Fast Artificial Intelligence (AI) Chip Ready To Change Manufacturing

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ROHM and A*STAR’s Institute of Microelectronics (IME) are fostering the era of smart manufacturing with a new artificial intelligence (AI) chip which is anticipated to enable faster prediction of machine failures by processing and analyzing data gathered by sensors in real-time. This will pave the way for greater asset productivity and lower overall maintenance costs.

The new AI chip 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.

The chip leverages ROHM’s original AI analytical algorithms, and IME’s capabilities in ultra-low power analog/digital integrated circuit and systems, as well as analog computation circuits developed by both firms.

ROHM noted that the new AI chip will filter volumes of data across multiple sensors, and analyze complex data patterns in real-time.

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However, as the number of sensors increases in the future, the wireless communication technology for Wireless Sensor Networks (WSNs) would face bandwidth constraints, and be unable to expeditiously transmit the increasingly large sensor data to the computer server.

In pursuit of this, the firms developed the chip to process and analyse the 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.

This will move intelligence to the sensor, rather than a central server, to cope up with the restricted data bandwidth on the wireless sensor networks in future. ROHM explained that some of the raw data has considerable bandwidth, which local processing can reduce.

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“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”, said ROHM in the announcement.

ROHM has plans for the AI chip to be compatible with wireless technologies such as Wi-SUN, and EnOcean) , and incorporate the chip to its proprietary sensor nodes and wireless modules.

“I’m exceptionally delighted that we have our first opportunity for cooperative research with A*STAR’s IME. Through the fusion of ROHM’s sensor technology, analog low-power technology and AI architecture with IME’s capabilities in low-power integrated circuit technology, we want to provide the optimum solutions for edge nodes”, commented Mr Koji Taniuchi, Fundamental Research and Development Division, General Manager at ROHM.

For further details, view the full Press release.

 

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