TY - JOUR AU - Arslan, Yusuf PY - 2019/09/30 Y2 - 2024/03/28 TI - Weight losses estimation of industrial punch tools JF - International Journal of Intelligent Systems and Applications in Engineering JA - Int J Intell Syst Appl Eng VL - 7 IS - 3 SE - Research Article DO - 10.18201/ijisae.2019355380 UR - https://ijisae.org/index.php/IJISAE/article/view/1052 SP - 183-187 AB - <p>Many studies have been conducted on the estimation of weight losses of industrial tools; however, these investigations are very rare. And there is no prediction study on the weight loss of industrial punches. An artificial neural network model (ANN) was proposed in order to establish relationships with the field data including input parameters as punch diameter, punch stroke, stroke noise, and punch temperature and output parameter as weight loss of punch. Effect of each parameter on the weight loss of industrial punch was analyzed with the developed model. An empirical formula was also obtained with the generalization capabilities of the ANN system. Analysis results showed that the estimation results are in good agreement with the field data. And these numerical results with high efficiency can make it possible to use the neural designs for real-life industrial punch estimation applications.</p> ER -