The global plastic market size was valued at USD 568.9 billion in 2019 and is expected to grow at a compound annual growth rate (CAGR) of 3.2% from 2020 to 2027. Significant increasing plastic consumption in the construction, automotive, and electrical and electronics industries is going to be the main driving force of the market for plastic over the forecast period. With such a large industry, one of the largest concerns for organizations in the industry is quality check and assurance.
Many manufacturers know that problems tend to start at the beginning of a production line and defects can devastating consequences. Sometimes, defects are merely cosmetic and otherwise perfectly safe to use. In other cases, defects can result in damaging effects on the company, including customer product safety hazards and costly recalls.
The goal of automation has always been to produce high-quality parts as quickly as possible. It is unavoidable that some parts come out of lower quality, and the job of quality control is to ensure that those parts never make it into the end product or to the customer. Checking parts by hand requires a massive investment of both time and labor costs. Luckily, technology now makes it possible to inspect many plastic parts using machine vision.
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CHALLENGES FACED IN THE PLASTIC INDUSTRY
When your plastic parts lines are humming along at high-speed rates, an undetected defect can cause a lot of waste, literally in the blink of an eye. In most cases, the problem occurs at the beginning of the production line.
To the human eye, product moving down the line at those speeds is a blur and undetected defects will fill your fail bins at 30 fps as opposed to filling your production quota. Inspection tasks such as detecting flawed seals, fill levels, or flash defects require intelligent machine inspection systems to support competitive high-speed production demands.
The continuous material runs for surgical tubing in the medical field, or for wire and cable, applications can reach rates of 600 fpm. If a defective plastic product somehow makes it past your fail bins and into the market, your company could be looking at costly recalls, especially in cases of product safety hazards. To operate safely and profitably at 30 fps or more, high-speed machine vision is the solution.
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HOW MACHINE VISION SYSTEMS CAN IMPACT THE PLASTIC INDUSTRY
Machine vision inspection can pick up on minute variations between parts that a human would not be able to see, and can reject defective pieces with astounding accuracy. Depending on the application, machine vision inspection can determine the presence or absence of safety seals, cap heights, colors, proper alignment of parts, correct labels, and much more. Almost anything that can be seen by a camera can be used as a metric in a machine vision system.
For continuous material systems producing, for example, surgical tubing or wire, machine vision can inspect them for defects at a rate of above 600 feet per minute. When manufacturing plastic bottles, machine vision can:
- Inspect the seals of over 1000 bottles per minute
- Inspect both oval and round bottles
- Detect even small breaks and chips in the seal
- Ensure that all bottles of the same type are packed together (color sorting)
- Check that all labels are correct in both content (language) and location
- Can evaluate any custom metric your manufacturing requires
Imaging does not need to take place on the visible spectrum: thermal cameras and UV imaging are also valuable tools for inspecting seals.
The Machine Vision system stores data in a raw image form, making it inconvenient to access. AI Computer Vision not only provides the user with meaningful findings but, also stores the data in a binary format. It is easy to access and track real-time data and the user will get a detailed report on all the findings, including the defects he wants to know about in particular. The report can be availed anytime, anywhere.
Machine vision is also of a major utility in the automotive industry, where it can be used to detect breaks in mesh filters or perform dimensional analysis on plastic parts. With a 1.6-second cycle time, an ability to detect multiple types of defects, and a high rate of accuracy, machine vision is critical to making high-quality automotive parts.
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CONCLUSION
Machine vision systems save time and money in manufacturing. They remove a major source of human error, help prevent costly product recalls, and improve the overall quality of products. Machine vision systems also collect specific data on the types and numbers of defects found, which can give insight into problems in the overall manufacturing process. Machine vision inspection is a crucial part of a constantly improving manufacturing environment.
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