Defect detection during manufacturing is an essential step for ensuring the quality and consistency of the product. Optical inspection is a time consuming and expensive task. Firstly, it requires training for human experts to perform inspections. Secondly, it can cause bottlenecks in production/time to market timelines. And to scale such inspections means hiring and training more humans, making the final production expensive.

In 2017, a Chinese factory replaced 90% of its human workers with machines, and it led to 250% increase in productivity and a significant 80% drop in defects. This has led to a number of companies exploring and adopting various automated methods to detect defects in their manufacturing processes to lower costs and reduce manual efforts. But what about accuracy? With the boom in technology, the trend has now been to reach human level accuracy or more in quality inspection with automation.

With Just Analytics' Defect Detection System, modern Industrial firms can strive to achieve both quantity and quality with automation without compromising one over the other using Computer Vision powered by Deep Learning. Here is a quick demo of how our solution works.

Benefits of having a Defect Detection System

• Lower Costs -  Single computer with enough processing power can do more work than multiple humans collectively. And with advances in technology, computers have been getting more powerful and less expensive with time (Moore's law).

• High accuracy -  With help of high resolution cameras and computer vision, defects can be detected easily and with more precision.
• Scalability -  Compute for computer vision can be scaled up and down easily depending on the production load.

Interested to see how our solution works behind the scenes? Here’s a quick demo that runs you through our approach.