AI analytics anomaly detection enhances treatment plant
AI analytics has been a game changer for industries today. Not only is AI analytics able to provide more accurate data and insights, but it also does it in real-time. Today, there is a myriad of use cases for AI analytics for almost any industry.
In the manufacturing industry, AI analytics is used to analyze data collected from machines in the plant. The insights from the data help businesses make the right decisions to maximize their productivity as well as avoid any disruptions.
Detecting anomalies in the manufacturing industry can be a huge challenge without the right technologies. In the past, most production lines would run manually and would require factory workers to test and check for any anomalies or disruptions in the facility.
Over the years though, technology has automated most of these processes. Today, sensors fitted on key areas on the production line can give insights o the status of the plant, enabling companies to have more visibility over their production. These AI-enabled sensors provide results in real-time, avoiding any possible disruption as well.
For example, in Japan, NEC will be providing Suntory Beer with NEC Advanced Analytics-Invariant Analysis, an AI-based facility anomaly detection system. This system is planned to begin operation in late May 2022 at the can filling line at Suntory’s Natural Water Beer Plant in Kyoto, Japan.
Traditionally, at production lines at manufacturing sites where mass production is undertaken, field personnel mainly use sensor data from equipment to monitor usage thresholds. However, there is a need for experience and know-how to understand the fine changes in individual data, and passing these skills along is a challenge.
This new anomaly detection system is centered on NEC Advanced Analytics-Invariant Analysis, which uses Invariant Analysis Technology, part of NEC’s leading-edge AI technology group, NEC the WISE. By collecting and analyzing a large amount of time-series data from a large number of sensors installed in facilities through control systems such as PLCs (Programmable Logic Controller), modeling invariant relationships between sensors (invariants), and comparing changes between predicted data with actual data, users can detect “irregular” occurrences at an early stage.
This system takes advantage of the features of White Box AI and provides information necessary for taking action at maintenance sites, such as where and why functions are performing abnormally. When modeling, users can easily visualize conditions by simply entering the sensor information they want to see with the time that those sensors were operating.
Suntory’s Natural Water Beer Plant in Kyoto will have a new can filling line using IoT in order to accelerate digital transformation in production lines. In this line, NEC’s system will automatically discover the relationships between approximately 1,500 sensors, and issue alarms when changes occur, thereby detecting equipment anomalies at an early stage and helping to resolve them as soon as possible.
Moreover, NEC will install microphones near filling machines to analyze when sounds are different from usual, which could possibly indicate an abnormality with the system. In the future, it is expected that these advancements could help to reduce the number of people required for maintenance work while helping to detect abnormalities more quickly.
“Through the provision of this system, NEC is supporting the stable operation of facilities, preserving expert know-how and experience, recognizing errors that are difficult to detect, and contributing to the DX of production lines,” said Masayuki Ikeda, General Manager, AI Analytics Division, NEC Corporation.