IOTA Foundation, a non-profit foundation focused on distributed ledger technology (DLT) and open-source ecosystem development, announced today that it has partnered on a project initiated by Best Materia and IMC, Japanese maintenance related companies, and funded by NEDO (New Energy and Industrial Technology Development Organization), a national research and development agency. The goal of the project is to develop technology to strengthen the security, longevity, and durability of critical infrastructure assets in Japan and abroad.
By adding artificial intelligence and distributed ledger technology to Risk Based Maintenance (RBM) Systems deployed in power plants, energy plants, industrial plants, petrochemicals and oil refining plants, the group hopes to capture a large share of the domestic social infrastructure conservation market, valued at 170 Trillion Yen (1.5 Trillion USD). This type of predictive maintenance system that shares industry data using a distributed database is set to be the first of its kind in the world.
While damage prediction assessment based on the current RBM standards exists, most processes are still left up to field workers to do manually. To further optimize these systems, maintenance data will be digitized and processed by an artificial intelligence system to predict when and which parts in a plant are going to require maintenance. This will reduce unplanned outages, improve plant availability and lower costs by reducing unnecessary inspections and repairs.
“Creating a decentralized, open source and free distributed ledger technology to ensure data integrity has always been our driving purpose. As a non-profit we are honored seeing the IOTA protocol being utilized to secure a wide variety of data points in this project. Digitalizing the risk based maintenance (RBM) systems for safer and more efficient industrial plants is only one of many applications where IOTA will be used in the future.” – Holger Köther, Director of Partnerships, IOTA Foundation
“Because of the aging problem in Japan, we seriously need the AI system supporting our business in place of retired RBM consultants. We expect that IOTA Tangle will enable us to securely collect and store RBM related data including sensitive plant information which is the key to the accuracy of the AI system.” – Shigemitsu Kihara, Best Materia, CEO
The project will develop a cloud-based SaaS software with the following capabilities:
- A decentralized database using IOTA’s distributed ledger technology- Centralized databases are vulnerable to accidents, tampering and leakage. By building an RBM using IOTA, maintenance companies are able to provide a solution to infrastructure partners that is resistant to cyber-attacks while protecting sensitive data.
- Artificial intelligence system developed- With current RBM systems, individuals are dependent on the knowledge of skilled technicians making standardization difficult. Due to Japan’s aging population, there is a serious risk of information loss when current employees retire. By creating an artificial intelligence system, information can be captured, shared, and acted upon by distributed teams across the world.
- Digitizing and sharing infrastructure data- Right now, data for plants across Japan are stored manually and not digitized. This can cause a host of issues when it comes to the integrity and sharing capabilities of data. By digitizing infrastructure data, maintenance companies can make it easier for partners across the supply chain to collaborate and share data in a safe, efficient way.
Key Statistics About The Project:
- For Data digitization (supporting initial data input by skilled engineers from paper to PDF, PDF to RBM software), the labor cost of skilled engineers per plant is 20-30 million yen.
- Maintenance personnel cost of a distributed database and AI is 30 million yen/ year.
- There are 30,000 plants that require initial input for RBM system construction in Japan.
- The initial data input contract cost for one plant is 30-50 million yen, 0.9-1.5 trillion yen.
- The initial data input subcontracting cost for one plant is 30 to 50 million yen, and if AI is advanced in this research and development, the cost will be less than half.
Organizations collaborating on this project include Best Materia, IMC, High Pressure Institute of Japan, The Society of Chemical Engineers Japan, OMC, Lloyd’s Register and Yokohama National University.