Product quality is one of the most important factors to be considered in manufacturing industries. Autonomous production line rapidly increases its productivity; however, quality check becomes a difficult problem and a smart system for quality assurance is indispensable in the modern production line In this study, we developed a transmission error based machine learning algorithm to check the quality of planetary gear assemblies and identify the defective parts in the planetary gear sets.
Han, S., Seo, S., & Choi, H. J. (2015). A study on modeling customer preferences for conceptual design. Journal of Mechanical Science and Technology, vol. 29(12), pp. 5083-5091
Wimarshana, B., Ryu, J., & Choi, H. J. (2014). Neural network based material models with Bayesian framework for integrated materials and product design. International journal of precision engineering and manufacturing, vol. 15(1), pp. 75-81.
Dreiseitl, S., & Ohno-Machado, L. (2002). Logistic regression and artificial neural network classification models: a methodology review. Journal of biomedical informatics, vol. 35(5), pp. 352-359.
Sheela, K. G., & Deepa, S. N. (2013). Review on Methods to fix number of hidden neurons in neural networks. Mathematical problems in engineering 2013, pp. 1-11.