Implementing an Effective Preventive and Predictive Maintenance ProgramOil and Gas Engineering

In any city around the world 00447455203759 Course Code: AC/2024/121

Course Description

Course Duration: Five Training Days

Course Language: Arabic or English

Include:

Scientific material with TAB

Workshops

Reception and farewell at the airport

Daily lunch

Coffee Break


Introduction: Effective Planned & Predictive Maintenance 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 program has been designed to benefit both qualified new professionals as well as experienced professionals who may be involved in the rollout of a comprehensive. Maintenance system or auditing an existing system. It covers all the steps required in developing a successful Planning & Predictive Maintenance program from system development until a well-managed Maintenance system is in place and operational.

Targeted Groups: The training is intended for:- Maintenance Personnel. Maintenance technicians. Maintenance engineers. Reliability engineers. Maintenance supervisors/managers. Operations Personnel. Operators who work closely with the equipment. Production supervisors/managers. Engineering Personnel. Reliability engineers. Management Personnel. Plant managers. Maintenance managers. Operations managers. Support Staff. Those involved in data analysis and interpretation. Administrative staff responsible for documentation and record-keeping. Cross-Functional Teams.

Training Objectives: By the end of this course the participants will be able to: Understanding Maintenance Concepts. Equipment Knowledge. Maintenance Planning and Scheduling. Condition Monitoring Techniques. Predictive Maintenance Technologies. Maintenance Procedures and Best Practices. Safety and Compliance. Cross-Functional Collaboration. Performance Monitoring and Continuous Improvement.

Targeted Competencies: Equipment Knowledge. Maintenance Procedures. Condition Monitoring Techniques. Data Interpretation. Analytical Competencies. Problem-Solving. Data Analysis. Risk Assessment. Communication and Collaboration. Interdepartmental Communication. Documentation. Safety and Compliance. Continuous Improvement. Leadership and Management. Resource Management.

Course Content: Unit 1: The Need for Maintenance: Failure Mode Effect & Criticality Analysis (FMECA): Causes of Failures. Likelihood & Severity of Failure - Risk Analysis. Reliability Centered Maintenance (RCM). Optimization of Maintenance Decisions: Failure Pattern Identification. Statistical Analysis of Failures. Weibull Analysis. Zero Base Budgeting: Define the production requirement. Define the maintenance requirement.

Unit 2: Developing the CMMS: Database Construction: Installed Asset Base. Hierarchical Structure. Procedures and Plans. Resources: Dedicated Manpower. Contractors. Specialist Tools. Maintenance Strategies: Centralized/Decentralized. Life/Emergency/Corrective/Planned. Planned & Predictive.

Unit 3: The Planning Function: Roles & Responsibilities: The Planners. Job Initiators. Maintenance Trades. Job Planning: Planning Corrective Work. Integrate Planning with Procedures. Resource Leveling. Scheduling: Long Term Scheduling with Production. Medium- & Short-Term Scheduling. Planning Department Interfaces.

Unit 4: Predictive Maintenance: Potential Failure Analysis (PFA): Integration of PFA with FMECA & RCM. Understanding the P-F Interval. Decide which Technologies to Apply. Vibration Analysis: Detectable Faults. Setup Parameters. Monitoring & Protection. On-Line or Off-Line. Supporting Technologies: Infrared Thermography. Passive Ultrasonics. Oil Analysis.
Unit 5: Control of the Maintenance Process: CMMS Integration: Predictive Maintenance Interface. Optimizing PM Kit Usage with PdM. Operational planning. Reporting: Monthly PM & PdM reports for Management. Financial Feedback Reports. Budget Control. Key Performance Indicators: Reliability & statistics – MTBF, Reliability, etc. Work request backlog analysis. Customer feedback analysis.