AI cameras in manufacturing
To find out, let’s follow the journey of a product along the factory floor.
AI cameras
As the world demands smarter products in shorter time frames, all eyes are on factories. Can they deliver Industry 4.0 and its promise of fully digitized, automated production lines?
With the help of machine vision cameras – yes.
Vision is a form of artificial intelligence (AI) that uses industrial cameras to help machines see and understand things happening on the factory floor. Whether positioned above, among, or within manufacturing technology, AI cameras can help factories optimize their entire supply chain.
The most common camera types used in manufacturing include:
GigE (Gigabit Ethernet): High-performance cameras that quickly transfer images over long cable lengths.
Industrial USB: Connect to computers via USB and capture high resolution, low noise images. They’re often very small, making them cost-effective and easy to install.
Aerial: Provide a full view of the factory floor from above. Useful for mapping and monitoring the activity of people, products, and machinery.
Line scan: Capture the pixel lines of objects in motion – moving along a conveyor belt, perhaps – then combine them to form an image.
We recommend: The Tokay Pro
Cameras are integral to machine vision systems in manufacturing. That’s why we recommend the MaxLab Tokay Pro: RISC-V Edge AI Camera, which offers the lightning-fast efficiency and accuracy needed on today’s production lines. It can analyze images and make decisions in real-time, all on a high-performance edge computing chip, and connect to major IoT software for seamless factory management. Its small size and low-power consumption also make it a great fit for robotic systems that need to perform complex visual tasks.
To understand the role of AI cameras in manufacturing, let’s imagine we have a product. We’ll call it ‘Product X’. There are three main stages to Product X’s journey through the factory:
1) Assembly
2) Quality
3) Delivery
Breaking these stages down, AI cameras will help with the following tasks:
| Assembly | Quality | Delivery |
|---|---|---|
| Object detection | Defect detection | Packing and labeling |
| Measurement | Predictive maintenance | Track and trace |
| Guidance | Safety and compliance | Scaling |
Here’s how.
Assembly
Product X first needs to be put together. On the factory floor, AI cameras are often embedded in robots, giving them some autonomy in conducting precision manufacturing tasks including:
– Object detection
– Measurement
– Guidance
Object detection
Identifying and locating the parts needed to build Product X isn’t always straightforward. They can vary in size, shape, and complexity, and they may be moving between different working areas.
This is no trouble for AI cameras, though – they can find objects in the factory by their coordinates or position relative to a human operator, and handle them safely, as well as keep tabs on stock and inventory.
If the objects needed are mixed up with other items, machine vision systems can detect them by classifying and segmenting visual data using light and laser projection or Time-of-Flight imaging (which measures a light beam’s rebound time). This allows machines to count, pick, and sort objects in what would otherwise be a tedious and error-prone job for a human. AI cameras can even learn from this task to help machines handle objects they haven’t seen before.
Measurement
So that Product X doesn’t end up a misshapen mess, its parts are measured. Machine vision systems can analyze the images taken by AI cameras in 3D to calculate the length, width, volume, and surface area dimensions of parts to ensure they slot perfectly into place.
AI cameras measure time too. They can automatically figure out how long a production cycle will take and decide on the best time to start a new one – good news for a busy factory where multiple products may be vying for a space on the conveyor belt. This data can also be visualized using IoT software to help factories build highly accurate process models.
Guidance
Now to put Product X together. This is a task often delegated to robots, especially in dangerous environments. Armed with AI cameras, robots can weld, paint, and seamlessly assemble Product X over and over again, autonomously and without any downtime.
Quality
It’s vital that Product X is built properly, that it works, and that everyone is kept safe during the process. In terms of quality control, AI cameras can help with:
– Defect detection
– Predictive maintenance
– Safety
Defect detection
Product X could be tested in random samples, but why take a chance on the rest? If it’s defective and pushed along the production line anyway it can derail operations and put reputations on the line.
