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Visual inspection and Image processing using AI

AI visual inspection and image processing are offering a solution to many repetitive tasks. This new technology is especially valuable in the manufacturing industry.

In the manufacturing unit, there are various tedious processes of grading, sorting, and processing materials. You will have a more thorough understanding of the benefits of automation. But the automatic systems haven’t been implemented properly due to limitations of sensory. This condition is starting to change as computer technology evolves through the use of artificial intelligence advances and machine learning. Now, let’s look into the reasons why AI image processing is useful for developing and established businesses.

Deep Learning In a Visual Inspection

 

Visual inspection is a challenging stage in any manufacturing process. This is especially true for products with difficult characteristics, such as highly viscous parenteral solutions where air bubbles cannot be completely eliminated, making it problematic to differentiate them from particles. Those cases usually require long development and optimization times for vision algorithms before achieving a balanced operational level of detection versus false reject rates.

 

Artificial Intelligence has the potential of shortening this development period and optimizing the desired results more quickly—a classic win-win situation for both manufacturers and the consumers, who ultimately receive high-quality products.

 

With visual inspection technology, integration of deep learning algorithms allows differentiating parts, anomalies, and characters, which imitate a human visual inspection while running a computerized system. 

 

Deep learning is a facet of machine learning technology that’s powered by artificial neural networks. The operating principle of deep learning technology is teaching machines to learn by example. With dispensing a neural network with labeled examples of specific types of data, it’s possible to extract common patterns between those examples, and then transform it into a math equation. This helps to classify future pieces of information.

 

Using Faststream Technologies deep learning-based computer vision technology powered by AI in the Manufacturing units the production cycle can be optimized by automating material quality inspection. The main purpose of it is to minimize human intervention and at the same time reach human-level accuracy or more as well as optimize factory capacity, labor cost, etc. Our usage of deep learning has varied, from object detection in self-driving cars to disease detection with medical imaging. Deep learning has proved to achieve human-level accuracy & better.

 

Overall, Faststream’s Automatic optical inspection solutions based on image analysis are finding production environments where quality inspections are required.

 

 

Optical Grading

 

From the last few years, various industries have used cameras to monitor and sort produce such as fruit, vegetables optically, and fish. However, The whole system required a certain level of human involvement as the previous image analysis algorithms were dependent on tuning that had to be performed by human operators.

 

With the use of Faststream Technologies AI image processing, optical grading, and sorting can become exponentially faster, operate autonomously, and become more accurate.

 

These systems are good for a range of high-quality inspection processes, allowing them to grade and sort products accurately. Here are some examples:

  • Nuts and seeds
  • Timber products
  • Fruits and vegetables
  • Recycled and virgin plastics

 

Robots With the Ability of Sight

 

The advances of AI image processing and objective tracking can be implemented with the help of Robotic vision. Robotic vision helps in navigation and mobility, like moving materials around a warehouse.

Faststream Technologies is working on  Robotic image processing technology using machine learning software, which helps the Robots to study accurately the environment and make the correct reactions to the various events and features they encounter.

 

AI Visual Inspection and Image Processing Solutions in Manufacturing and other industries

 

Nowadays the AI image processing has been used by several experts within the manufacturing, finance, health, and other industries.It can incorporate the complete repetitive tasks without enervation as it has the ability to quickly analyze information faster than the human eye.

By implementing Faststream’s AI Image Processing Solutions within your own organization you can improve your productivity, reduce the number of mistakes, and can be managed by you and a team of developers.

 

Application of Visual Inspection

 

Visual inspection is used in manufacturing for quality or defect assessment, in non-production environments, it can be used to determine whether the features indicative of a “target” are present and prevent potential negative impacts.

 

Several Areas where Visual Inspection and Image Processing using AI can help to identify the defects :

 

  • Inspect Automobile Parts for Defect
  • Identify Defective Product on your Assembly Line
  • Inspect Car for Surface Defects
  • Detect Defects on VLSI Wafers
  • Inspect unwanted Air Bubbles on Pharmaceutical Products
  • Inspect the unintended ingredients or physical contaminants on food and beverages.

 

 

Industry Targets Defects
Automobile Parts Material Parts, Resin Parts, Fabrics Scratch, Cracks, Dirt, Dent
Electronic Parts PCB, Electronics Parts, Electronic Components, Panel Scratch, Crack, Burr/Chip
Building Material Wood Board, Sash, Metal Fitting, Tile Surface Pattern, Scratch Crack, Dirt, Dent
Non-Ferrous Metals Wire, Cable,  Aluminium, Stainless Steel Scratch, Cracks, Dirt, Dent
Raw Material Chemical Fibre, Rubber, Glass, Paper, Pulp,  cratch, Cracks, Dirt, Dent
Medical Medicine Foreign Object, Wrong Print, Crack
Food Processing Food, Beverages Foreign Object, Wrong Print, Leak
Others Material Parts, Resin Parts Defect Classification, Shape Check

Benefits of Implementation of Faststream’s AI for Visual inspection and Image processing

Imprecision of eyesight

The human eye is incapable of making precise measurements, especially on a very tiny scale. Even while comparing two similar objects, the eye might not notice that one is slightly smaller or larger than the other. This concept also applies to characteristics such as surface roughness, size, and any other factor that needs to be measured.

Imprecision of eyesight

The human eye is incapable of making precise measurements, especially on a very tiny scale. Even while comparing two similar objects, the eye might not notice that one is slightly smaller or larger than the other. This concept also applies to characteristics such as surface roughness, size, and any other factor that needs to be measured.

Cost of labour

Machine Vision has a very high optical resolution which depends upon the technology and equipment used for image acquisition.Compared to human sight, machine vision has a ‘wider’ spectrum of visual perception with the ability to perform observations in the Ultraviolet, XRay and Infrared regions of the spectrum as well.

Cost of labour

Manual inspection remains a costly venture due to the appointment of (multiple) trained individuals.

Better Perception Optimisation

Manual inspection remains a costly venture due to the appointment of (multiple) trained individuals.

Better Perception Optimisation

Machine Vision has a very high optical resolution which depends upon the technology and equipment used for image acquisition.Compared to human sight, machine vision has a ‘wider’ spectrum of visual perception with the ability to perform observations in the Ultraviolet, XRay and Infrared regions of the spectrum as well.

Faster

Observations as well as conclusions are made extremely fast, with the speed of a computer’s speed as measured in FLOPs and also, they result in precise calculations.

Visual Inspection and Image Processing