Tag Archives: Machine Vision

Robots with Eyes and Brain

In the manufacturing industry, a huge transformation is taking place—machine vision—and it is growing at astronomical proportions. This includes all types of machine vision. For instance, the market is expecting 3D machine vision to double in size during the coming six years. As of now, this technology is proving to be a vital component in many modern solutions for automation.

Several factors contribute to the increasing adoption of this technology in manufacturing. While there is greater demand for automation solutions as the industry grapples with labor shortages, the cost of automation has decreased tremendously—sensors, cameras, robotics, and processing power are now substantially cheaper—enabling greater deployment.

Technological performance has also jumped up a notch higher, and machine vision systems now have the ability to process substantial amounts of information within a fraction of a second. Finally, machine learning algorithms and advanced artificial intelligence are transforming the data collected by machine vision even more versatile, allowing manufacturers to better realize the power from those solutions. Incorporated into automation solutions, machine vision is now producing better outcomes.

The vision system of a machine is basically made up of a number of disparate parts. These include the camera, lenses, sources of lighting, robotic movements, processing computers, application-specific software, and artificial intelligence algorithms.

While the camera forms the eyes of the system, machine vision can have several types of cameras depending on the application’s needs. An automated solution may have various cameras with different configurations.

For instance, there can be static cameras, for placing in fixed positions. These usually have a more bird’s eye view of the process, useful in applications where speed is imperative. On the other hand, dynamic cameras placed on the end of robotic arms can come much closer to the process, resulting in much higher accuracy and detailed capture.

Another important aspect of the vision system is its computing power. This is the brain of the system that helps the eyes (cameras) to do their work. Computation resources, coupled with machine learning algorithms, must not be confused with traditional machine vision applications. Companies offering machine vision capability also offer software libraries for implementation.

While manufacturers design their systems specifically for application users, others offer them targeted toward software programmers. Ultimately, the software provides the machine vision system with advanced capabilities offering a dramatic impact for manufacturers. Programs are available for control of tasks along with the ability to provide feedback from the line with valuable insights.

Machine vision-guided systems are gaining steam as a concept for replacing basic human capabilities. For instance, machine vision for assembly lines enables an increasing range of processes and applications.

Typical applications of machine vision include assembly processes for power tools, medical equipment, home appliances, and industrial assembly lines. Most assembly steps in the fabrication of electronic equipment can benefit from the use of machine vision, as it offers a substantial increase in the level of precision achieved.

For instance, machine vision improves inspection of component placement of tiny surface mount components on printed circuit boards before they go for soldering. It improves the line throughput, while not succumbing to fatigue as a human inspector would.

Astronomical Growth of Machine Vision

Industries are witnessing rapid growth of machine vision. This technology being a vital component of the industry’s modern automation solutions, they expect the market for 3-D machine vision to nearly double in the next six years. In the manufacturing context, two major factors contribute to this increase in adoption of the machine vision technology. The first is due to the industry facing acute labor shortage problems, and the second is the dramatic decrease in hardware costs.

Additionally, with an increase in technological performance, the industry needs machine vision systems to process ever-expanding amounts of information every second. Moreover, with the advent of machine learning and advanced artificial intelligence algorithms, data collected from machine vision systems are becoming more valuable. The industry is rightly realizing the power of machine vision.

So, what exactly is machine vision? What makes a robot see? A vision system typically is a conglomeration of many parts that include the camera, lighting sources, lenses, robotic components, a computer for processing, and application-specific software.

The camera forms the eye of the system. There are many types of cameras that the industry uses for machine vision. Each type of camera is specific for a particular application need. Also, an automation solution may have many cameras with different configurations.

For instance, a static camera typically remains in a fixed position in a scenario where speed is imperative. It might have a bird’s eye view of the scene below it. On the other hand, a robotic arm may mount a dynamic camera at its end, to take a closer look at a process, thereby picking out higher details.

One of the important aspects of the vision system is its computing power. In fact, this is the brain to help the eye understand what it is seeing. Traditional machine vision systems were rather limited in their computing powers. Modern machine vision systems that take advantage of machine learning algorithms require far greater computation resources. They also depend on software libraries for augmenting their computing capabilities.

Machine vision manufacturers design these capabilities specifically for application users. They design the software to provide advanced capabilities for machine vision systems. These advanced capabilities allow users to control the tasks for the machine vision, such that they can gain valuable insights from the visual feedback.

With the industry increasingly using vision for assembly lines, the concept of a vision-guided system replacing basic human capabilities is on the upswing in a wide range of processes and applications.

One of the major applications of machine vision is inspection. As components enter the assembly line, machine vision cameras give them a thorough inspection. They look for cracks, bends, shifts, misalignment, and similar defects, which, even if minor, may lead to a quality issue later. The machine vision compares the crack, and if larger than a specified size, rejects the component automatically.

In addition to mechanical defects, machine vision is capable of detecting color variations. For instance, a color camera can detect discoloration and thereby reject faulty units.

The camera can also read product labels, serial numbers, or barcodes. This allows the identification of specific units that need tracking.

Improvements in Machine Vision

The way consumers now interact with retailers, banks, and the hospitality industry, has undergone a sea of change. There are many self-service kiosks and ATMs for the consumers to interact, and this is undergoing a revolution. However, these improvements mean the back-end systems must undergo a huge improvement in terms of new hardware, firmware, software, and connectivity.

New businesses are getting the most out of their kiosks, with the role of machine vision creating a seamlessly connected experience for their customers. Initially, they had started with a software platform that helped customers execute their requirements more quickly. However, they realized very soon that machine vision could integrate software and physical-device designs.

Customers typically try to create or replicate a better experience. It is not just about pushing through quicker, building lines, or going through traditional use cases. They want to create a richer and more engaging experience with the minimum number of touches. They relish a more personal experience.

The businesses deploying the kiosks want to offer their customers a more seamless experience. Machine vision is playing a massive part in these applications in making the entire process seamless. For instance, postal services can be quite complex, such as when a customer needs to send a parcel through, and machine vision makes sure they fill out their forms the right way.

Machine vision has improved to the extent of recognizing handwriting. It can automatically detect the destination and verify the address. As the customer fills in the form, machine vision, along with the AI system, cleans and corrects the data as the parcel goes through. This ensures the parcel reaches its destination.

Another example is a kiosk connected to a retail bank. Tokenization distinguishes the customer’s skill level when they use the kiosk. This allows it to bypass any instructional content, taking the customer right to the point. That is what the customer expects—when they have used the kiosk once or twice—-they prefer a seamless experience.

Machine vision and AI applications are very useful during hotel check-ins. Most hotels look for a universal premium experience for their customers when they are using the kiosk service, like check-in, valet, or similar services.

Most cases such as the above require tightly integrated machine vision and AI solutions within their kiosk applications. Customers also expect the high-traffic kiosks to stay clean and safe to use.

For this, businesses are opening their kiosks to various options, such as finger and eye-tracking. These new techniques do not require the customer to physically touch the device. However, most customers did not quite adapt to the touchless techniques, and these did not add to their best experiences.

Therefore, businesses have developed advanced techniques like antimicrobial and heat-mapping touched areas on the kiosk. It uses AI and a combination of touchscreen and pressure sensors. With the presence of physical cameras on the screen, the kiosk allows the creation of a complete digital manifest of areas that others have touched. After a threshold, the kiosk shuts down, until a local attendant physically cleans it. The kiosk maintains a complete manifest of who cleaned it and when.