Industrial robots complete tasks such as painting, welding, assembly and product inspection with speed and precision. They don’t tire like humans and perform repetitive actions reliably without getting bored, 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 variation, as in typical ‘pick and place’ applications. These actions are determined by programmed routines that determine the direction, speed, acceleration, deceleration, and distance of a coordinated series of movements.
Other robots use machine vision systems to perform complex tasks, such as weld inspection and optimization in the automotive industry. This usually involves complex actions and sequences of movements, which the robot itself may even have to identify.
Machine vision systems comprise high-resolution cameras linked to powerful image processing software. They make for efficient handling and control, and work without wear and tear even under demanding manufacturing conditions. Machine vision systems achieve high success rates, and ensure smooth production without manual intervention or supervision, even in unpleasant 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 capture photographic images that contain width and length, but no depth. By processing these images, they measure the visible characteristics of an object, and feed robotic handling systems data on its position, rotational orientation, and type.
The automotive industry uses 2D vision systems to pick heavy gearboxes from cages, unload cylinder heads from wire mesh boxes, identify axle castings, and detect the position of slide bearing shells.
Automated 3D Position Detection
3D vision systems detect the position and shape of an object in three dimensions using specialised cameras and lasers. They determine the starting point, overall length and rotation of a component, and transmit this data to industrial robots for fast and efficient handling. 3D vision systems enable the automated, reliable handling of different sized objects.
A common application for 3D vision systems is the production of crankshaft castings in the automotive industry, where they instruct robots to position castings ready for the next stage of assembly.
Proper part assembly is essential to any manufacturing process. Poorly assembled parts lead to malfunctioning, unsafe products. Machine vision systems equipped with fast, fixed focus cameras and LED illumination continuously inspect parts during assembly to verify the presence of characteristic features, and instruct robots to remove defect items from the production line.
Characteristic features include screws, pins, fuses, and other electrical components. Machine vision systems also check for missing slots or holes, which can prevent proper assembly. Inspection takes just seconds, even with a huge variety of different parts, allowing manufacturers to maintain high levels of efficiency and productivity.
Machine vision systems for assembly inspection have a wide range of applications. These include checking vehicle components in the automotive industry, verifying fill levels in blisters, chocolate trays, and powder compacts, and ensuring correct label positioning on boxes.
Machine vision systems for contour inspection examine the profile of an object using high-resolution cameras and 3D sensors to ensure it is free from deviations (e.g. chips), which affect the shape and thus the function of the product. They also check measurements such as length, width, and radius to ensure they are within set parameters.
Pharmaceutical companies use machine vision systems in automated production lines to inspect injection needles, which are unusable if blunt or bent. Multiple cameras photograph needles as they flow through the system on powered conveyors. Sophisticated computer software analyses the captured images to determine needle sharpness and check the contour of the tube. Industrial robots use this information to separate and discard defect needles.
Injection needles’ size makes them almost impossible to inspect with a naked eye. Machine vision systems can inspect 40 needles per minute with 100% accuracy, speeding up production and reducing costs. Other contour inspection applications include concentricity checks of spark plugs for petrol engines, the measurement of coating structures on capacitor foils, and tooth inspection of saw blades.
3D Seam Inspection
Poorly welded components break, causing products to fail. In the case of automobiles and aeroplanes, this often has disastrous consequences and costs lives. Robotic weld seam inspection and optimization is now the standard in many industries.
Machine vision systems for weld inspection comprise a sensor mounted on a robotic arm. A laser in the sensor projects a line of light across the surface of a component joint, a technique known as laser triangulation. At the same time, a high-speed camera, also housed in the sensor, captures an image of the line as an elevation profile. Through the relative motion of the component and the sensor, the system builds a 3D image of the welded seam surface.
Using this image, a computer checks the seam’s consistency along its length. It accurately detects imperfections like profile variations and pores, which weaken the joint, and instructs a robotic burner to rework or repair seams if necessary.
Machine vision systems store inspection results in a database along with serial numbers, which makes components easy to trace. They work on multiple seams of different types, shapes and sizes, and operate at high speed. The automotive industry uses automated weld inspection and optimization systems extensively to ensure vehicles are of high quality and safe to drive.