xpertsystems/oil022-sample

OIL-022是一个合成停机与周转数据集（样本），属于石油天然气下游精炼行业，专注于维护规划、检查优化和周转操作。该数据集是XpertSystems.ai企业级精炼厂停机与周转数据集的免费预览版，用于维护规划机器学习、检查优化、进度延误预测、重启准备评估、周转成本预测和基于风险的检查（RBI）分析。样本覆盖10个全球区域的15个精炼厂，包含2,250台设备和1,200个周转活动，共165,114行数据，分布在15个表格中。数据生成基于行业标准（如API 510、API 570、API 580/581、NACE TM0274、OSHA 1910.119等），并通过10个指标校准验证，确保数据真实性和行业相关性。数据集支持多种机器学习用例，包括API 510剩余寿命回归、可靠性等级分类、进度延误回归等。OIL-022 is a synthetic shutdown and turnaround dataset (sample) for the oil and gas downstream refining sector, focusing on maintenance planning, inspection optimization, and turnaround operations. It is a free, schema-identical preview of XpertSystems.ais enterprise refinery shutdown and turnaround dataset for maintenance planning ML, inspection optimization, schedule slippage prediction, restart readiness assessment, turnaround cost forecasting, and RBI analytics. The sample covers 1,200 turnaround campaigns across 15 refineries with 2,250 pieces of equipment in 10 global regions, with 165,114 rows linked across 15 tables. Data generation is anchored to industry standards (e.g., API 510, API 570, API 580/581, NACE TM0274, OSHA 1910.119) and validated via a 10-metric scorecard for realism and industry alignment. The dataset supports various ML use cases, including API 510 remaining life regression, reliability grade classification, schedule slippage regression, and more.