Every successful business needs high plant reliability, and in the current economic environment, this is more crucial than ever. Engineers must make sure that every option is being used to maximize plant performance and reliability because the costs of equipment failure and decreased output might be high. Reliability Centered Maintenance (RCM), one of the five basic approaches that engineers can take to plant maintenance, is one of the least applied (perhaps due to its lack of widespread understanding).

Course Objectives:

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

Explore and understand the power contained in maintenance history records (failure data), and how this can be harnessed using statistical approaches to improve maintenance (and hence overall plant) performance
Analyze failure data using a range of first principles and industry-standard methods, all implemented in Microsoft Excel
Understand failure mode shape analysis and thereafter to extract failure mode shapes from history record data and use this to optimize Planned Maintenance (PM) activities
Understand the theory and application of reliability modelling
Apply the theory of reliability modeling to a range of practical case studies, using the teaching version of an industry-standard reliability modelling software package
Develop from first principles a practical and comprehensive reliability modelling and statistical analysis toolbox in Microsoft Excel, and use this to analyze numerous practical case studies
Use reliability models to predict future spare parts requirements and the proportions of maintenance time that will be spent in reactive (breakdown) and proactive (PM/PPM) maintenance activities
Explore the implementation of a Reliability Centered Maintenance approach as part of a modern maintenance management strategy, including a detailed cost-benefit analysis of a real application

Who Should Attend?

It is highly recommended to Reliability Engineers, Maintenance Planners, Maintenance Supervisors and Maintenance Engineers.

Course Outlines:

Maintenance strategies and the power of historical data

Fundamental approaches to maintenance
Formulating a maintenance strategy
The importance of maintenance history records
Understanding plant performance
An introduction to the statistical analysis of failure data
The principles of failure data analysis
Industry-standard measures of reliability (Availability, MTBF, MTTR, etc)
Extensive hands-on experience
Open discussion

Statistical analysis of failure data

Pareto analysis, rank order charts and standard deviation
Linear regression models and determining model accuracy
Failure mode analysis
Interpreting failure mode shapes
Extracting failure mode shapes from real data
Optimizing PM activity using mode shape analysis
Knowing when to use a breakdown maintenance approach
Extensive hands-on experience
Open discussion

Reliability models and approaches to modelling

The principles of RCM and reliability modelling
Developing a reliability model
Weibull statistics and the range of Weibull models (2 parameter, 3 parameter, maximum likelihood, maximum accuracy)
The Weibull curve and plotting data on a Weibull scale
Defining parameters: shape, scale, mean life, minimum life, characteristic life, standard deviation
Model accuracy assessment (observed model accuracy and hypothesis rejection)
Interpreting model results
Confidence levels and Weibull critical values
Key graphical functions:

The reliability function: survival probability
The cumulative distribution function
The failure probability density function
The failure rate function

Extensive hands-on experience
Open discussion

Cost based maintenance and the basis of a reliability toolbox

Converting reliability model data into cost based maintenance decisions
Optimizing PM activity based on cost and by using reliability predictions (note that the course will NOT cover the costing of maintenance activities, but will assume that this information is already known)
Calculating the cheapest PM interval for age-based replacement policies
Graphing costs versus PM interval
Predicting future failures
Predicting spares utilization
Development of the key components of a reliability toolbox
Extensive hands-on experience
Open discussion

The finalization of a comprehensive reliability toolbox in Excel

The cost of maintenance convenience and making informed maintenance optimization decisions
Incorporating real world effects within reliability models
Specifying the PM interval and understanding the implications of doing this
Completing the reliability toolbox
Graphing toolbox results
Toolbox testing and comparison of results with best-of-breed modelling software
Extensive hands-on experience
Overall review of concepts learned and how they can be applied in practice

Filters