The manufacturing environment is defined by its ability to manufacture goods using assembly lines and machines. Factories should have the main intent to reduce costs, increase production efficiency, and reduce hazards. This can be achieved by integrating robotic automation within their production process. In order to achieve true automation, however, a robot needs to know what it is working with, along with its physical measurements in order to perform its instructed tasks. Such applications include but are not limited to identification, measurement, positioning, flaw detection, etc. This can be done through the use of robotic inspection, or machine vision. Machine vision uses sensors and software algorithms to complete visual tasks and guide the equipment during product assembly.
There are different technologies available for automated measuring/inspection installations. Each of them with its own advantages and disadvantages based on the environment they are subject to. It is important to understand that the technology chosen is dependant on the material/object under inspection. Below is a list of the most commonly used inspection technologies:
- Vision Systems
- Measurement Sensors
- Optical Comparators
This week’s post will be part 1 of 3, where we will highlight the capabilities of Vision Systems and their applications in the industry. The remaining topics will be discussed in posts to come.
Vision systems use your typical sensors to detect if an object is present. If the sensor is triggered, a camera will capture an image. Then, depending on the machine’s software, it will determine whether or not machine instructions will take place based on the reference image captured. Depending on the application, manufacturers have two choices with regards to vision systems: 2D or 3D.
2D machine vision uses a camera to capture images of an object and can detect variations in contrast. Applications that involve 2D vision systems can include label orientation, barcode reading, defect detection, pattern or color inspection, etc. 2D vision systems are well known in the automation industry for their simple and effective inspection capabilities. As you would expect, 2D machine vision limitations include ambient lighting, contrast variations, and parallax.
3D vision systems are capable of sensing the height of an object. This type of vision system has multiple ways to create a 3D image. These include the use of multiple cameras which splice images together, structured light projectors which sense optical patterns and captures an ideal image, and laser triangulation to follow the profile of an object and create a digital geometry. Recently, manufacturers have begun to use 3D machine vision more due to its more accurate dimensional data. By using 3D vision, a robot can also sense variations in its physical environment and adapt accordingly. This feature is extremely useful for bin picking robots where objects are in random poses located in a container like a box. Hence, the majority of industrial robots work in the three-dimensional world.
Vision Systems are very capable of performing robotic guidance. By using the processes stated above, guidance systems can locate the position and orientation of a part, and compare it to a tolerance that takes into account the contrast, lighting, scale, rotation, etc. In other words, 2D and 3D systems can locate an object anywhere within the vision range of the camera, and perform programmed robotic instructions accordingly.
A few benefits vision systems present are listed below:
Vision systems have the capability to notice when there are errors or discrepancies between products. This could include incorrect physical structure (damaged or manufactured wrong), mislabeling of the products, etc. These errors cost manufacturers money when needing to replace or recall product.
Some manufacturing environments still rely on human inspection of products. With automated vision systems, products can be accurately inspected. This will save time and money while still maintaining a strict schedule. Vision systems can also increase efficiency by analyzing products as they move down production lines. An example could be as a product comes off the assembly line, it may be in different position orientations. Through machine vision, and the correct software, a machine would know where to grab or position the product to correctly manufacture or package it.
That concludes the content for this week’s post on Robotic Inspection Installations. In later posts, we will touch on the remaining two topics stated above. Please feel free to contact us regarding any of the stated material, or if you have questions about our products: https://diy-robotics.com/contact/.