Reliability, Availability and Maintainability Crash Course

Reliability, Availability and Maintainability Crash Course

Reliability, Availability and Maintainability (RAM) is used to estimate the availability of a system.

A Reliability, Availability and Maintainability Study (RAMS) is used as a decision making tool to increase the availability of the system, and thus increase the overall profit as well as reducing the life cycle costs.

The main objectives of a RAM analysis is for it to be used as a decision making tool to increase the availability of the system, and thus increase the overall profit as well as reducing the life cycle costs (inclusive of the cost of maintenance, lost production, operating, etc.).

RAM analysis can be carried out on systems and facilities of different types and sizes in various industries ranging from oil and gas, water and waste water treatment, nuclear, process, manufacturing and many more.

As well as suggesting tangible improvements, a Reliability, Availability and Maintainability analysis provides confidence that the system will meet its operational targets and support the through-life viability of a project.

By applying Reliability, Availability and Maintainability techniques in the early phases of the project lifecycle, organizations identify any shortfalls against targets and proposes practical solutions which yield significant improvements in reliability, availability and maintainability.

For some, the benefit of using RAM analysis during all design phases of physical security systems may seem an unnecessary design and implementation cost.

However, RAM analysis and evaluation is important to ensure the design provides security at minimum risk with no costly rework and provides predictive failure rates for operations and maintenance planning.

By understanding RAM goals throughout the design, sources of failure can be identified and planned for more effective sustainment management. Of course, components will fail eventually, but with effective analysis and planning, the system sustainment can manage system failures and effectively decrease operational downtime.

RAM analysis in the conceptual design phase ensures site-specific requirements evolve from the performance-based requirements.

Reliability, Availability and Maintainability analysis during conceptual design provides a mechanism for designing security into the system by implementing aspects of Security by Design.

Experts in this field say that because there may be more than one way to meet performance-based requirements, early understanding of the options for the design allows for all stakeholders to understand compliance options and trade space.

RAM analysis is particularly important when resolving safety (fail safe) and security (fail secure) design conflicts. This results in providing a basis for the Competent Authority to make informed decisions when evaluating the options with respect to risk.

Reliability, Availability and Maintainability Crash Course Description

Reliability, Availability and Maintainability Crash Course provides a comprehensive training on the fundamental concepts of Reliability, Availability and Maintainability (RAM) and processes and techniques necessary to use RAM in practice.

Reliability, Availability and Maintainability Crash Course focuses on RAM management actions in order to help attendees to ultimately enhance the performance of materiel systems.

Reliability, Availability and Maintainability Crash Course will also discuss both ‘design for RAM’ and ‘RAM verification’ activities to provide the viewpoints of producer and customer.

Reliability, Availability and Maintainability Crash Course also covers the mathematics of the essential modeling approaches, the application of certain modeling techniques and how they can be employed to approximate and boost the availability of a system.

Learn About:

• RAM Engineering
• Background and the ‘value’ of RAM
• Advantages of RAM engineering
• RAM engineering context and process
• RAM Mathematics and Statistics
• Key probability distributions
• Monte Carlo Simulation
• RAM Activities
• Reliability modeling
• RAM testing and confidence intervals
• RAM requirements engineering
• Design for Reliability (DFR)
• Reliability Centered Maintenance (RCM)
• RAM data management
• RAM System Modeling and Analysis
• Fault trees
• Reliability Block Diagrams (RBDs)
• Repairable System Analysis
• Reliability Growth Modeling
• RAM Organizational Considerations and Maturity

What Will You Gain by Taking RAM Crash Course?

• You can define reliability, availability, maintainability and their differences
• You will know the benefits and limitations of reliability, availability, and maintainability
• You will understand qualification, quality conformance, and their differences
• Define the nature of basic system reliability models
• You will have sufficient knowledge and understanding of FMEA

Audience

Reliability, Availability and Maintainability Crash Course is a 4-day training designed for:

• Project managers
• Project engineering managers
• Capability development personnel
• Project technical personnel
• Systems engineers
• Hardware and software engineers
• Process engineers
• Maintenance professionals
• Design engineers
• Reliability specialists
• Product/ program managers

Learning Objectives

Upon the completion of Reliability, Availability and Maintainability Crash Course, attendees are able to:

