Learn the benefits of AI-based visual inspection & how industries can benefit by adopting the same. Read on to know more.
Are you still inspecting products the old-fashioned way? If so, you're likely missing out on some major benefits. AI-based visual inspection can take your business to the next level by making your production process more efficient and accurate. In this blog post, we'll explore what AI-based visual inspection is, how it works, and why you should make the switch today.
If you're ready to learn more about how AI-based visual inspection can take your business to the next level, keep reading.
AI-based visual inspection is a type of quality control that uses artificial intelligence to inspect products for defects. This process is typically done with the help of a camera, which is used to capture images or videos of the products being inspected. These images or videos are then fed into an AI system, which analyzes them and looks for any defects that may be present.
Traditional visual inspection is typically done by human inspectors, who manually examine products for defects. This process is often slow and error-prone, as it can be difficult for human inspectors to spot all of the potential defects in a product. AI-based visual inspection, on the other hand, is automated and much more accurate. This is because AI systems are able to analyze images or videos of products much more quickly and effectively than human inspectors can.
There are numerous benefits of using AI-based visual inspection, including:
If you're looking for a more efficient and accurate way to inspect your products, AI-based visual inspection is the way to go.
If you're ready to make the switch to AI-based visual inspection, there are a few things you'll need to do:
If you're ready to make the switch to AI-based visual inspection, follow these steps and you'll be up and running in no time.
Now that you know how to switch to AI-based visual inspection, it's time to integrate it into your workflow. Here are a few tips for doing so:
Follow these steps and you'll be able to integrate AI-based visual inspection into your workflow with ease.
AI-based visual inspection is the future of product inspection. If you're not using it, you're falling behind. Switch to AI-based visual inspection today and you'll be able to improve your product quality, increase your production rate, and reduce your costs.
Few real-world applications where AI-based visual inspection is making strides Visual inspection AI is primarily used to uncover defects, maintain quality standards, inventory management, and more. Here are a few examples of real-world applications of visual inspection AI:
The healthcare sector is always looking for ways to improve their security and safety standards with the help of artificial intelligence. AI-based visual inspection can be used in analyzing videos from surveillance cameras, which will allow them to identify any possible violations or hazards that pose risks to patients' well-being before it becomes too late. Hospitals can keep a close tab on confidential data and respond effectively to time-sensitive situations with this new technology.
Video analytics can provide real-time detection of objects, events, and incidents in a video. AI algorithms are then used to raise alerts for these unusual behaviors leading directly toward intelligence operations such as understanding visitor traffic within the facility or identifying instances when someone might have unauthorized access near restricted areas while being proactive about safety protocols forever more!
With the help of AI and deep neural networks, fire-prone zones can be monitored remotely for patterns. trends in activity that may indicate an accident is about to happen or has happened already; alarms will go off when these hazardous areas come close enough so their automatic shutoffs prevent any mishaps from occurring at crucial times like during surgery where lives depend on it being safe!
Hospitals are essential for the survival of any society, but they also have very specific needs that must be met in order to keep people safe. For example: A hospital building has certain safety requirements which extend beyond just being fully functional and include things like cleanliness or regular inspections depending on whether it's indoor/outdoor facilities. AI-based visual inspection can keep a tab on the maintenance schedule and raise alert based on compliance or non-compliance.
With AI, hospitals can monitor their patients in real time and detect any untoward incidents. This ensures that the patient is well cared for despite what happens; this way there will be no need to worry about anything happening without being noticed!
Hospitals are required to maintain a certain level of security, which can be compromised when equipment isn't stored appropriately. Hospitals have critical lifesaving items like oxygen tanks and heart bypass machines that need protection. An AI-based visual inspection system can keep a look out for any unauthorized users accessing these life-saving equipment and share visual proofs with respective authorities to take action when such an incident happens.
