Mainformatics?

PROLOGUE

For Power Plant Business Intelligence!

Mainformatics is our technical slogan emphasizing the fusion discipline of maintenance technologies cooperated by information science, informatics. This aims to develop the technologies to learn from experience (data) to predict future behavior of plants to make better decisions

The maintenance needs were born with the beginning of industrialization, but its significance seems more highlighted with the advent of 4th industrial revolution. We are in pursuit to apply state-of-the-art information technologies for advanced intelligence in safety- or performance-critical assets.

We are focusing on (1) Design for Maintainability, (2) Probabilistic Safety and Security Assessment, and (3) Plant Health Management.

THE RIGHT WORK, ON THE RIGHT EQUIPMENT, AT THE RIGHT TIME

Our group aims at achieving the above catchphrase with information manufacturing and analytics.

  • Risk Informed Design of Complex Systems with Interactive Design between Success and Failure Domain
    In terms of the right work (How should we repair?), we are focusing on the Design for Maintainability. In order to satisfy customers' needs on maintenance, we are studying on the framework to go through the entire life cycle of a system and to renovate its design in a methodical manner. The concerns on human errors during maintenance tasks should be correctly recognized in the framework.

  • Probabilistic Safety & Security Assessment with Dynamic & Stochastic Cyber Physical Simulation
    In terms of the right equipment (What should we repair?), the risk-assisted decision-making enables making decisions better (more efficient while less cost) in a world of uncertainty associated with them. This requires a substantial understanding of the sources of failure modes, quantifying those modes, and assessing the probability or risk associated with each.

  • Plant Analytics with Monitoring, Diagnostics, and Prognostics
    In terms of the right time (When should we repair?), the reliable observations, the analysis by data mining, and the diagnosis cooperated with system simulation are the key processes. The current focus is broader covering of a variety of theories, principles, and computational techniques.