Automated Visual Inspection Software
Automated Visual Inspection (AVI) is a form of quality control, which involves the analysis of products in the production line with computer vision.
Since 2013, ScienceSoft develops AVI software to help companies improve defect detection rates and reduce production costs.
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Why is AVI better than manual inspection?
Machine vision has a number of advantages in comparison with human vision:
Besides that, the automated visual inspection systems have several pros that are intrinsic to the entire machine kind:
AVI Software Use Cases
Ensuring high production quality by reducing both false positive and false negative test results.
Production Line Automation
Minimizing efforts required for defects detection through the automation of monotonous visual inspection, grading and sorting tasks.
Why Choose ScienceSoft as Your AVI Partner
AVI Software We Build
AVI system structure
- Equipment for image acquisition (lighting or a radiant; a digital camera, photometer, colorimeter, etc.), software running (a processor) and data output (monitor, printer, etc.).
- Supplementary equipment (e.g., for grading and sorting).
- Software that processes digital images and produces a valuable output.
explore the processing chain of the AVI system
ScienceSoft creates AVI software that analyzes images captured by a digital camera, starting with preprocessing and up to the final decision step.
AVI software functions
- Displaying inspection results.
- Automatic discarding of defective items.
- Marking items for further human inspection.
- Sorting and grading objects according to predetermined parameters (shape, size, color, etc.).
Image analysis capabilities of AVI software
Automated visual inspection software developed by ScienceSoft can detect and classify:
- Surface defects: scratches, stains, nodules, etc.
- Positioning and orientation: correctness of assembly components’ orientation.
- Dimensions, shapes and angles.
- Completeness: components on a printed circuit board, barcodes on a parcel, a filling level of a bottle.
- Color and reflectivity.
- Presence of foreign objects.
Our Hallmark AVI Projects
Development of Automated Visual Inspection Software for Defect Recognition in Polyurethane Film
ScienceSoft built image recognition software for improving quality control at the Customer’s PU film manufacturing division by detecting film defects in real time.
Development of Defect Recognition Software for an Oil Drilling Equipment Manufacturer
ScienceSoft empowered a manufacturer of oil drilling equipment with the defect-recognition application used to detect drill bit defects and perform drill bit wear analysis.
Development of an Automated Visual Inspection Mobile Application for a Luxury Vehicles Manufacturer
ScienceSoft delivered an image recognition solution that allowed the Customer to speed up user registration in the customer service system by 10 times.
Design on an Image Analysis Application for Remote Monitoring of Oil Storage Tanks
ScienceSoft designed an image analysis application to help optimize inventory management and detect oil leakage by remotely monitoring oil storage tanks in real time.
Development of Image Analysis Software for Automated Optical Inspections
ScienceSoft enabled automated optical inspection of printed circuit assemblies (PCA) with the application that enhanced the PCA manufacturing workflow, saving time and meeting the highest quality standards.
Development of an Automated Visual Inspection Application for LED Display Quality Diagnostics
ScienceSoft developed a cross-platform application for Linux and Windows for real-time video monitoring, error detection and notification.
Technologies We Apply
Libraries and frameworks
Cloud databases (DBaaS)
Google Cloud Platform
AWS: Amazon Rekognition
GCP: Google Cloud Vision API
Azure: Computer Vision, Face, Custom Vision, Form Recognizer, Video Indexer, Microsoft Emotion API
Convolutional neural networks
Support Vector Machine (SVM)
Scale-invariant feature transform (SIFT)
AVI Challenges ScienceSoft Solves
For complex objects, significant variations exist in the appearance of both normal and defective items.
Check out the solution
The decision-making part of the AVI system is based on machine learning methods. In order to learn how to distinguish between normal and defective objects, it needs a large dataset of possible variations in their appearance. Having enough data to train the machine learning algorithm, we can ensure its ability to make accurate decisions.
Very small and non-distinctive details
Recognizing features and objects may be difficult if they have a very small size (such as PCA components) or melt into the background (a grey caption on a grey background).
Check out the solution
Depending on the task, our specialists will implement advanced image preprocessing, segmentation and feature extraction techniques to machine vision software to enhance the image and extract valuable information.
Changes in the illumination affect the resulting images creating new lines and disguising existing ones.
Check out the solution
- Ensuring uniform lighting conditions
- Implementing advanced machine learning algorithms.
If uniform illumination is not available, it is possible to mitigate the effects of bad illumination using more sophisticated preprocessing and edge detection algorithms.
Build AVI Solutions with ScienceSoft
AVI consulting services
- AVI solution design.
- Business case creation.
- AVI software architecture (re)design.
- Outline of optimal implementation options.
- AVI software features roadmapping.
- Project planning.
- PoC and prototyping (if required).