Preventive & Predictive Maintenance

Course Introduction

Effectively planned Preventive & Predictive Maintenance integrated with the workflow is critical for a successful company and an integral part of maintenance management strategies such as RCM, RBM, TPM, and even 6-Sigma. This comprehensive 5-day training course designed to benefit both qualified new professionals as well as experienced professionals who may be involved in the rollout of a comprehensive Maintenance & Asset Management process or auditing an existing process. It covers all the steps required in developing a successful Preventive & Predictive Maintenance Program from failure behavior and finding the right preventive maintenance task until a well-managed preventive & predictive maintenance program, fully integrated with the workflow and the CMMS.

Leading industrial organizations are evolving away from reactive ("fix-it-when-it-breaks") management into preventive and predictive management ("anticipating, planning, and fix-it-before-it-breaks"). This evolution requires well-planned and executed actions on several fronts.

Objectives

• Preventive & predictive maintenance strategies and their position within Asset Management
• Risk Based Maintenance
• Maintenance & reliability engineering best practices
• Best practices in planning and scheduling (workflow management)
• The application of CMMS (Computerized Maintenance Management System)
• Monitoring & managing performance with Key Performance Indicators (KPI’s)
• Continuous improvement aspects

Professional Impact

At the end of this training course, you will learn to:

• Understand how world-class organizations solve common planning problems
• Improve productivity through use of better, more timely information
• Implement a practical and effective predictive maintenance effort
• Improve consistency and reliability of asset information
• Optimize preventive and predictive maintenance strategies.

Daily Topics

For Registration, Course Outline & more information please contact

NAYEL Training Centre 

T: +971 4 379 7245 | M: +971 50 249 6876 |WhatsApp :+971 50 249 6876

Email [email protected]