Predictive & AI-Driven Maintenance Strategies

Course Introduction

Seattle International Institute for Training offers a specialized training course in Predictive & AI-Driven Maintenance Strategies. This course is tailored for professionals in the oil & gas sector seeking to enhance their technical knowledge in engineering systems, maintenance reliability, asset integrity, and predictive technologies.

Course Objectives

- Develop advanced strategies for asset reliability and availability.

- Implement predictive and condition-based maintenance programs.

- Apply international engineering standards and safety practices.

- Optimize equipment performance and lifecycle management.

- Integrate digital tools and AI for maintenance planning.

Target Audience

- Maintenance Engineers and Supervisors

- Reliability and Rotating Equipment Engineers

- Asset Integrity and Inspection Specialists

- Mechanical, Electrical, and Instrumentation Engineers

- Plant Managers, Operations Engineers, and HSE Coordinators

- Professionals from KOC, KNPC, Aramco, ADNOC, KIPIC, and other energy companies

Course Outline

Day 1: Engineering & Asset Fundamentals

·         Engineering systems in oil & gas operations

·         Introduction to asset lifecycle management

·         Failure modes and maintenance strategies

·         Maintenance KPIs and performance indicators

·         Overview of international standards (ISO 55000, API)

·         Case study: asset failure analysis

Day 2: Reliability & RCM Applications

·         Reliability-Centered Maintenance (RCM) framework

·         Failure Modes and Effects Analysis (FMEA)

·         Criticality assessment and asset prioritization

·         Maintenance optimization modeling

·         RCM in rotating and static equipment

·         RCM implementation case examples

Day 3: Predictive & Condition-Based Maintenance

·         Introduction to predictive maintenance tools

·         Vibration analysis and thermography

·         Oil analysis and motor current diagnostics

·         Condition-Based Monitoring (CBM) systems

·         Data-driven maintenance planning

·         Integration of CBM with CMMS systems

Day 4: Digital Transformation & AI Tools

·         AI and machine learning in maintenance

·         Smart sensors and IoT for monitoring

·         Predictive analytics and dashboards

·         Digital twins and asset simulation

·         Remote diagnostics and cloud integration

·         Cybersecurity in maintenance systems

Day 5: Strategy, Safety & Best Practices

·         Developing maintenance strategies and KPIs

·         Asset integrity and safety management

·         Root Cause Analysis (RCA)

·         Risk-Based Inspection (RBI)

·         Team roles and workflow integration

·         Final workshop: full maintenance strategy design