1M.Tech, Mechanical Engineering, Universal Institutions of Engineering and Technology, Bollapur, Lalru
2Assistant Professor, Mechanical Engineering Department, Universal Institutions of Engineering and Technology, Bollapur, Lalru
When the data and graphs of the London Metal Exchange are studied, stainless steel prices are obviously increasing. There are, therefore, significant problems faced by steel producers with pricing competitiveness and growing expenses. Waste reduction and improved productivity methods in the production and factory washing plugs are therefore necessary. It involves the adoption of automatic processing and classification of items and replacement of people with machines. The machines incorporated need to be smart to take decisions like humans and thus artificial intelligence makes iteasy. In this paper, we have proposed our study related to easy classification of items like washers and locating pins in the industries in order to save money and time. The system uses Convolutional Neural Network. The dataset is downloaded from the internet and same is used for training the model. Many models are made with different training parameters and the highest accuracy found was 96%. The testing phase involved the classification of image into washer and locating pin. Spyder software was used for simulation and language used is python.
Dataset, Open CV, Convolutional Neural Network, Epoch, Batch Size
