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Your Industrial Automation Initiatives Are Incomplete Without Machine Vision (Demo)

While human vision is still preferred for qualitative analysis of complex industrial settings, machine vision systems are capable of driving a range of industrial tasks, including object recognition, optical character recognition, materials inspection, item counting, etc.

Speed, repeatability, and accuracy remain the cornerstones of machine vision technology. In the manufacturing industry, for example, machine vision systems can check over hundreds and thousands of parts in a minute. These systems are equipped with image sensors, lenses, vision processing and lighting capabilities, etc., to inspect even the most granular details of the object under consideration. The broad applicability of machine vision systems, therefore, makes them integral to industrial automation initiatives. Let’s discuss the technology in more detail.

What Is Machine Vision & Its Benefits

Machine vision is the process of automated inspection (visual) of manufactured goods using industrial cameras, lighting, and lenses. This real-time review driven by machine vision allows for rapid and accurate inspection of industrial components. It also pictures and analyzes each item that comes down the high-speed line to ensure quality control.

As such, machine vision helps detect problems and defects, verify product types, check the presence and absence of industrial components, carry out code reading, etc.

The worldwide market size of machine vision stood at $13.32 billion in 2021. The market is expected to grow at a CAGR of 7.7% from 2022 to 2030. With the growing demand for high-quality inspection as well as automation across industrial verticals, this market will soar through the ranks in the coming years.

There are several direct benefits of machine vision systems that positively influence production lines. Let’s discuss them.

Mitigates Human Errors

Although human-led inspection can be excellent for qualitative interpretation, there’s no doubt that it is fallible. Contrarily, machine vision successfully gauges the quality and quantity of products with accuracy, speed, and repeatability.

When machine vision systems are paired with high-resolution cameras, they can inspect minute object details that may otherwise go unnoticed. In addition, it can reduce operator fatigue as well as discrepancies between the operators. Overall, it greatly reduces the scope of disassembled goods and subpar parts.

Reduces Cost

Machine vision system improves manufacturing speed. It also scales down the required amount of labor to operate a piece of equipment. In addition, it reduces the rate of scrap to ensure fewer materials are wasted, which reduces overhead costs.

With machine vision, it is possible to fine-tune manufacturing processes to improve overall results. Especially when it comes to high-priced components, manufacturing requires precision, failing at which can cost fortunes. Thus, it is best to implement the required checks that come with a machine vision system.

Lowers Downtime

Machine vision safeguards parts from damage by mitigating physical contact between the test system and adjacent manufactured parts. It further reduces the fees and time needed to fix those mechanical components in case of wear and tear. As a result, operation times improve as machines require less attention. Ultimately, industries can meet production deadlines consistently and easily.

Boosts Throughput

When downtime is reduced, it automatically increases throughput. However, a machine vision system goes a step ahead to provide corrective commands faster than the trained operators. As a result, it reduces the scope of manual correction and stabilizes productivity levels.

Better Safety

As machine vision lessens human involvement during manufacturing, it also creates a safe work environment. Employees are not exposed to injuries while operating powerful and bulky machines. Likewise, they remain at low risk when it comes to exposure to harmful materials and products.

Detects Print Defects

Printing anomalies are often difficult to identify. However, with machine vision, you can detect incorrect shades, missing letters, and blemished prints quickly. A master image is fed as input and used to compare manufactured components. Any anomaly is immediately flagged.

Located Objects

Machine vision is also used for locating objects with robotic guidance. If the goal is to locate the position or an object, the information is picked up and processed to detect the accurate location.

Key Components of Machine Vision

Lighting System

The lighting system is the key component of machine vision. It maximizes contrast for features of interest and minimizes contrast for other parts. It requires varying light intensity, lighting style, and correct light source placement to achieve this. These parameters can significantly improve the ability of the machine vision system to consistently detect and measure features of the parts under consideration. Lighting options like strobe lights and LED lights are ideal examples of the same.

Optical System/Lens

Optical components of the machine vision system typically constitute a camera or lenses. The lens section establishes the field of vision or the 2D areas for making observations. The lens also determines the focal points and depth of focus. The selection of an optical system depends on the specific functions of the machine vision system.

Sensor

Sensors capture the light from an optical system and give it a digital look. In other words, sensors use CCD or CMOS technology to capture the light and convert it into pixels showing the presence of that light in various areas of the original product that is being observed. Sensors with a higher resolution produce images with greater pixels. Higher accuracy increases the accuracy of measurement.

Vision Processing

It takes data from digital images and uses typical software to perform specific functions to evaluate parts under observation. These are pre-programmed conditions defining the criteria for acceptance/rejection of the observed part. To that end, vision processing involves a series of steps, from acquiring digital images to establishing the result.

Communication

The communication protocol is the final element of the machine vision system. Its purpose is to deliver a useful output in a standard format, which provides a definite signal driving other components in production depending on the output of the system. System integrators assist by embedding signals of communication between machine vision systems and allied machines used.

Applications of Machine Vision for Industrial Automation

Pattern Matching

Machine vision also enables matching patterns, which allows automated systems to locate objects or related features. Without this software, robots or automated machinery cannot count, detect, locate, or even measure any part.

Presence/Absence Detection

Machine vision systems often look for objects within the visual field to detect the items that demand focus during an inspection. This allows concentrated focus on relevant objects only. Detecting the presence or absence of objects for quality control, inventory management, and other applications is essential.

Sorting

Since human vision has limitations in detecting shades and determining dimension variations, sorting becomes a challenge. Image processing systems can help with sorting thanks to programmable motors. These custom visual systems are integral tools for modern industrial practices.

The Bottom Line

As modern technologies are constantly evolving, more enterprises are focusing on versatility and tailored scope of work. Cloud computing, deep learning, data integration, and faster processors are introducing new machine vision possibilities. This trend will continue and influence ERP infrastructure positively.

Interested in learning more about how machine vision capabilities can streamline your industrial automation initiatives? Talk to an expert today!

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