Diagnostic of Machines and Root Cause Analysis of Failures

Diagnostic of Machines and Root Cause Analysis of Failures

Methodology:

• Interactive training methods including questioning, group exercises, videos, case studies, and presentations on best practices and fundamentals of reliability improvement.
• Participants have opportunities to discuss their practical experiences, identify problems, and make improvements for immediate implementation in their organizations.

Course Objectives:

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

• Understand machine functions and effectively identify the causes of failures.
• Conduct effective diagnostics of machine failures and determine their root causes.
• Apply effective controls to prevent recurring failures.
• Engage the organization in an effective diagnostic process for failures.
• Analyze critical equipment and machine systems to prevent future breakdowns.

Target Audience:

This training course targets maintenance managers, operational managers, reliability specialists, maintenance engineers, experienced supervisors, and individuals responsible for planning and functional management of enterprise machinery and equipment.

Program Content:

1. Purpose of failure diagnosis and prevention methods and monitoring.
2. Understanding business needs.
3. Impact of machine failures on profits and customer satisfaction levels.
4. Risk assessment and prioritization.
5. Introduction to the integrated model for maintenance excellence.

Understanding machine functions and types of failures:

• Understanding machine functions.
• History of modeling types of failures and common errors for machine users.
• Introduction to types of failures.

Principles of failure diagnosis:

• What is Root Cause Failure Analysis (RCFA)?
• Data collection and root cause exploration.
• Accurate diagnosis using obstacle analysis and change identification.
• Using the Five Whys technique to determine the root cause.
• Organizing diagnosis processes by cause types and fault trees.
• Importance of factual and data-driven analysis.

Principles of failure prediction:

• What is Failure Mode and Effects Analysis (FMEA)?
• Determining the appropriate time for conducting FMEA for different types of failures.
• Errors in conducting FMEA and how to avoid them.
• FMEA as part of an integrated process for reliable maintenance.

Adhering to preventive controls for failures:

• Types of controls.
• How to select appropriate controls.
• Enhancing the sustainability of controls.

Practical application methodologies:

• Organizing your work to learn from failures.
• Stakeholders involved in achieving change.
• Importance of communication.
• Applying continuous improvement in the learning-from-failures process.