Prepare yourself for the Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning course

Shutdowns and turnarounds (SD/TAR) are among the most critical and expensive activities in industrial operations. They require precise planning, flawless execution, and tight coordination across engineering, maintenance, operations, procurement, and contractors. Traditional planning methods - while essential - often struggle with scope growth, schedule overruns, resource bottlenecks, and unforeseen risks. Artificial Intelligence (AI) now offers powerful new capabilities to analyze historical turnaround data, optimize planning decisions, predict risks, and support real‑time execution control.

This 5‑day Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course provides a comprehensive and practical exploration of how AI can transform shutdown and turnaround planning. Delegates will learn how machine learning, predictive analytics, and intelligent automation can enhance scope definition, scheduling, cost estimation, contractor management, and risk mitigation.

Through real‑world case studies, hands‑on exercises, and scenario‑based discussions, participants will discover how AI can reduce uncertainty, improve accuracy, and drive measurable improvements in safety, cost, and schedule performance. This training course is ideal for organizations seeking to modernize their SD/TAR processes and prepare their teams for the next generation of intelligent, data‑driven turnaround management.

This Aicademy Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course will highlight:

  • AI fundamentals applied to shutdown and turnaround planning
  • Machine learning for scope optimization and risk prediction
  • AI‑enabled scheduling, resource planning, and cost modeling
  • Predictive analytics for contractor performance and productivity
  • Digital twins for turnaround simulation and scenario analysis
  • Integration of AI with CMMS, EAM, planning tools, and historian systems
  • Real‑time execution monitoring using AI and IoT data
  • Case studies from oil & gas, petrochemical, mining, and power sectors

The learning journey

Course Summary Outline

Day 1

Foundations of Shutdown/Turnaround Planning & AI

Day 2

AI Driven Scope, Risk & Cost Analysis

Day 3

Scheduling, Resources & Digital Twins

Day 4

AI Tools, Dashboards & Execution Control

Day 5

Turnaround Excellence & Future Trends

Key Learning Outcomes and Objectives?

By the end of this Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course, participants will be able to:

  • Analyze turnaround data using AI and advanced analytics
  • Predict risks, delays, and cost overruns before they occur
  • Apply AI to optimize scope, scheduling, and resource planning
  • Use digital twins to simulate turnaround scenarios
  • Implement AI‑enabled dashboards for real‑time execution control
  • Develop an AI‑supported SD/TAR improvement plan

The Excentra Learning Approach

The Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course is delivered through a blend of instructor-led presentations, live demonstrations, guided exercises, and real-world case studies. Participants will work with actual AI tools, explore practical engineering scenarios, and complete hands-on activities that reinforce learning. The training course is structured to be interactive, engaging, and immediately applicable to workplace challenges. 

Excentra capability map

Six capabilities, and how far this course takes each one

Every Excentra course is mapped against the same six AI capabilities, so you can see at a glance what a course builds and compare it with any other in the catalogue.
01

Data Intelligence

Inventorying and rating CMMS, EAM, historian, procurement and contractor data for AI use
02

Intelligent Monitoring

Scope-growth, risk and cost prediction; execution KPIs, alert thresholds and contractor performance analytics
03

Document Intelligence

Reading historical scope lists, work orders and close-out reports to find hidden work
04

Workflow & Agent Design

Where AI outputs enter planning and execution systems, and which decisions the planner keeps
05

Responsible Implementation

Human-machine collaboration, industrial cyber-security assessment and governance of AI-assisted decisions
06

Business Transformation

The phased AI-supported SD/TAR improvement roadmap, defended on day five

Is This Course Right for You?

This Aicademy Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course is suitable to a wide range of professionals but will greatly benefit:

  • Shutdown/turnaround planners and coordinators
  • Maintenance and reliability engineers
  • Project managers and engineering managers
  • Operations and production supervisors
  • CMMS/EAM specialists
  • Procurement and contractor management teams
  • Digital transformation and Industry 4.0 professionals

Frequently Asked Questions

Participants will learn how artificial intelligence, machine learning and predictive analytics can support major maintenance events. The Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course covers data analysis, scope optimisation, scheduling, resource planning, cost modelling and risk prediction. It also addresses digital twins, intelligent dashboards and real-time execution control, helping participants develop an AI-supported SD/TAR improvement plan.
The course is particularly relevant to shutdown and turnaround planners, coordinators, maintenance and reliability engineers, and project or engineering managers. Operations supervisors, CMMS/EAM specialists, procurement teams and contractor management professionals can also benefit. It is equally applicable to digital transformation and Industry 4.0 professionals responsible for introducing data-driven methods into maintenance and turnaround processes.
The course explains how machine learning and historical turnaround data can support more informed scope decisions. Participants will learn how AI can help analyse SD/TAR data, identify patterns and improve scope definition before execution. This knowledge is relevant to planners, maintenance teams and engineering managers seeking to control uncertainty, reduce avoidable scope growth and align maintenance requirements with available resources.
AI can improve shutdown scheduling by analysing planning data, resource requirements and potential bottlenecks more systematically. Participants will learn how AI-enabled scheduling and resource planning can support better coordination across engineering, maintenance, operations, procurement and contractors. The course connects these capabilities with the objectives of improving schedule adherence, resource utilisation and control of complex maintenance events.
Yes, predictive analytics for delays, cost overruns and operational risks is a central course topic. Participants will learn how AI can analyse turnaround information to identify emerging risks before they materially affect execution. The Artificial Intelligence (AI) for Enhanced Shutdown / Turnaround Planning training course also links risk prediction with cost modelling, safety considerations and more informed planning decisions.
Participants will learn how predictive analytics can be applied to contractor performance and productivity data. This can help procurement, contractor management and turnaround teams identify performance trends, anticipate resource constraints and make better-informed planning decisions. The course places contractor analysis within the wider SD/TAR context of schedule control, cost management, resource utilisation and coordination between internal and external teams.
Digital twins are presented as a means of evaluating turnaround scenarios and alternative planning decisions before a major maintenance event. Participants will learn how these digital models can support analysis of scope, schedules, resources and potential risks. This helps planners and engineering managers understand dependencies, compare options and reduce uncertainty when preparing complex shutdown or turnaround plans.
The course covers the integration of AI with CMMS, EAM, planning tools and historian systems. Participants will explore how information from these systems can support advanced analytics and more connected turnaround decision-making. This is especially relevant to CMMS/EAM specialists, reliability teams and digital transformation professionals responsible for improving data use across asset management and SD/TAR processes.