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AI Vision in Electronic Manufacturing Industry

Without a doubt, artificial intelligence (AI) is the driving force for the development of electronics manufacturing, and early adopters will enjoy the benefits in terms of process efficiency, cost reductions, and fresh insights. There are two AI implementation examples, and we’ll look at how AI has already impacted the industry, as well as what the future will bring.

In the electronics manufacturing industry, computer-aided design (CAD) is usually used to create the physical blueprint of electronic products. CAD model enables the development, modification, and optimization of the design process. Usually, the company will create a CAD design, and collaborate with the manufacturers to create the physical model of the product according to the CAD design. However, companies and manufacturers need to discuss and go back and forth for the CAD reviewing and quotation processes, which is inefficient.

To provide a solution in a not timely manner addressed to the CAD model, companies such as Xometry, 3Dhubs, or Spanflug implement AI and machine learning to simplify the offering process and at the same time enable new business models in the field of industrial manufacturing. An offer can be generated automatically by uploading a CAD model and providing parameters (material, surface treatment, tolerances, etc.), and the AI-technique platform serves as an interface between companies that want to have CAD components manufactured and the manufacturers. For example, instead of sending manual requests to manufacturers, company A uploads the component’s CAD model to the AI platform. The platform calculates the cost and delivery time of this component using an algorithm and gives a real-time quote to Company A. The quote is forwarded to the manufacturer’s internal operation systems if Company A accepts it. A manufacturing company accepts the order and produces the component if it believes the price supplied is economically viable. The drawbacks of this AI implementation are that the system is not matured for complex components or large quantities..

The next implementation of AI in electronics manufacturing is AI vision in automated optical inspection (AOI) machines. The adaptable machine can inspect virtually any product that requires precise visual inspection. AOI is generally used to look for defects in printed circuit board assemblies (PCBAs). AOI machines use cameras to scan PCBAs and detect two sorts of failures: catastrophic failure (e.g. missing component) and quality defects (e.g. fillet size or shape or component skew). Defects could happen throughout the production process, lowering the quality. It is vital to accurately classify the defects found by the AOI machine, particularly killer defects. The more accurately problems are classified, the less cost is spent on R&D team problem solving and PCBA repair. 

Printed circuit boards (PCBs) are becoming more complex as components become smaller and more densely packed. By incorporating artificial intelligence, the AOI machine is able to expand its inspection capabilities, optimize the yield rate, improve manufacturing operations and processes, and reduce manual operations. Moreover, the combination of AI technology and AOI equipment has higher accuracy and fewer false positives than current AOI systems and can be quickly trained to detect new products or identify unknown defects. AI can automatically modify various parameters and make decisions with many reduced risks, resulting in reliable detection results irrespective of whether the AOI system is programmed by a beginner or a professional.

Artificial intelligence has impacted the electronic manufacturing industry and optimized production processes. With the innovation of AI and technology, people expect that AI will play a crucial role in factory planning and layout optimization, real-time data collection and analysis, generative design, and even intelligent plant.


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Artificial Intelligence in Electronics Manufacturing: Vanti Analytics. Vanti. (2021, August 29). Retrieved April 9, 2022, from

How can AI improve automatic optical inspection? Market Prospects. (n.d.). Retrieved April 9, 2022, from




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