Visionary Insights:

Exploring the Impact of Computer Vision in Electronics Manufacturing

The manufacturing sector has the highest expectations of productivity increases generated by Computer Vision technology, indicating the wide range of applications it has in this sector. From operational use in automated precision pattern cutting and welding, to adjacent processes such as quality control, inspection, monitoring, and packaging, Computer Vision can accelerate production without compromising quality.

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Andreas Prusak
Senior Product Manager
Panasonic Connect Europe

AI is already in use in some of our manufacturing solutions, such as stencil and screen printers for the solder and adhesive materials application process and pick and place machines for the SMT assembly, i.e. the component placement process  (SMT Mounter). Rapid improvements in computer vision is likely to assist in two additional areas:

1. Electronics Final Assembly

When products leave the automated production line, often additional bulky or heavy leaded odd shaped components need to be inserted or sub-assemblies connected to main boards. This fiddly task is performed by people. Especially for complex boards or for production environments with frequent changeovers between a high variety of products even experienced assembly operators might need some sort of placement instruction guidance. This needs to happen in a way that the operator is not unnecessarily disturbed by confirmation actions whether a component has been placed correctly or not. Cameras with increased accuracy and latest computer vision applications help to overcome these challenges.

2. Analyzing and Optimizing Operator Movements

Computer vision, backed by AI, can enable manufacturers to automatically analyse and optimise the movements of operators inside a factory and in manufacturing cells to  improve efficiency. This can be for moving between various process steps, e.g. between preparation areas and machines. Or if a smaller observation area is used it helps during training or even at performing critical maintenance tasks to ensure maintenance quality.

State-of-the-art technology in manufacturing

Back at university, computer vision was the topic of my thesis and I have been following the research for personal interest. In my opinion, there is always a delay between state-of-the-art technology from research to industry, I know of cases where e.g. technology developed in 2009 in the lab was then introduced to the market in 2015.

However, in our SMT and THT manufacturing industry the situation is a not that bit different, I believe many state of the art technologies are not yet used in the key processes. But for different reasons!

The basic applications are already sufficient for the current processes. As we can fix and calibrate the position of the camera it becomes easy to work with different pictures of an ideal picture by using a simple pattern matching algorithm. Computer vision is capable of working with not defined positions through SLAM (simultaneous localization and mapping). One of the core processes which enable high degree quality control within the SMT production environment, is parts recognition and 3D reconstruction. With the help of our multi camera type 3 we can generate a 3D multi-view vision. This process can be done quickly and easily as camera positions are fixed and known. Inspection machines within the industry often use at least 8 simultaneous views of the same object in order to get high multi-view visions. However, in my opinion, computer vision could be used for even more complex applications within manufacturing, because the same multi-view model reconstruction methodology could be used to generate a freehand television application. It might give us the opportunity to create videos and freely choose viewpoints which we have never been recording from. This is particularly useful for training or maintenance tasks, as it allows for the generation of virtual pictures from even the most inaccessible positions, where taking a normal picture would be impossible.

More potential for freestyle data generation

The electronics manufacturing industry comes up with a huge potential for more robust and freestyle data generation. One example is the new Panasonic offline camera teaching station implementing computer vision algorithms. The latest vision system enables offline data creation for all component data for each machine and as a result reduces the data creation time. When talking about zero downtime strategies, computer vision and especially the offline camera unit are essential. Data creation and verification can be done at the workplace of the programmer without using the actual production line which should be reserved for production only.

Looking towards the future

Application areas to come are all kinds use cases where we have interaction, i.e. AR, VR for maintenance, remote or assisted service and training, as well as more freestyle guidance of manual work. Further, the area of manual assembly or material preparation and troubleshooting have more potential for computer vision. Computer vision would be also used as secondary information to improve upper-level decisions or to quickly deliver a manufacturing solution until there will be a permanent solution available wich can rely on hardware and solves the issue directly. With the help of AI and computer vision, the manufacturing industry could extend data creation further, e.g. towards creating fast development cycles. 

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