RSM) surrogate model is adopted. The robust optimization of the motor is based on design for six sigma (DFSS) methodology and the samples are generated using descriptive Monte Carlo sampling (MCS). Finally, the deterministic and robust motors are compared using FEM and the mass production of both motors is simulated.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
