• 5-Day Training Course

Rotating Equipment Reliability Optimization

Date Venue Fees Enroll

27 Jan - 31 Jan 2025

Dubai - UAE

$5,500

Enroll Now

24 Mar - 28 Mar 2025

New York - USA

$7,500

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26 May - 30 May 2025

Dubai - UAE

$5,500

Enroll Now

22 Sep - 26 Sep 2025

Dubai - UAE

$5,500

Enroll Now

24 Nov - 28 Nov 2025

Bangkok - Thailand

$6,500

Enroll Now

29 Dec - 02 Jan 2025

Dubai - UAE

$5,500

Enroll Now

Course Introduction

The problem of reliability allocation and optimization of Rotating Equipment has been widely investigated by world-class process companies during the last decade. Instead of concentrating exclusively on redundancy allocation as per the old fashion maintenance, the minimum required reliability for each component of the equipment’s are now estimated in order to achieve the equipment reliability goal with minimum cost. Thereafter, the engineer can decide whether this minimum required component reliability will be achieved via fault avoidance or redundancy. This new philosophy allocates reliability to a component according to the cost of increasing its reliability.

Continuous improvement of plant reliability by optimizing predictive maintenance for rotating equipment is one of the most important challenges plants face today. To know how to effectively prevent equipment failures, conduct a successful root cause failure analysis and improve condition monitoring for pumps, turbines and compressors are continuing challenges for engineers. Proper analysis and solving of chronic problems at the source save time and money.

This intensive training course is designed to explain the effective method of component condition monitoring for use as both a predictive maintenance and root cause analysis tool. It also details the major failure causes, the world-class proven root cause analysis procedure with exercises and case histories, installation, pre- commissioning planning, functional testing and commissioning, preventive maintenance strategies and more.

 

Objectives

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

  • Apply an in-depth knowledge on rotating equipment reliability optimization and recognize the concept of organizing for world class operations particularly the characteristics and steps used toward pacesetter performance
  • Review equipment failure patterns and maintenance affect on reliability and discern how maintenance influences equipment performance
  • Optimize equipment maintenance and replacement decisions through CCM and PDM
  • Recognize the principle of predictive maintenance, employ the various predictive maintenance andcomponent condition monitoring techniques and determine its importance in rotating equipment reliability optimization and continuous improvement
  • Carryout the concept of optimizing reliability particularly condition monitoring and predictive maintenance and identify its components and importance
  • Illustrate root cause failure analysis (RCFA) by identifying its step-by-step process
  • Perform site reliability assessment in order to identify targets for improvement and prepare a sitereliability optimization plan
  • Discuss in detail rotating reliability assurance and carry out machinery installation as per the guidelines
  • Identify pipe stress and soft foot effects on component failures, the effects of misalignment on reliability and conversion to metric system

Training Methodology

This interactive training course includes the following training methodologies as a percentage of the total tuition hours:-

  • 30% Lectures, Concepts, Role Play
  • 70% Workshops & Work Presentations, Techniques, Based on Case Studies & Practical Exercises, Software & General Discussions
  • Pre and Post Test

Target Audience

This course is intended for Managers, Section Heads and Planners as well as Maintenance, Reliability, Machinery, Plant, PMV and Operations Engineers and other Technical Staff.

 

Daily Topics

For registration & more information please contact

NAYEL Training Centre 

Tel: +971 4 5587735 | Mob: +971 54 7962098 |WhatsApp: +971 54 7962098

Email:  [email protected]

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