Currently, PCBA manufacturing enterprises are becoming increasingly data-driven and intelligent in all their business and production processes, from raw material procurement and manufacturing to product sales and distribution. The continuous accumulation of data and the continuous development and maturity of data algorithms and models provide opportunities for the integration of artificial intelligence into the manufacturing industry, thereby promoting the transformation of enterprises from traditional production to intelligent production.

PCBA processing

In the era of machine intelligence, it can only be compensated by human intelligence. However, human physical strength is limited and prone to fatigue, there are differences in intelligence and skills, and human psychological state is uncontrollable. More importantly, many problems cannot be solved due to human discernment, such as how much compound stress a key component in a machine is currently subjected to? Will environmental vibrations cause processing quality issues? When will the dust in the workshop explode.

Therefore, people have always expected the participation of some "intelligent" elements outside the human body in PCBA processing and manufacturing activities, whether it is intelligent elements similar to humans or other organisms, added to machines, production environments or production processes, so that the entire manufacturing activity can meet the needs of real-time acquisition and rapid response of all status information, appropriate and timely decision-making, full satisfaction of all product feature changes (personalized needs), all products are of high quality and high added value, all manufacturing processes are efficient and safe, all equipment maintenance is proactive and predictive, all enterprise operations are high profit, low-cost, green and environmentally friendly, etc.

Enterprises can use sensors and intelligent chips distributed throughout the workshop to process and analyze data from the entire production process, thereby improving key indicators such as production efficiency, inventory turnover, and equipment utilization.

At the sales level, artificial intelligence can develop automated and intelligent production plans for enterprises by mining, calculating, and analyzing massive transaction data; At the production level, through the collection and analysis of product data and production equipment data, artificial intelligence realizes intelligent diagnosis of production equipment and product quality, and improves product yield; At the circulation level, sensors deployed on products can collect product status data in a timely manner, providing decision support for the production process of enterprises, and also providing predictive maintenance services.