Automation of Physical Defect Detection in Bangle Industries
- 1 min-
Creation of Unique Dataset by bangle factory product and using Data augmentation.
-
Applying ML Algorithms to Predict whether the bangle is Good, defected or partially defected.
Abstract
Automation in the bangle industry is the base study of this work. The manufacturing of bangles is a complicated task and requires great concentration in visualizing the quality of bangles.
In bangle manufacturing industry, product defect directly contributes to the low quality of the products which lead to the failure of the industry. Although a human can easily identify the defects present, but its still a difficult task to examine each and every bangle. It is time-consuming as well as a tiresome process.
Scope of the Project
This device helps us to classify the bangles on the basics of defects (Physical level defects) during manufacturing and to distinguish between defected bangle and non-defected bangle thereby increasing the quality of production.
The device will also help to reduce the problem of finding the skilled workers who can identify the defect and also reduce the manufacturing cost of the bangles. It is a small step towards the automation of the bangle industry.