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Machine vision will become one of the key components of Industry 4.0 and the Internet of Things

 Last Update: 2021-10-11
 Source: Internet
 Author: User

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[ Hot attention from Chemical Machinery Equipment Network ] Machine vision combines machine learning with a series of tools to give consumers and commercial-grade hardware new capabilities to observe and interpret the environment
.
In the industrial environment, these technologies, together with automation and higher-speed networks, constitute a new industrial revolution-Industry 4.
0
.
They also provide a new way to develop low-waste, high-efficiency industrial activities
.

Chemical machinery and equipment network hotspots pay attention to chemical machinery and equipment

Now that machine vision has begun to take shape, companies all over the world are exploring the benefits it brings
.

Machine vision affects manufacturing, drilling and mining
.
There are other advantages in freight and supply chain management, quality assurance, material handling, safety, and various other processes and verticals
.

In the near future, machine vision will be ubiquitous, adding a key layer of intelligence to the Internet of Things built in the industrial world
.
Let's take a look at how the company puts it into practice
.

What is machine vision?

Machine vision is a set of technologies that allow machines to better perceive the surrounding environment
.
It facilitates higher-level image recognition and decision-making based on that perception

To take advantage of machine vision, an industrial device uses a high-fidelity camera to capture digital images of the environment or workpiece
.
The image can be taken in an automated guided vehicle (AGV) or a robot checkpoint
.
From there, machine vision uses extremely complex pattern recognition algorithms to determine its location, identity or condition
.

　　In manual inspection, achieving the correct lighting is a key factor for the correct realization of machine vision
.

　　There are several common light sources in machine vision applications, including leds, quartz halogens, metal halides, xenon, and traditional fluorescent lamps
.
If the barcode or part of the workpiece is obscured by the shadow, the reading may be transmitted incorrectly when there is no barcode or workpiece, and vice versa
.

　　Machine vision combines cutting-edge hardware and software to enable machines to observe and respond to external stimuli in novel and beneficial ways
.

　　How does machine vision support business and industrial IoT?

　　The popularity of Industrial Internet of Things (IIoT) devices marks an important moment for technological progress
.
IIoT provides enterprises with new operational visibility from top to bottom
.
Network sensors and cloud-based enterprise and resource planning hubs provide two-way data mobility between local and remote assets and business partners
.

sensor

　　The bidirectional mobility can be as small as a mechanical piston or bearing
.
It can also be as large as a truck fleet and can generate valuable operational data using the right IoT hardware and software
.
Companies can be seen everywhere, even if they are short of resources or labor
.

　　The Internet of Things first represents ubiquitous computing
.

　　Where does machine vision stand in all this? Machine vision makes existing IoT assets more powerful and can better deliver value and efficiency
.
We can expect it to create some brand new opportunities
.

　　• Make the sensor more useful

　　Machine vision makes the sensors in the entire Internet of Things more powerful and useful
.
Sensors do not provide raw data, but provide a level of interpretation and abstraction that can be used for decision-making or further automation
.

　　• Reduce bandwidth requirements

　　Machine vision may help reduce the bandwidth requirements for large-scale IoT expansion
.
In contrast to capturing images and data at the source and sending them to the server for analysis, machine vision usually conducts research at the data source
.
Modern industry generates millions of data points, but thanks to the help of machine vision and edge computing, it can generate a lot of actionable insights without needing to be transmitted to auxiliary locations
.

　　• Support IoT automation solutions

　　Machine vision complements the automation technology of the Internet of Things very well
.
Robotic checkpoints can work faster and more accurately than QA employees, and when defects and abnormalities are found, they can immediately provide decision-makers with relevant data
.

　　• Improve the safety and practicality of robots and collaborative robots

　　The navigation system built with machine vision enables robots and collaborative robots to have greater autonomy and pathfinding capabilities, and helps them work faster and safer with humans
.
In warehouses and other environments where there is a risk of error, machine vision can help robot pickers reduce response time and limit defects that may cause business losses
.

　　• Make more understanding between assets

　　The economy of today and the future requires companies and industries to operate while reducing waste of time, material resources and labor
.
Machine vision will continue to enable drones, material handling equipment, unmanned vehicles and pallet trucks, production lines and inspection stations to better exchange detailed and valuable data with other parts of the network
.

　　In a factory environment, this means that machines and personnel can better coordinate their work without bottlenecks, overruns and other failures
.

　　How do companies apply machine vision?

　　When you consider every step involved in a typical industrial process, it is not difficult to find that machine vision can improve every aspect of operation
.

　　In order to manufacture a single car part, humans and machines collaborate to obtain raw materials, evaluate their quality, transport them to the factory for processing, and deliver these products to the factory at each manufacturing stage
.
In the end, they successfully saw it through the QA process, and then went out again, where at least the last part of the process was waiting for it
.
Later, the retailer or end user will receive it
.

　　Whether the product is in a static state, in transit or not yet assembled, machine vision provides a way to automatically process the product
.
It improves the efficiency of each department (such as assembly) and maintains a higher and more consistent quality level
.

　　In the real world, companies have added machine vision to their workflow
.

　　Some applications are simple, such as placing a production line on the floor of a warehouse to allow unmanned vehicles to follow safely
.
Other machine vision tools are even more complex, although even very simple examples can change the rules of the game
.

　　In the industry, the most exciting examples of machine vision include tasks that were once considered difficult or impossible to outsource to robots
.
As mentioned earlier, picking from the trash bin in the warehouse is a process, and when it comes to errors, it has inherent risks
.
Errors in the performance process can cause losses to goodwill and customers
.

　　Considering that product damage, item location and slight changes in SKU are the biggest sources of errors in this field, machine learning box picking is a natural choice
.

　　Today, nearly 100% of automatic picking robots are available.
They can safely navigate, check parts and products in trash bins, use robotic arms for correct picking and transport picking to assembly or packaging areas
.

　　Ultimately, this means that the company has much less risk when shipping damaged goods or the wrong SKU that appears to be ordered by the customer (but does not exactly match)
.

　　Automated quality assurance and inspection is another aspect of machine vision and IoT, which is rapidly gaining popularity
.

　　In some modern manufacturing environments, it can help employers automate and improve the results of the QA process without even sacrificing manpower
.
In contrast, automated inspection stations handle these high-priority tasks, while employees learn more skills that require cognitive abilities
.

　　By 2025, assisting robots are likely to account for 34% of all robot sales
.
This is largely due to improvements in machine vision and efforts to eliminate as much as possible the inefficiencies, inaccuracies and waste in modern industry
.

　　Machine Vision and the Fourth Industrial Revolution

　　It is expected that machine vision will continue to develop in the next few years and make further contributions to Industry 4.
0, which many people call the fourth industrial revolution
.
People have begun to pay attention to new low-cost products for embedded and board-level image processing with machine vision capabilities
.

　　Machine vision capabilities will enable wider adoption of the Internet of Things and machine vision, and provide new ways for companies to use digital intelligence
.

　　Original title: Machine vision will become one of the key components of Industry 4.
0 and the Internet of Things

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