Inspecting equipment, products and materials with the human eye is the oldest and simplest form of visual inspection. It is still used today in manufacturing, the energy industry and the medical field because it has proven to be an effective method for detecting surface-level defects.
In the pre-digital era, inspectors were trained to identify defects, sometimes with the naked eye, and in other cases, using the simplest of tools, such as lights and magnifying glasses. With the advancement of portable, high-quality cameras and drones, visual inspection has evolved to a new stage; today, companies collect digital images and videos of machinery, manufactured products and other aspects of physical operations to conduct visual inspections. Inspections with video footage and imagery can be done in real-time from a remote location or reviewed at a later time once the camera collecting imagery has been retrieved.
Software that leverages artificial intelligence (AI) is also used today for visual inspection automation. By “teaching” a computer to read images and determine when they meet acceptable standards, companies can automate the visual inspection process, saving time and in some cases, improving accuracy. This could range from identifying corrosion on the tops of wind turbines to identifying faulty connectors within products’ electronics.
One example of integrating AI into visual inspection systems is in the automotive industry. Today’s car manufacturers use images and deep learning to quickly and consistently identify defects earlier in the production process.
With this technology, also known as intelligent visual inspections, organizations can conduct inspections faster, more accurately and cost-effectively across a wide range of environments. Employing machines to conduct visual testing, companies can keep people out of hazardous areas and confined spaces, such as storage tanks, protecting the safety of workers without sacrificing the benefits of visual inspection.
Visual inspection is a form of non-destructive testing (NDT). Nondestructive methods allow inspectors to assess a system or component without permanently changing it. In addition to visual inspections, NDT also includes inspection techniques such as emissions, radiographic, X-ray and infrared, and ultrasonic testing.
NDT is a term often used in manufacturing or industrial operations; however, it can apply to a number of other industries. For example, an X-ray to assess whether a person has a broken bone or a proofreader reviewing a document and indicating errors that need revisions would also be types of NDT.
Because visual inspections only look at the surface, organizations will often use them in tandem with other testing methods.
Every industry and organization will have its own process for conducting visual inspections. Yet, there are commonalities within the inspection workflows often found across visual inspection processes. These include:
Once a process has been established, organizations may use a variety of methods to carry out visual inspections, including:
Visual inspection has been used for many years to ensure quality and safety. In addition, it also offers these benefits:
When quality control and safety are paramount, visual inspection is used, and may be required, including in these use cases:
Until recently, visual inspection was a process that was difficult to automate. Computers had not yet caught up to the naked eye. Yet, the latest advances in AI capabilities have made automated visual inspection features more efficient and accurate.
A major hurdle engineers had to overcome is a computer’s inability to process the contents of an image. Computer vision helped solve this problem. This process enables computers to derive meaningful information from digital images, videos and other visual inputs. Not only can computers now process the image, but they can also generate data insights that can be used to take corrective actions or make recommendations.
Here are some capabilities computer vision offers:
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