Abstract: The current review paper examines how machine vision systems can be used to inspect cylindrical gears with reference to the shortcomings of the conventional techniques which include Coordinate Measuring Machines (CMMs), as well as manual inspection. Machine vision systems are highly throughput, non-contact, and real time, which enhance the quality control of gears (Wang et al., 2020). Machine learning and artificial intelligence (AI), specifically, Convolutional....
[1].
Kumar, A., & Sharma, R. (2020). Gear Manufacturing Quality Control Through Machine Vision Technology. Journal Of Manufacturing Science And Technology, 45(2) 123-134.
[2].
Li, Y., & Zhou, X. (2021). Defect Detection During Cylindrical Gear Inspection Driven By AI. International Journal Of Precision Engineering, 29(3): 567-576.
[3].
Wang, Z., Li, W., & Zhang, T. (2020). Machine Vision And AI Model Based Non-Contact Gear Inspection. International Journal Of Machine Vision, 55(3), 203-215.
[4].
Wang, L., Liu, S., & Zhao, F. (2019). Mechanical System Manufacturing With The Use Of Machine Vision. Journal Of Mechanical Engineering, Vol. 44(8), P. 120-133.
[5].
Zhang, Q., Wang, Z., & Wu, J. (2020). Real-Time Gear Defect Detection And Measurement By Using Machine Vision. Manufacturing And Materials Processing, 39(6), 189-201.
