Joint provision of abnormality sign detection for efficient plant operations

JGC Corporation

Using AI and IoT technologies to monitor operational status across an entire plant to contribute to trouble avoidance such as interruption in production, and more efficient plant operations.

To prevent interruption in production and other large-scale trouble in plant operations, it is essential to detect signs of abnormality and take other measures to monitor operational status on a daily basis. JGC Corporation, a leader in the engineering, procurement and construction of energy and chemical plants, with expanding business interests across domestic and international markets, is collaborating with NEC in providing services that use AI and IoT technologies to analyze plant operating data to ensure stable and efficient plant operations. Utilizing NEC's proprietary "System Invariant Analysis Technology" that detects abnormal signs in plant equipment and systems, the service analyzes a broad scope of operating data covering entire plants and contributes to improving productivity and reducing operating costs through more stable plant operations.


As plant operators become older and finding skilled workers becomes increasingly difficult both inside and outside Japan, plants are focusing on using AI and IoT technologies to maintain safe, secure and efficient plant operations.

In recent years, there has been an increasing need to adopt AI and IoT to improve operations and maintenance processes in the energy and chemical industries. In developed countries, this situation is attributable to the lengthening of plant life and the aging and shortage of skilled plant operators. At the same time, emerging countries are experiencing difficulties in securing operators with the requisite skills due to a rise in the number of plants in these countries. Conventionally, plant equipment and systems were equipped with sensors that collected operational data, which was analyzed by engineers and skilled operators with the appropriate knowledge and experience, and used to make operating decisions. Recently, however, a lack of skilled workers and other issues have prompted calls to find solutions to support plant operations. As this situation emerges, the adoption of AI and IoT technologies is gaining attention within the industry as a way to achieve stable operations across entire plants, improve productivity by detecting signs of abnormality, and implement predictive maintenance before trouble occurs.

"Up until now, operating monitoring systems monitored devices and systems individually based on a localized abnormality monitoring process, much like how the gastroenterology or pulmonary medicine departments play a specialized role in a medical facility. Going forward, however, it will be necessary for operations to diagnose the health of the entire plant in a similar role to a general hospital. I believe it has become even more vital to adopt ICT to make better use of data to promptly detect signs of plant failures at early stages and implement preventative measures before these failures escalate into large-scale problems."

Takuya Hanada, Executive Officer, Senior General Manager, Business Development Division

Using advanced AI technologies to detect abnormal signs to ensure stable and efficient plant operation

JGC, with proven capabilities and an outstanding reputation in the engineering, procurement and construction of energy and chemical plants, has turned its attention to adopting IoT and AI technologies to ensure even more stable and efficient plant operations. To bring about new services using these technologies, JGC Corporation has joined forces with NEC. NEC's System Invariant Analysis Technology is the primary reason behind JGC's decision to collaborate with NEC. This proprietary AI technology detects abnormal signs in the system derived from correlations between data collected from devices and equipment using IoT. It differs significantly from conventional technologies in that it can detect signs of abnormality even when individual measurement data thresholds (abnormality thresholds) are not exceeded. The collaboration combines the engineering know-how and specialist industry knowledge accumulated by JGC Corporation with NEC's advanced AI technologies. Services that analyze plant operating data were developed through repeated verification testing using actual operating data from customers.

"The reason we chose NEC was because of its highly regarded System Invariant Analysis Technology, which can detect abnormal signs in the continuous system processes in oil and gas production that is difficult to visualize. Another major reason was that NEC has data scientists who can identify user needs and provide appropriate analysis solutions."

Takuya Hanada

NEC is contributing widely to the industrial world through cutting-edge initiatives using AI and IoT technologies

The services that analyze plant operating data jointly provided by JGC and NEC can contribute to trouble avoidance and early prevention by analyzing a broad-range of data covering an entire plant to detect signs of abnormality early and analyze the cause. It can also help avoid interruptions in plant operations and reduce operational costs by delivering proactive measures to counteract degradation in such equipment as valves and pumps. In addition to improving productivity, safe and stable plant operations also contribute to protecting the environment through more efficient use of utilities such as water and electricity. In the short time since the establishment of the partnership in November 2016, the two companies have already received an order to supply the plant operation data analysis services, which they plan to implement at 30 plants inside and outside Japan by 2019. NEC will look to further contribute to the industrial world in the future by making full use of its world-class AI technology in areas such as energy demand forecasting. In addition, it will continue to leverage its System Invariant Analysis Technology to provide related services for plants specialized in oil, gas, chemical, power, resource development, and other fields.

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