Hospital workstations are faced with the challenge of ensuring workplace safety in a pandemic situation. One solution that can help is AI-based Visual Inspection system, which facilitates monitoring and implementing protocols to ensure staff don't cross into dangerous zones when wearing their protective equipment, among other things such as tracking people's movements so they do not come too close together or engage one another without proper distance between them.
The world of aviation is one that requires extreme care and attention. Thanks to AI in transportation, specifically automated visual inspection systems powered by computer vision can be optimized to ensure the safety of people while increasing efficiency and reducing costs.
E.g., 3D.aero, the leader in automation for aerospace inspections and quality control says that their new AI-powered inspection system can examine combustion chambers within 4 hours and with greater accuracy than ever before. This is 80% faster than traditional methods. The team doesn't let its AI have the feedback loop of learning like traditional AI methods due to risks at stake. The feedback loop primarily relies on the kind of data the AI was able to learn from, the company wants AI to not learn from incorrect or biased data. So their in-house team carefully verifies the data before they feed it into the system to improve.
When it comes to the Corrosion Prevention and Control Program (CPCP), companies are adopting climbing robots to make sure the structural integrity is on point. These robots look for any surface defects, oil spills on the aircraft skin, corrosion, or rupture of components.
Overall, the Aviation industry is saving billions of dollars by adopting AI-based visual inspection to do quality maintenance.
In recent years, the automobile industry has also started utilizing ai-based visual inspection to find defects in the assembly lines and uncover misalignment or dents during the process.
E.g., Volvo has started using AI-based Atlas inspection system from UVeye. The system utilizes multiple cameras at the end of the assembly line to inspect any defects or dents on freshly assembled cars. Spokesperson from the company has also mentioned that this new ai-based visual inspection system has been highly efficient than their usual manual inspection methods. Any and all exterior defects/imperfections are immediately identified and displayed on large monitors for the technician's purview.
Since then many automobile manufacturers such as Honda, Toyota, Skoda, Daimler, etc have started to adopt AI based visual inspections.
Rolls Royce has also made quite some strides in this area. Usually rejection on goods received are due to what they refer to as “Soft issues” like:
Then they also have manufacturing defects, which they refer to as "Special issues" like:
One of the crucial components in computer manufacturing is the semiconductors used across the peripherals. AI-based visual inspection is helping the production of these semiconductors yield better and faster output. The ability to automatically detect wafers and eliminate defective parts has now become a normal routine in these manufacturing plants.
In recent years we have also seen the kind of economical impact semiconductors can have across the world. Shortage of graphics cards, processors, and gaming devices has made the price to sky-rocketed and even opened up dark zones for scalpers and in the end, the consumers had a hard time procuring them.
To solve these issues the production has been ramped up 2x and for some critical parts 10x. They were able to meet this demand thanks to systems like AI-based visual inspection. The cameras mounted on top of the microscopes record, analyze and segregate the defects and manufacturers can further pick up insights from the data to make better decisions on parts procurement.
There has been great demand in fashion and in extension to the textile industry. To adhere to large-scale production, the textile industry has adopted AI-based tools at every stage. Whether it is spreading, cutting, stitching, or even color matching, texture, or weaving.
We can see AI-based visual inspection tools been used for:
Solar panels are known to suffer from cell matching defects, cracks, discolorations, delaminations, hotspots, soiling, and even snail trails. To detect these issues in a large scale production, companies have adopted a combination of drone and AI technology.
The imagery captured using these drones are then processed in real-time using computer vision to identify these issues. The data process from these RGB and Thermal infrared images has been helping the solar industry process the data 50x times faster than traditional methods.
Identifying issues in Gas and Oil pipelines is a daunting task but well worth the cost. Implications from spills and leaks from these pipelines can be hazardous and sometimes even disastrous. Like the solar industry, the pipeline industry has been using drones and computer vision to solve this issue at scale. They primarily solve:
This is only the beginning of what AI-based visual inspection can do across industries. As we make great leaps in making AI accessible for end-users, the adoption and application will ramp up. We are yet to witness the age of AI showing its full capability.
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