RSG-GAS Reactor Component Reliability Metrics and Surveillance Intervals

A 95.1 KB dataset supporting a study on predictive maintenance for the RSG-GAS research reactor. It contains reliability metrics and simulation results for determining surveillance intervals of critical components. The dataset was authored by Sri Sudadiyo and last updated in April 2026.

Use Cases

• Calculate surveillance intervals using the Maintenance Priority Index (MPI) and weighted factors w1 and w2.
• Model component failure times and reliability using Weibull distribution parameters and Monte Carlo simulation.
• Analyze key performance indicators like Mean Time Between Failures (MTBF) of 171.16 days and thermal efficiency improvements.
• Support virtual monitoring strategies by integrating remote condition inspection data with performance profiling.

Strengths

• Includes specific, calculated reliability metrics such as an MTBF of 171.16 days and a 44.2% thermal efficiency improvement.
• Applies a structured methodology combining the Maintenance Priority Index with Weibull-Monte Carlo simulation.

Limitations

• The dataset is very small at 95.1 KB, indicating limited scope and likely a small number of records or components.
• Specific column names, row counts, and the full data structure are unknown.
• The data is focused on a single case study (KLD-BRV10 generator set), limiting generalizability.

Provenance

Source

figshare, authored by Sri Sudadiyo.

Collection Method

Derived from a study proposing a data-driven framework for predictive maintenance, likely involving simulation and analysis of reactor component metrics.

Time Range

null

Freshness

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Geography

Likely related to the RSG-GAS research reactor facility, but specific location is unknown.