Computer vision has seen a steady increase in adoption and implementation on the factory floor as part of Industry 4.0. For the uninitiated, computer vision is a type of AI focused on interpreting images or videos typically for the purpose of identifying objects and their relative positions to the same level of accuracy that a human is capable of (or greater).
The Benefits of Computer Vision In Manufacturing
There are clear benefits to implementing computer vision within manufacturing facilities:
- Efficiency: An automated system can work faster than a human, and also work for 24 hours a day if required.
- Accuracy: Implementation of computer vision systems lead to a higher level of accuracy in production and quality control.
- Repeatability: Computer vision systems are very efficient at repetitive and rote tasks. Even a partially automated system speeds up production time and reduces the cost of production.
- Reduced cost: Computer vision systems reduce labor costs and lead to fewer mistakes, higher quality, and less waste.
- Image: Computer vision on the assembly line (Credit: JourneyApps)
The Uses of Computer Vision in Manufacturing
Computer vision has numerous applications within manufacturing, here we discuss some of the most prevalent.
Product Assembly
Product assembly is one of the more widely automated processes within manufacturing, and computer vision plays an important role in that. Computer vision helps to ensure that products are assembled accurately and can significantly increase yield. The process usually involves the generation of a 3D model design using specialized software. Based on these designs, the computer vision system guides the assembly process precisely. The system assists robotic arms and human employees on the assembly line by constantly monitoring and guiding them.
Defect Detection
Computer vision conducts defect and anomaly detection by analyzing new images and comparing them to a pre-existing dataset. When a large number of items need to be inspected on the production line, computer vision can help automate that process. A computer vision solution can capture photos or videos of the product from several angles to make an inference as to whether a specific component is present or absent.
Since humans may struggle to accurately detect small defects in a large number of products, computer vision can help catch these defects so that they can be addressed before the product leaves the manufacturing plant.
Packaging Inspection
In some industries, packaging products correctly is more important than in others. For example, in the pharmaceutical industry (it is essential to maintain a specified number of whole tablets or capsules per bottle without fail. In retail industries, the correct amount or weight of the product needs to be included in the final package. Computer vision algorithms have advanced to a level where they can be used to automate many of these quality processes. Moreover, the system can be trained to check for damages on the final packaging and divert any product found lacking.
Computer vision systems can also ensure the packaging itself is in the required condition. It can check whether the size, color, and shape are correct and make sure it is intact.
Quality Inspection and Control
One of the more widely impacted processes is quality control during the production process. Quality control is very important in manufacturing and getting it right is important. Traditionally, Quality Inspectors have completed this task manually, but due to the possibility of human error, many companies are moving toward automated computer vision-driven systems.
These technologies reduce labor costs and can be more accurate as well as faster than humans. Instead of inspecting a sample of the products being manufactured, every piece can be inspected with alert events triggering when anomalies are detected.
Reading Barcodes
Almost all products sold these days have barcodes, which makes the tracking of a specific product a lot easier. Computer vision systems have advanced to allow for scanning multiple different barcodes at the same time with speeds comparable to laser scanners.
- Image: Manufacturing automation (Source: metamorworks/Shutterstock.com)
Improving Safety
Manufacturing facilities can be hazardous environments with many large machines, moving parts, processes that produce extreme temperatures, and many people working in one space. In large factories, people are often encouraged to watch numerous screens to look out for accidents or potentially hazardous situations. This can be difficult for a human to do accurately all the time, and here is where computer vision systems can make an important impact.
The system monitors the manufacturing site and detects issues related to worker or equipment safety. If an anomaly or accident is detected, a notification can be sent to management and first responders so that it can be dealt with immediately.
Predictive Maintenance
Many specialized machines are used in the manufacturing process and these suffer from wear and tear over time and need to receive maintenance. If the maintenance is not done in time, the machine could break, leading to production shutdowns and lost revenue. The use of computer vision technologies is much more effective than humans in detecting changes in manufacturing equipment.
This makes it possible to identify and repair faults before it leads to a malfunction. The technology is used for the fault diagnosis, leakage detection, and prognosis of industrial equipment.
- Image: Warehousing automation (Source: Gorodenkoff/Shutterstock.com)
Vision Picking
When it comes to order fulfillment and parts or product picking, computer vision can have a direct impact on speed, efficiency, accuracy, and cost. Here, technology can assist robots or humans to complete their jobs better. For robots, by identifying parts or products on the assembly line or in the warehouse for it to pick or sort. For humans, making use of assisted reality by way of a wearable headset (such as RealWear) guides the employee to the correct part or product.
AI allows users to take this a step further, by identifying the best “pick point” and placement orientation, speeding up the packaging process and maximizing package volume. This route optimization cuts down on time and the required distance to travel for the user.
Conclusion
Computer vision can and has made a great impact on manufacturing processes. It has the potential to increase efficiency, improve safety, and reduce costs. Whether it be on mounted cameras or through wearable headsets, companies can benefit from implementing computer vision systems. To see more of how JourneyApps enables computer vision for defect detection on RealWear devices, schedule a demo.
