Maintenance and Reliability Courses

Duration

2 days

Program and objectives

The goal of this course is to provide the attendees with the basic concepts, methodological competences and quantitative modelling tools used for Reliability, Availability and Maintainability (RAM) analysis. The course covers the following topics:

  • Basic concepts: failure time distribution, reliability, hazard function, bath-tub curve.
  • Probability distributions commonly used in RAM analyses.
  • Reliability of simple systems.
  • Reliability Block Diagram (RBD).
  • Fault Tree Analysis (FTA).
  • Availability and Maintainability.

Who Should Take the Course

Individuals involved in the performance of system RAM analysis, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on fundamentals of RAM analysis and its use for achieving improvements in systems or processes performance.

Duration

1 day

Program and objectives

The course presents the Reliability Centered Maintenance (RCM) technique, which is commonly used in industry to set proper maintenance policies by a systemic process of system analyses for better understanding of the relationships among scheduled maintenance and reliability. The course provides an overview of the RCM process and details the steps required to implement it. The attendees will understand the fundamentals of RCM, its benefits and how it can be applied in day-to-day operations. Successful completion of this course will foster the attendees understanding of RCM concepts and processes, and enable participation in or supervising of RCM analyses.

Exercise section

The course includes the development of a scaled-down RCM case study as hand-on case study.

Who Should Take the Course

Individuals responsible for or involved in the organization and implementation  of maintenance processes, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on fundamentals of RCM and its use for achieving reliability improvements. Basic knowledge of the FMEA is advantageous for a quick understanding of the course contents.

Duration

1 day

Program and objectives

The goal of this course is to provide the attendees with the methodological competences and the quantitative tools required to implement or supervise the development of Risk-Based Maintenance (RBM) strategies. The topics covered in the course are:

  • The formation and concepts of Safety and Risk.
  • Reverse Fault Tree Analysis.
  • Analytic Hierarchy Process.
  • RBM applications.

Exercise section

The course provides examples of successful applications of RBM to industrial systems.

Who Should Take the Course

Individuals responsible for or involved in the organization and implementation  of maintenance processes, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on fundamentals of RBM and its use for achieving plant performance improvements through better maintenance.

Duration

3 days

Program and objectives

The goal of this course is to provide the attendees with the concepts, methodological competences and modeling tools for Prognostics and system Health Management (PHM), for on-condition and predictive maintenance of industrial components and systems. The course covers the following topics:

  • Fault detection: Auto Associative Kernel Regression, Principal Component Analysis.
  • Fault detection: applications to industrial case studies;
  • Fault Diagnostics: Classification methods for fault diagnostics: K Nearest Neighbor Clustering Methods; Artificial Neural Networks; Ensemble Systems.
  • Fault Diagnostics: Applications to industrial case studies.
  • Fault Prognostics: Methods for fault prognostics: Experience based (Weibull distribution), Statistical methods (Auto-Regressive Moving Average _ARMA, Hidden Markov models, Proportional hazard models).
  • Applications to fault prognostics.

Exercise section

The course includes some exercise sections with computers about fault detection, diagnostics and prognostics.

Seminar

The course includes an industrial seminar: “Maintenance in electrical power plants; Monitoring the conditions of industrial equipment in practice”.

Who Should Take the Course

Individuals responsible for and involved in the development of maintenance policies and its improvement by PHM forward on-condition and predictive methods, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on fundamentals of PHM and its use for improving the system performance through a more effective and efficient maintenance setting.

Duration

2 days

Program and objectives

The goal of this course is to provide the attendees with the methodological competences and the modeling tools used for setting proper maintenance policies on industrial components and systems. The course trains in the concepts and procedures at the basis of the safe and economic operation of industrial systems. The course covers the following topics:

  • Maintenance concepts.
  • Importance of maintenance in industry.
  • Maintenance approaches: Corrective (corrective); Preventive (Planned, On Condition, Predictive).
  • Computerized Maintenance Management Systems.
  • Maintenance Costs.
  • Maintainability.
  • Maintenance strategic planning: Reliability Centered Maintenance, Risk-based maintenance(basic concepts)

Exercise section

The application of different maintenance approaches to a practical case study will be discussed.

