COURSE OVERVIEW:

Advanced machinery reliability analysis is a strategic discipline that moves beyond reactive maintenance to a data-driven approach for maximizing the lifecycle of industrial assets. This course explores the integration of statistical tools, failure physics, and engineering judgment to predict and prevent machine breakdowns. Understanding how to quantify reliability through mathematical models is essential for optimizing maintenance intervals and reducing the total cost of ownership in complex industrial plants.

The scope of this training includes the application of Weibull analysis, Mean Time Between Failures (MTBF) calculations, and the study of bathtub curve dynamics for different equipment classes. Participants will examine the relationship between operational parameters, such as load and temperature, and the physical degradation mechanisms of rotating and static components. The coverage extends to the development of Reliability Centered Maintenance (RCM) programs and the implementation of Failure Mode and Effects Analysis (FMEA) for critical systems.

Furthermore, the course addresses the human and organizational factors that influence machinery reliability. It delves into the use of root cause failure analysis (RCFA) to identify systemic issues and the application of life cycle costing to justify reliability improvements. By focusing on both the analytical techniques and the management frameworks, this course empowers professionals to transform maintenance departments into reliability-focused organizations that contribute to the plant’s profitability.

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

1. Apply Weibull distribution models to predict component failure rates.
2. Calculate and interpret MTBF, MTTR, and Availability metrics.
3. Perform detailed Failure Mode and Effects Analysis (FMEA) on machinery.
4. Conduct systematic Root Cause Failure Analysis (RCFA) using logic trees.
5. Develop Reliability Centered Maintenance (RCM) strategies for plant assets.
6. Analyze the economic impact of machinery downtime using Life Cycle Costing.
7. Optimize spare parts inventory based on reliability data and criticality.
8. Implement proactive maintenance tasks to eliminate "infant mortality" failures.
9. Assess the effectiveness of Condition Monitoring programs in improving reliability.
10. Utilize Pareto analysis to prioritize maintenance and engineering efforts.
11. Design reliability into new equipment through technical specifications.
12. Evaluate the impact of human factors and training on machine longevity.
13. Integrate reliability data into Computerized Maintenance Management Systems (CMMS).
14. Facilitate reliability improvement cross-functional team workshops.

TARGET AUDIENCE:

This course is intended for reliability engineers, maintenance managers, asset management professionals, and lead mechanical engineers responsible for improving the performance and longevity of industrial machinery.

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximise the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.