Promoting Utilization of Advanced IT -Introduction of NS-DIG(TM) capable of advanced data analysis and AI development-

Apr. 25 2019

NIPPON STEEL CORPORATION

Promoting Utilization of Advanced IT
-Introduction of NS-DIG^TM capable of advanced data analysis and AI development-

NIPPON STEEL CORPORATION (hereinafter NIPPON STEEL) is committed to providing the high quality steel products our customers need in a stable and timely manner. In order to achieve this, we have been proactively deploying advanced IT solutions, including AI and IoT, into our supply and engineering chains, to create safe and competitive manufacturing sites through support for safety as well as operational and workstyle reforms, to ensure stable production and quality improvement through preventive maintenance and to promote intelligent solutions (improved sophistication of work).
Fig. 1: Application of advanced IT in supply and engineering chains as promoted by Nippon Steel
The deployment of advanced IT requires the high-speed and advanced analysis of a large variety and volume of data or what is called “Big Data.” In order to enable any staff who are promoting the development and application of advanced IT to quickly analyze such data anytime, we have deployed NS-DIG^TM. NS-DIG^TM is a platform capable of high performance computing, including advanced image analysis and deep learning, to analyze various data in order to develop and apply AI (See Fig. 2).
As a tool for AI development, NS-DIG^TM is embedded with DataRobot^®, an AI automation tool that has already been deployed, and KAMONOHASHI^®, a newly adopted image analysis and deep learning tool developed by NS Solutions Corporation. As such, NS-DIG^TM is a platform seamlessly capable of tasks from data preparation and analysis to AI development and evaluation for realizing more efficient and more extensive AI development and evaluation. Initially, the data scientists and staff in charge of advanced data analysis and AI application are using NS-DIG^TM to improve intelligent capabilities at our steel works.
We plan to integrate the NS-DIG^TM hybrid cloud in order to deal with more extensive data analysis and promote AI development and application further in the future.
  (Fig. 2: Outline of NS-DIG^TM)
NIPPON STEEL also promotes workstyle reforms for our employees utilizing advanced IT in order to ensure safer and higher productivity. We have established a system in which data scientists can fully support AI development in collaboration with the staff at our steel works, head office and laboratories. In order for users to improve their IT literacy, we have also held corporate-wide presentations to show case studies on advanced IT utilization and consortiums where developers discuss about technological development since 2014. In addition, an in-house machine learning competition on the NS-DIG^TM started last year. NIPPON STEEL has also endeavored to educate employees and enhance their awareness of advanced IT and AI, as a part of which IT literacy education for new employees started in 2019.
We plan to further strengthen our education support system in the future.

NIPPON STEEL has realized monitoring of the manufacturing status through deep learning for image recognition, packing inspection during the shipping process by applying AI to the manufacturing process at steel works. We are continuing our collaboration with our group company NS Solutions and are promoting advanced IT and AI applications through further infrastructure improvement. NIPPON STEEL group is making concerted efforts to promote intelligent capabilities, operational reforms and standardization and workstyle reforms in the steel industry.


Reference: The origin of the name of NS-DIG^TM
“DIG” consists of the initial letters of the words “Data,” “Innovation” and “Gateway.” “DIG” also means to “bring something out of the ground” or “investigate thoroughly.” This name represents what NIPPON STEEL wishes to achieve – to support the digging out and careful investigation of the data that it holds and to have users bring about innovation in their work and exhibit the effects of improvement in the company-wide data analysis environment.

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