ROHM and A*STAR'S IME to develop artificial intelligence Chip for predictive maintenance in smart factories

ROHM Semiconductor, a leading semiconductor manufacturer, and ASTAR’s Institute of Microelectronics (IME), a world renowned research institute under the Agency for Science, Technology and Research (ASTAR) today announced the joint development of an artificial intelligence (AI) chip to boost efficiency in predictive maintenance for smart factories. The concept of ‘Predictive Maintenance’ has become widespread in the manufacturing industry as manufacturers begin to digitalize their production lines for increased productivity and competitiveness. Predictive maintenance forecasts machine failures, and it involves monitoring the function and health of machines, and identifying potential problems based on data received through device logs and sensors, and eventually taking counter-measures such as repairing or replacing the affected machine. In order for any machine abnormality to be detected throughout a production line, diverse amounts of data gathered from multiple sensors are first transmitted over a wireless network to a central computer server for processing and analysis. However, as the number of sensors increases in the future, the wireless communication technology for Wireless Sensor Networks (WSNs)*1) would face bandwidth constraints, and be unable to expeditiously transmit the increasingly large sensor data to the computer server (Please refer to Figure 1 for illustration of wireless transmission of sensor data to computer server). Powered by the Internet of Things (IoT), AI is becoming a key enabler for predictive maintenance and performance improvement, because of its cognitive abilities such as learning, reasoning and problem-solving. ROHM and IME will develop an AI chip that is capable of processing and analyzing data as soon as they are received by a sensor node. This drastically reduces the amount of sensor data to be transmitted wirelessly to a central computer server for them to be further processed and analyzed.”