Who Should Take the Course

Individuals responsible for and involved in the optimization of maintenance policies, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on fundamentals of Maintenance Engineering.

Duration

2 days

Program and objectives

Information about the life time distribution of a component can be inferred from ‘life test’, whereby a number of identical units of the component are operated and their lifetimes recorded. The knowledge of the stochastic behavior of the component allows estimating the probability of having a failure at future time instants, and, on this basis, making maintenance decisions.

The course covers the following topics:

  • Complete and censored datasets.
  • Maximum Likelihood and Method of moments estimation techniques.
  • Confidence intervals.
  • Probability plots.
  • Goodness of fit tests.
  • Practical case studies: Exponential distribution, Weibull distribution.
  • Multi-state system parameter estimation: case studies.
  • Bayesian estimation.

Exercise section

The course includes some exercise sessions with computers.

Who Should Take the Course

Individuals responsible for and involved in the characterization of the statistical behavior of operated components, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on the basics of statistics in support of reliability engineering.

Duration

1 day

Program and objectives

This course introduces the basics of the Markov approach to system modeling for reliability and availability analysis. In this approach, the stochastic process of evolution of the system in time is described through the definition of the system states, the possible transitions among these states and their rates of occurrence. The various system states are defined in terms of the states of the components comprising the system. The components are not restricted to having only two possible states but rather may have a number of different states such as functioning, in standby, degraded, partially failed, completely failed, under maintenance, etc.; the various failure modes of a component may also be defined as states. The transitions between the states occur randomly in time, because caused by various mechanisms and activities such as failures, repairs, replacements and switching operations, which are random in nature. Under specified conditions, the stochastic process of the system evolution may be described as a so-called Markov process, which is mathematically defined by a system of probability equations that can be solved either analytically or numerically.

Exercise session

An example of the technique application on a practical case study will be presented.

Who Should Take the Course

Individuals responsible for and involved in investigating advanced modeling techniques of system behaviors, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on fundamentals of the technique.

Duration

1 day

Program and objectives

This course gives an introduction to the theory of Monte Carlo simulation for reliability and availability analysis. The presentation is kept at an intuitive and practical level. The Monte Carlo simulation method is shown to offer a powerful tool which can be of great value in the analysis of complex systems, due to its inherent capability of achieving a closer adherence to reality in the representation of the system stochastic behavior.

Exercise section

The course includes some exercise sessions with computers.

Who Should Take the Course

Individuals involved in and responsible for reliability, availability and maintainability (RAM) analyses of complex systems, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on the fundamentals of Monte Carlo method.

Duration

1 day

Program and objectives

This course illustrates the use of Evolutionary Algorithms (EAS) such as the Genetic Algorithms and the Differential Evolution within the area of RAMS (Reliability, Availability, Maintainability and Safety) optimization. The methodological concepts behind the operation of the EAs are presented. The steps of the algorithm are sketched to some details for both the traditional breeding procedure as well as for more sophisticated breeding procedures. The necessity of affine transforming the fitness function, object of the optimization, is discussed in detail, together with the transformation itself. Finally, two examples of application are illustrated with regards to problems of reliability allocation and periodic inspection and maintenance.

Exercise section

The course includes some exercise sessions with computers.

Who Should Take the Course

Individuals involved in and responsible for solving optimization problems, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on the fundamentals of the Evolutionary Algorithms.

Duration

1 day

Program and objectives

Petri nets serve mainly as the pictorial representation of dynamic processes and systems, as they allow a deep understanding of the connections among the sub-systems and components. They are widely used in reliability engineering, especially in dynamical contexts.

Exercise section

The course includes some exercise sessions with computers.

Who Should Take the Course

Individuals involved in and responsible for solving optimization problems, in different fields of application (military, transportation, manufacturing or production). Engineers, maintenance professionals, plant/facility managers and operators will benefit from the knowledge the course provides on the fundamentals of Petri Nets

to sign up  for the courses, please contact ats@aramis3d.com