Prediction of life of piercing punches using artificial neural network and adaptive neuro fuzzy inference systems

Autor:	E. Balasubramanian, Sachin Salunkhe, Udayagiri Chandrasekhar, D. Rajamani
Rok vydání:	2019
Předmět:	Adaptive neuro fuzzy inference system business.product_category Materials science Artificial neural network Neuro-fuzzy business.industry Principal (computer security) Inference Fatigue limit Finite element method Machine tool General Materials Science Artificial intelligence business
Zdroj:	International Journal of Materials Engineering Innovation. 10:20
ISSN:	1757-2762 1757-2754
DOI:	10.1504/ijmatei.2019.097892
Popis:	Predicting the life of piercing punch is one of the major concerns in the design of compound dies. Finite element analysis is performed to determine the maximum and minimum principal stresses through which fatigue limit of punch is estimated. The factors affecting the life of punch are examined and a mathematical model is established using artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS). The developed model is utilised to evaluate the life of punch for varied load conditions. Comparative evaluation of ANN and ANFIS results suggested that the later model is superior in predicting the life of punch and it can be effectively utilised in machine tool applications.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ca130d88dd9aba18dfbd97a526d80a5 https://doi.org/10.1504/ijmatei.2019.097892 Zobrazit plný text záznamu