Industries
Plastics Processing
SIT offers numerous advantages over traditional quality control methods in plastics and rubber manufacturing, including higher accuracy, consistency, and speed. This leads to increased efficiency, reduced costs, and improved product quality.
The result, for example, in injection molding, is influenced by a number of factors, including the raw material, the quality of the mold, temperature, pressure, speed, etc., which leads to the occurrence of defects. These defects can include various types of stains, burrs, inclusions, voids, or cracks.
Our AI software consists of several modules capable of identifying such defects, detecting missing parts, and reading and verifying all characters and symbols. It can even detect defects such as stains, micro-voids, cracks, or inclusions that are difficult to identify manually or by a rule-based system because they are too small or hard to recognize. Furthermore, for cases where the shape of the defect is difficult to predict, our software offers the Anomaly Detector module, which requires only a few defect-free images for training, thus significantly saving costs in defect image generation.
Metalworking
Metalworking processes are susceptible to defects, some of which are barely visible to the human eye and often not suitable for manual inspection. Furthermore, manual inspection is time-consuming, and the results are often inconsistent. AI-based visual inspection, on the other hand, not only offers economic advantages but also improved quality and consistency.
Our AI software has already been successfully used in various production steps of metal processing, from incoming material inspection to assembly and packaging inspection. Its reliable visual inspection, based on advanced deep learning algorithms and a neural network, easily finds anomalies and detects and classifies defects, including cracks, scratches, sand inclusions and blowholes, corrosion defects, stains, and many other defects or imperfections.
Textiles and other fabrics, leather, films and sheets
Our AI software learns to understand the product using a series of images and is able to find anomalies, detect and classify defects, and check the integrity of surfaces. It is well suited for inspecting textiles and other woven and knitted fabrics, nonwovens, leather, plastic or rubber films, filter media, paper, surgical drapes and many other materials.
The Anomaly Detector module identifies defects of previously unknown shape, pattern and size. In addition, the results are not affected by irregular patterns on the fabric, as the pattern is learned and recognized, which can be difficult with manual inspection. For clarity, the defect is always highlighted with a heatmap.
Pharmaceuticals & Cosmetics
Visual inspection and quality assurance with our AI software based on proprietary deep learning algorithms and neural networks has become an indispensable tool in the pharmaceutical sector. It ensures product quality, including packaging and seal integrity, sterility, and proper labeling, thereby contributing to regulatory compliance.
SIT offers a selection of tools to address many challenges in pharmaceutical manufacturing, including completeness checks and packaging integrity inspection, defect and contaminant detection, label reading and verification, and much more.
Building Materials
Deep learning-based visual inspection with our AI software is used for defect and anomaly detection on a variety of building materials, including paving stones, bricks, tiles or other floor coverings, glass and marble, as well as their packaging. It is very easy to set up, maintain, and operate.
Electronics Inspection
AI-powered optical inspection is becoming increasingly popular in the electronics industry, particularly in quality control. AI's ability to detect defects with a high degree of accuracy and speed has made it an attractive solution for manufacturers looking to improve product quality and reduce manual inspection costs.
SIT offers deep-learning-based visual inspection of electronic components and printed circuit boards (PCBs) to identify defects such as missing components, misaligned parts, soldering errors, and other types of manufacturing defects. The advantages of using our AI software include higher accuracy, speed, lower costs, and improved consistency. Another advantage is the ability to detect defects that are difficult or impossible to identify through human inspection. It is easy to use, set up, and maintain.
Request a free demo to experience the benefits of our software for yourself.
Food inspection
Deep learning-based visual inspection in the food and beverage industry significantly improves product quality and safety, preventing costly recalls while substantially increasing efficiency. Traditional inspection methods, such as manual inspection, are time-consuming, subjective, and prone to errors, leading to inconsistencies and potentially unsafe products reaching customers.
SIT uses proprietary deep learning algorithms and a neural network to accurately analyze large amounts of visual data in real time, detecting defects and anomalies that might be missed by conventional methods. Its modules can identify solid contaminants, check the integrity and completeness of packaging, verify that the correct labels are applied, read best-before/expiration dates, and much more.
Additionally, we offer lighting components that, for example, use UV or IR light to detect faulty food products with much greater precision.
Automotive
AI-based visual inspection has become an important part of the vehicle manufacturing process. What gave car manufacturers a competitive advantage a few years ago has now become a necessary part of the manufacturing process. SIT has formed cooperations with manufacturers to advance this topic.
From pre-shipment inspection by automotive suppliers or pre-assembly inspection in an assembly plant, which prevents costly rework later in the manufacturing process, to final inspection before a vehicle is shipped to the showroom, SIT helps reduce waste, improve product quality, increase productivity, and meet stringent vehicle safety standards.
Virtually every car part that requires visual inspection, including defect detection, completeness checking, product sorting, OCR or character verification, can be performed with our AI software.
Wood, Flooring, and Furniture
Due to the non-uniform wood structure, each piece is unique, making quality control of wood a challenging task. To overcome these challenges, SIT's deep-learning neural network learns to understand texture from a series of images, helping to determine if the required quality is achieved. It helps to sort wood by quality and determine the suitability of each individual piece for a specific application, which significantly increases speed and consistency while reducing inspection costs.