A picture is worth more than a thousand words. This time-tested maxim illustrates how effective the use of visual explanations can be for conveying complex ideas. It has become increasingly relevant in the manufacturing environment, as the adoption of digital technologies has accelerated. Manufacturers are turning to digital technologies like Industrial Internet of Things (IIoT) applications to paint a picture of their operations to drive improvements in productivity and quality using data collected from their factory floor. Over the next decade, manufacturers are estimated to capture approximately $4 trillion of value from IIoT applications through increased revenues and reduced costs. This value is not easy to realize when the problems are complex and require the observation of countless variables. When traditional sensor technologies fall short of the mark, manufacturers turn to machine vision technology to literally capture a picture that can tackle these problems.
Machine Vision Explained
At their foundation, machine vision systems consist of a camera and a computer or a microcontroller. An image is captured and depending on its quality, may undergo a series of pre-processing events like rotation, brightness enhancement, and image restoration to enable further analysis. Then, software toolsets are employed for use case-specific processing like segmentation and feature recognition to create actionable data points. These datasets are interpreted by analytics tools to inform decisions and trigger programmable logic controllers (PLCs), dashboards, and robots to perform actions like rejecting a part or displaying a warning.
The potential of these systems is vast, as the principal limiting factor to their use is that the key insights they are deployed to find must exist somewhere in the camera’s line of sight. Given the widespread applicability, the unique value of these systems is not in the ability to capture an image, but rather in the algorithms that process those images for a more transparent view of the factory floor.
A Vision Of Quality And Authenticity
One of the most common applications of machine vision systems is in quality assurance and control. Before the digital transformation in manufacturing, trained operators manually inspected parts on the line for defects and compliance.