Course Details

Objective

By the end of this course, participants will be able to:

• Recognize early warning signs of abnormal operations
• Understand human and technical contributors to abnormal events
• Apply structured decision-making and escalation protocols
• Use tools such as alarm management, root cause analysis, and data monitoring
• Strengthen operational discipline and reduce unplanned downtime

Content

Day 1

Module 1: Introduction to Operational Abnormalities

• Definition of operational abnormality
• Common causes and consequences of abnormalities
• Types of abnormal situations (mechanical, process, human)
• Case studies of abnormal events and lessons learned

Day 2

Module 2: Human Factors and Situational Awareness

• Role of human error in abnormal operations
• Decision-making under stress
• Situational awareness and early warning signs
• Crew resource management principles

Module 3: Process Safety and Abnormal Situation Management

• Connection between abnormality management and process safety
• Hierarchy of controls for abnormal conditions
• Alarm management (ISA-18.2 standard)
• Control system response to abnormal situations

Day 3

Module 4: Detection and Diagnosis

• Indicators of abnormal operations (pressure, temperature, vibration, alarms, etc.)
• Diagnostic tools and techniques
• Using data analytics and condition monitoring
• Role of control room operators and field personnel

Module 5: Response and Mitigation

• Structured response protocols (e.g., ESD, isolation, depressurization)
• Communication and escalation procedures
• Real-time decision-making tools
• Use of Standard Operating Procedures (SOPs) and deviation handling

Day 4

Module 6: Root Cause Analysis and Learning

• Incident vs. abnormality vs. near miss
• RCA tools: 5 Whys, Fishbone, Barrier Analysis
• Documentation and reporting systems
• Integrating findings into operational procedures and training

Module 7: Operational Discipline and Culture

• Building a culture of operational vigilance
• Leadership and frontline engagement
• Role of operations management in sustaining reliability
• Integration with Reliability and Integrity programs (e.g., RCM, RBI)

Day 5

Module 8: Technology and Digital Tools

• Use of AI, machine learning, and predictive analytics
• Digital twins and real-time monitoring
• Abnormal Situation Management (ASM) software
• HMI/SCADA design for early detection

NOTE:

Pre & Post Tests will be conducted

Case Studies, Group Exercises, Group Discussions, Last Day Review & Assessments will be carried out.

Methodology

A highly interactive combination of lecture and discussion sessions will be managed to maximize the amount and quality of information, knowledge and experience transfer. The sessions will start by raising the most relevant questions and motivate everybody finding the right answers. The attendants will also be encouraged to raise more of their own questions and to share developing the right answers using their own analysis and experience.

All attendees receive a course manual as a reference.

This interactive training workshop includes the following training methodologies

30% Lectures

30% Workshops and work presentation

20% Group Work & Practical Exercises

20% Videos & General Discussions