Automated Defect Detection and visual inspection using AI for industry 4.0

Intelgic’s Vision AI platform is specially designed for automating visual inspection processes in the manufacturing and supply chain industry. Our defect detection system takes an innovative approach where We use custom AI models along with the generative AI to detect defects such as scratches, cracks, stains, dirt, nicks, colors and everything that a human eye can detect.

Vision AI and machine inspection capabilities in defect detection and quality inspection

Nonferrous metals

Detect scratches, die marks, cracks, dirts and dents and other cosmetic defects from the product surfaces accurately using Vision AI.

Pharmaceutical

Pharmaceutical products are one of the most sensitive products where various defects can be detected using AI efficiently and accurately. There are many defects in the tablet such as capping, lamination, sticking, binding, mottling, cracking, double impression, etc. that can be detected accurately.

Apart from that, we can also detect leveling errors, capping errors and other irregularities that are cosmetic and visible.

Electronics components

Detect various defects within the electronic chips with high accuracy. PCB defects, bad soldering, position shifts, blowholes, acid trap, plating voids, missing solder masks are some of the defects that vision AI can detect.

Building Materials

Detect Scratches, cracks, surface defects, dents on different construction and building related products such as wood boards, sashes, metal fittings, tiles, concrete, bricks and blocks, glass, metallic products etc.

Automotive parts

Vision AI can inspect and successfully do surface defect detection such as Scratches, dents, dirt, cracks, wrong orientation, wrong shape and size of auto parts.

Raw materials

Detects Scratches, chips, cracks, dents etc. on glass, rubber, papers and other raw materials efficiently and accurately.

Food production

Food is a sensitive product. Detect Foreign objects, labeling errors, leaks, packaging damage, missing bottle caps are some of the things that we can detect with machine vision AI

To implement defect detection in products, it's crucial to set up a visual or machine inspection system within your manufacturing lines. Please follow the steps below to develop the machine vision system within your manufacturing.

Step

Evaluate and pinpoint the common defects typically observed in your production line. List down the product defects that significantly impact your production efficiency, revenue, etc.

Step

Gather images of these defects as they appear in your products. These images will be used to train an AI model tasked with monitoring your products moving forward.

Step

Annotate or label these images using rectangle bounding boxes, polygons, or key point annotation methods to prepare the dataset for the AI model to be trained.

Step

With the annotated dataset, proceed to train the AI model. During this training phase, it's crucial to fine tune the AI by continually testing it with various images until high accuracy is achieved. This feedback loop process is vital for enhancing your AI model's accuracy.

Step

After finalizing the model, deploy it to your on-premises server or a cloud server, depending on your needs and IT policies. Establish a server setup and deploy the AI accordingly.

Step

Integrate the AI model with cameras already installed along your production or assembly line. Depending on your requirements, you might need high-resolution cameras for detailed image processing.

In some instances, it may be necessary to conduct pre-processing before you send them to the AI or post-processing of the images received from the AI model to reach the desired accuracy or objectives.

Tailored Solutions for Complex Challenges

We believe in facing challenges head-on. For highly complex or unique manufacturing problems, our team is ready to develop fully customized AI algorithms. Our passion for innovation drives us to deliver solutions that not only meet but exceed your expectations.