Smart automated systems employ FDC systems to detect production anomalies, outliers in machine parameters, and sensing data, to avoid problems in product reliability and performance losses.
Fremont, CA: The semiconductor industry faces the risks and opportunities of rising product demand in the near future. The development of artificial intelligence (AI) and the Internet of Things (IoT) and the continual demands from the smartphone sector and other high-tech industries will significantly impact the semiconductor supply chain. The issue will be further affected by continuous international trade conflicts, which may increase the price of semiconductor materials and disrupt global collaboration within the sector.
Given how long it takes for semiconductor materials to be manufactured, downtime constitutes a financial and material expense at any stage in the manufacturing process. Human handling will bear the possibility of human error in wafer transport. With thousands of stages in the manufacturing process, blunders in transferring wafers to the right machine in the appropriate manufacturing pattern are all too probable.
Furthermore, even in a clean room regulating airborne particulate concentration, human management will risk contaminating wafers with dust particulates. In order to prevent contamination and make sure that each wafer is precisely transported and placed, the semiconductor companies utilize unified front opening pods that monitor automatic material handling systems (AMHSs).
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Failure to test performance requirements can also occur. To minimize this risk, performance tests are increasingly automated, both individually and when assembled into bigger semiconductor products, by using smarter systems to evaluate components for quality.
This doesn't mean automated systems are inefficient. Automated failure of equipment may interrupt a production process. The use of industrial IoT sensors and predictive maintenance enables semiconductor companies to detect equipment problems in the early stages of growth, thereby reducing output downtimes.
AI goes hand in hand with automation. Smart machines help enhance facilities by detecting and removing production constraints.
Intelligent automated systems employ FDC systems to detect production anomalies, outliers in machine parameters, and sensing data, to avoid problems in product reliability and performance losses. Given the narrow error margin when integrated circuits are produced, this function alone is an important industry tool.