AI cameras can capture image and video footage to help vision systems trace defects back to a serial number, source, or point in time. Using techniques like hyperspectral imaging to measure wavelengths beyond the visible light range, AI cameras can automatically spot defective parts and products and help fix them or alert auditors for further investigation.
Predictive maintenance
Equipment can break too. It’s used day after day to manufacture vast amounts of products, often in harsh environments, and few machines are immune to repetitive strain. But acting too late can be expensive. If Product X was a car, say, it could cost the factory $20,000 for each minute of downtime.
AI cameras can monitor manufacturing equipment in real time. Thanks to deep learning models and techniques such as thermal and multi-spectral imaging, they can diagnose signs of deterioration, corrosion, deformation, overheating, leaking, and more, then make repairs or alert operators.
To do this, cameras themselves need to survive tough conditions. Therein lies the advantage of IP67-rated (water- and dust-proof) technology, such as the MaxLab waterproof AI camera module, which monitors outside weather conditions to help protect factory infrastructure.
Safety and compliance
Factories can be dangerous places, so it’s important to keep employees safe while Product X is being made.
AI cameras can monitor the entire factory and prevent pile-ups by routing autonomous machines away from objects and people, as well as detect the early outbreak of a fire. If an accident does occur, machine vision systems can measure its seriousness, raise the alarm, and direct staff to the right place while switching off any nearby production processes.
Using aerial cameras to track movement on the factory floor, machine vision systems can also help enforce environmental, safety, and security regulations. Are employees wearing helmets? Are they working in restricted or dangerous areas? Through image and pattern recognition, AI cameras can see if the rules are being flouted and alert staff. They can also bolster security by tracking suspicious people or objects around the factory and flagging them if certain threat parameters are met.
Read more on using machine vision with security cameras in our blog on smart parking lots.
Delivery
The work doesn’t stop yet – Product X needs to arrive at its destination in one piece. AI cameras can make sure it does so by helping to automate the following tasks:
– Packing and labeling
– Tracking and tracing
– Scaling
Packing and labeling
Most products need to be packaged up somehow, whether that’s in boxes, bottles, cartons, or pallets. To do this accurately and in compliance with packaging regulations – you guessed it – factories can employ machine vision.
AI cameras can guide machinery in filling packages and bottles, then inspect the finished product for breakages, tears, and open flaps or caps to make sure it’s assembled and positioned correctly. This is all to make sure the product within doesn’t get damaged on its way to customers. If something has gone wrong with the packaging, machine vision systems can automatically stop the item leaving the plant.
Track and trace
Now that Product X has left the factory, manufacturers need to know where it’s going. Using intelligent optical processing techniques, AI cameras can accurately and automatically track products around the world based on print text labels, serial numbers, barcodes and QR codes, manufacturing dates, globally unique identifiers, and more.
This information, fed to databases, allows manufacturers to verify and cross-reference the status of products and their routes to customers in real time, as well as divert products with faulty or unreadable identifiers. It’s a logistical balancing act made easy by machine vision, which makes sure nothing gets misplaced or lost while shipping.
Tracking and tracing with AI cameras is especially useful for food and pharmaceutical products which must often adhere to strict regulations regarding their ingredients, who they’re being sent to, and when they expire.
Scaling
Product X has arrived at its destination thanks to the help of AI cameras – time to do it all again.
As manufacturers seek to increase production turnover while cutting costs, they need to replicate and scale up technology that works well. The good thing about AI cameras is that they’re highly adaptable to different clients, industries, and countries.
Successful, automated production cycles can be implemented at new factories – passing down data on object properties, common defects, optimal working conditions, and more to speed up manufacturing processes. This frees up more time for innovation and paves the way to more autonomous and intelligent manufacturing.
Plug your manufacturing bottlenecks with Maxlab
Smart manufacturing requires smart technology. The Tokay Pro is ideal for the factory floor. With its integration with autonomous machines like robots and connectivity with major IoT platforms, the Tokay Pro can optimize your full production cycle. If you’re looking to tackle your manufacturing bottlenecks head on, get in touch with us at Maxlab and our world-class team of experts will help you find an intelligent solution.