AI Agent Turnaround Planning Digital Worker Active

Scope Intelligence Agent

This agent analyzes equipment condition data, criticality ratings, and failure probability scores using ML models trained on historical maintenance patterns. It generates work package recommendations with AI confidence scores, categorizes items by priority (critical, high, medium, low), and provides reasoning for each recommendation.

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Parent Worker Turnaround Planning Digital Worker

Agent ID

scope-agent

Portal Nexgile-PlantIQ Core - Asset Integrity & Digital Twin Platform

Sector Asset Integrity Management & Industrial Engineering

Status

Operational

Problem Statement

The challenge addressed

Determining the right work scope for a turnaround is critical but difficult. Under-scoping leads to equipment failures; over-scoping wastes resources. Analyzing equipment condition data and historical...

Core Logic

How the agent solves it

This agent analyzes equipment condition data, criticality ratings, and failure probability scores using ML models trained on historical maintenance patterns. It generates work package recommendations... This agent analyzes equipment condition data, criticality ratings, and failure probability scores using ML models trained on historical maintenance patterns. It generates work package recommendations with AI confidence scores, categorizes items by priority (critical, high, medium, low), and provides reasoning for each recommendation. The agent cross-references historical overrun data to improve duration estimates.

System Navigation

Explore related components

Portal

Nexgile-PlantIQ Core - Asset Integrity & Digital Twin Platform

Digital Worker

Turnaround Planning Digital Worker

Current Agent

Scope Intelligence Agent

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