Learn how some of our most successful customers using Impulse

Osaka Gas

~Using Impulse as a trigger for business transformation~

Osaka Gas, one of the major gas providers in Japan, has analyzed their big data as a trigger for business transformation. The Business Analysis Center, specialized section of data analysis, has sought the fastest and most effective way to solve their business issues.
They choosed “Impulse on AWS” as the automated and scalable data analytics platform. Furthermore, through PoC(Proof of Concept), anomaly detection system in Impulse worked very well, so that they could predict abnormality of their equipment more than a week ago.

JFE Engineering

〜Building a data analysis platform on AWS for the plant monitoring~

JFE Engineering provides plants’ management solutions in fields of environment, energy, and social infrastructure. They have collected and analyzed their plant operation data and tried to automate and enhance their maintenance tasks. However, They did not have matured data analytics way and wanted data analytics platform.
One of the reason why they choosed “Impulse on AWS” is that the anomaly detection service do not need to programming. Through PoC, we sure that our system can detect signs of failures in plant operation three days ahead of the actual occurrence.

MEIDENSHA

〜Predictive Maintenance Analysis for the boilers on Edge and Cloud~

Meidensha, one of the world‘s largest industrial equipment producers, had trouble with building a failure detection system for water power facilities placed in the remote areas.
To reduce the risks of network interruption and stabilize detection processes at remote places, they choosed "Impulse on AWS" with the edge detection architecture. In PoC, we ensured that a failure sign could be detected 12 days ahead of the actual failure by the data from accelerometers in a water power facility.

YANMAR

〜Predictive maintenance of internal combustion engines~

Yanmar, one of the most famous exhaust valve of a diesel engine for a large ship producers, has analayzed their big data at their "Central Research Laboratory".
Started to develop advanced cloud infrastructure utilizing a wide variety of sensor data and machine learning for preventive maintenance of internal combustion engines. They -have a reputation for high reliability and durability of its products- introduced "Impulse" as an abnormality detection platform aiming for further research and development and service improvement.

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