Every AI Policy Ever · open in the interactive register
Published (non-binding, current)Non-binding · Guidelines / framework
プラント保安分野AI信頼性評価ガイドライン
Record JP-15
Guidelines of the liaison council of METI, the Fire and Disaster Management Agency and the Ministry of Health, Labour and Welfare on assessing the reliability of machine learning used in petroleum and chemical plants, where safety is crucial. Following AIST's Machine Learning Quality Management Guideline, they manage reliability through quality in use, external quality and internal quality, with required levels for risk avoidance and performance, and take account of external safety mechanisms, safety systems independent of the AI and human involvement in its decisions. They apply this to five plant use cases and set out tasks in development and operation.
The first edition was published in November 2020. The second edition of March 2021 clarified how AI safety assessment relates to existing plant risk assessment methods such as HAZOP and FMEA, added explanations to the template for recording reliability assessments, a Q&A and seven practical examples covering the five use cases (pipe wall thickness prediction, pipe image diagnosis, equipment deterioration diagnosis, detection of early signs of abnormality, operation optimisation). The guidelines were drawn up from a working group of plant operators and safety and AI experts that met from April 2020 to March 2021, and are to be reviewed as they are used. The council publishes an English edition of the second edition.
Open the official source https://www.fdma.go.jp/relocation/neuter/topics/fieldList4_16/jisyuhoan_shiryo.html
Archived. Last attempt 2026-10-18 00:46:11 UTC
Liaison Council of Three Ministries on Disaster Prevention of Petroleum Complexes (Ministry of Economy, Trade and Industry; Fire and Disaster Management Agency; Ministry of Health, Labour and Welfare). Guidelines on Assessment of AI Reliability in the Field of Plant Safety. 2020-11. https://www.fdma.go.jp/relocation/neuter/topics/fieldList4_16/jisyuhoan_shiryo.html. Status: Published (non-binding, current); verified 2026-10-18 (level A). Local copy archive/_runs/2026-10-14-discover-leads-2026-10-14/C020/2026-10-14/official.html retrieved 2026-10-14 13:11:38 UTC, SHA-256 c60df78e0244445c0e44253681cf40c489feec561e2f450c4d68b718a315f8c0. Every AI Policy Ever, version 1.18 (snapshot 2026-10-18), record JP-15.
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