Bibliometric analysis of artificial neural network applications in materials and engineering

Abstract

Manufacturing industries in world are under pressure to adopt new technologies in order to sustain their market reputation and increase their performance. ANN is the widely used approach using in the manufacturing industries in various machining processes which results in improving the performance of manufacturing industries. There is need to identify the relationship in cutting parameters in various machining processes which results in the improving the quality and productivity. These relationships can be identified with various mathematical modelling techniques in which ANN is widely used at present time. An Artificial neural network (ANN)is the collection of nodes called artificial neurons, which is modelled according to neurons in biological brain. ANN approach is used because it has an ability to learn, can be used to model complex patterns and prediction problems. Here, Scopus database is used for collection of data with the keywords “Artificial neural network” and also “Artificial Neural Network and machining” is used to determine the trend on machining area, based on collected data bibliometric analysis has been performed. This analysis is used to determine the popularity, impact of publications and use of ANN on machining of different materials. This method is to explore the impact of ANN, the impact of different research areas. A thorough study of statistics of ANN publications by years, research areas, document types, countries, source titles and authors are conducted in this paper. This paper is for research evaluation only.