Industrial robots quickly and accurately perform tasks such as painting, welding, assembling and testing products. They do not get tired like people do, and reliably perform repetitive actions without embarrassment, which leads to high productivity at low costs. These attributes make industrial robots invaluable to manufacturers in many industries.
Some industrial robots perform repetitive actions without changes, for example, in typical variants and locations, Applications. These actions are determined by the programmed programs that determine the direction, speed, acceleration, deceleration, and distance from a series of coordinated movements.
Other robots use machine vision systems to perform complex tasks such as welding inspection and optimization in the automotive industry. Usually they include complex actions and motion sequences that the robot can even identify.
High-resolution video surveillance systems associated with powerful image processing software. They provide effective management and control and operate without wear, even in difficult production conditions. Machine vision systems achieve high success rates and ensure smooth production without manual intervention or control, even under unacceptable environmental conditions.
Machine vision has a wide range of applications in industrial automation:
2D Robot Vision
2D-vision systems use line scan or area scan cameras to take photographic images that contain width and length, but do not have depth. When processing these images, they measure the visible characteristics of the object and feed the data of the robotic processing system to their location, rotation orientation and type.
The automotive industry uses 2D-vision systems to select heavy gears from separators, unload cylinder heads from wire mesh cells, determine axial castings and determine the position of sliding bearings.
Automatic detection of three-dimensional position
3D vision systems determine the position and shape of an object in three dimensions using specialized cameras and lasers. They determine the starting point, the total length and rotation of the component and transmit this data to industrial robots for fast and efficient processing. 3D-vision systems allow you to automate and reliably process objects of different sizes.
A common application for 3D-vision systems is the production of crankshaft castings in the automotive industry, where they assign robots to position castings ready for the next assembly stage.
Assembly check
Proper assembly of parts is necessary for any manufacturing process. Poorly assembled parts lead to malfunctioning unsafe products. Machine vision systems equipped with fast cameras with fixed focusing and LED backlighting constantly check parts during assembly to check for specific features and instruct robots to remove defective items from the production line.
Special features include screws, pins, fuses and other electrical components. Vision systems also check for the absence of cuts or holes that may interfere with proper assembly. Inspection takes only a few seconds, even with a huge variety of different parts, which allows manufacturers to maintain a high level of efficiency and productivity.
Machine vision systems for assembly control have a wide range of applications. These include checking vehicle components in the automotive industry, checking filling levels in bubbles, chocolate trays and powder compacts and ensuring that labels are properly positioned on the boxes.
Contour inspection
Machine vision systems for contour checking examine the profile of an object using high-resolution cameras and three-dimensional sensors to ensure that there are no deviations (for example, chips) that affect the shape and, therefore, the function of the product. They also check the measurements, such as length, width and radius, to make sure that they are in the specified parameters.
Pharmaceutical companies use machine vision systems in automated production lines to test injection needles, which are unsuitable for use if they are blunt or bent. Several cameras take pictures of needles as they pass through the system on powered conveyors. Sophisticated computer software analyzes captured images to determine the sharpness of the needle and check the contour of the tube. Industrial robots use this information to separate and discard defective needles.
Needles for injection. the size makes them almost impossible for inspection with the naked eye. Machine vision systems can test 40 needles per minute with 100% accuracy, speeding production and reducing costs. Other contour monitoring applications include checking the concentricity of spark plugs for gasoline engines, measuring coating structures on capacitor films and examining the teeth of the saw blades.
Checking the 3D seam
Poorly weldable components break down, leading to product malfunctions. In the case of cars and airplanes, this often has disastrous consequences and costs of living. Verification and optimization of robotic welds have become standard in many industries.
Machine vision systems for checking welding contain a sensor mounted on a robotic arm. The laser in the sensor projects a line of light over the surface of the component connection, a method known as laser triangulation. At the same time, a high-speed camera, also located in the sensor, captures the image of the line as a height profile. Due to the relative movement of the component and the sensor, the system creates a three-dimensional image of the surface of the weld.
Using this image, the computer checks the seam sequence along its length. It accurately detects imperfections, such as profile and pore changes, which weakens the joint, and instructs a robotic torch to reprocess or repair joints, if necessary.
Machine vision systems store test results in a database along with serial numbers, making it easy to track components. They work on several seams of different types, shapes and sizes and operate at high speed. The automotive industry makes extensive use of automated systems for monitoring and optimizing welding to ensure high quality vehicles and ensure their safety.
Conclusion
Machine vision systems have a wide range of applications in industrial automation. They enable industrial robots to perform complex tasks reliably and accurately and allow companies to achieve previously impossible levels of efficiency and productivity. Machine vision has improved significantly over the past ten years and is now important for many industries.