• Understand the importance of RAM in the process industries
• Understand how RAM is linked to life cycle cost
• Describe the fundamental concepts of RAM
• Explain the key factors affecting plant availability
• Construct their own databank
• Adjust maintenance strategy
• Derive system Reliability Block Diagrams, containing more complicated elements such as recycling and buffer storage
• Model process reliability/ availability
• Effectively enhance reliability, availability and throughput
• Cost-effectively employ standby equipment
• Explain RAM requirements
• Articulate the implications of RAM requirements
• Test against their requirements
• Apply a design for reliability program to meet RAM standards
• Anticipate warranty costs
• Identify the risks of incorrectly passing and failing formal demonstration tests
• Plan for in-service Reliability monitoring
• Understand the relationship between RAM requirements and a Performance Based Contract
• Analyze when their systems should be replaced
• Understand different metrics used to analyze a system’s maintainability and availability
• Explain the steps to an effective RCM program
• Apply appropriate techniques to evaluate the optimum part replacement intervals for Preventive Maintenance (PM) activities
• Describe various methods used to model system availability

Course Outline

Overview

• Reliability definitions
• RAM definition
• Historical background
• Common mathematical expressions
• Reliability Block Diagrams (RBD)
• Monte Carlo Methods
• Reliability target allocation
• Empirical prediction modeling
• Physics of Failure prediction modeling
• Introduction to growth models
• FMEA/FMECA
• FTA
• Dependency Modeling
• State-Diagrams
• Markov Methods
• Maintainability
• Maintainability distributions and metrics
• Maintainability predictions and allocation
• Renewal theory
• Availability
• Modeling maintenance actions
• RCM

Maintainability and Availability

• Maintainability review
• Reliability Centered Maintenance (RCM)
• Preventative Maintenance (PM) principles
• Determining optimum PM intervals
• Maintainability distributions and metrics
• Maintainability predictions and allocation
• Modeling maintenance actions
• Imperfect repairs (restoration factors)

Reliability Mathematics and Failure Physics

• Rounding Data
• Integration formulas
• Differential formulas
• Partial derivatives expansion of (a + b)ⁿ
• Failure physics
• Probability theory
• Fundamentals
• Probability theorems
• Concept of reliability
  • Reliability as probability of success
  • Reliability as absence of failure
  • Product application
  • Interface definition and control

Exponential Distribution and Reliability Models

• Exponential
• Failure rate dimensions
• Mean time between failures
• Calculations of Pc for single devices
• Distribution and reliability models
• Distribution rate definition
• Reliability models
• Calculation of reliability for series-connected
• Calculation of reliability or parallel-connected devices (redundancy)
• Calculation of reliability for complete systems

Using Failure-Rate Data

• Variables affecting failure rates
• Operating life test
• Storage test
• Summary of variables affecting failure rates
• Part failure rate data
• Improving system reliability through part derating
• Use of application factor
• Predicting reliability from part failure rate data
• Predicting reliability by rapid techniques
• Use of failure rates in tradeoffs
• Non-operating failures
• Applications of reliability predictions to control of equipment reliability
• Standardization as a means of reducing failure rates
• Allocation of failure rates and reliability
• Importance of learning from each failure
• Failure reporting, analysis, corrective action, and concurrence

Applying Probability Density Functions

• Probability density
• Application of density functions
• Cumulative probability distribution
• Normal distribution
• Normal density function
• Properties of normal distribution
• Symmetrical two-limit problems
• One-limit problems
• Non-symmetrical two-limits problems
• Application of normal distribution to test analysis and reliability predictions
• Effects of tolerance on a product

Testing for Reliability

• Demonstrating reliability
  • Pc illustrated
  • Pw illustrated
  • K-Factors illustrated
• Test objectives and methods
• Test objectives
• Attribute test methods
• Statistical confidence
• Test-To-Failure etmhods
• Life test methods

Software Life Cycle

• Life cycle activities
• Life cycle models
• Fault, manpower and cost profiles over life cycle
• Software Development Life Cycles (SDLC)
• Development phases
• What constitutes testing

Software Testing

• Definition of software testing
• Why Test?
• What composes testing?
• What to include in the test sample
• How to select the test sample
• How many inputs should be tested
• Limitations of testing

Safe Introduction of Software Using Scale Up

• The problem
• What can you learn from “n” successes?
• Extensions
• Applications

Factors Affecting Software Reliability

• Application type
• Methodologies
• Product characteristics
• Testing/verification
• Schedule
• Maintenance
• Operational/user profile

Overview of Software Reliability Models

• Types of software reliability models
• Nomenclature used in modeling
• Assumptions of the models

Data Required for Models

• Types of data
• Minimum fault data needed
• Setting up data collection system
• Root-cause analyzing bad data

Software Reliability Prediction Models

• Prediction models
• Rome laboratory TR-92-52
• Rome laboratory TR-92-15
• Musa’s execution time model
• Putnam’s model
• Historical data collection

Software Reliability Estimation Models

• Objectives
• Types of Estimation Models
• Fault Count
  • Exponential
  • Shooman model
  • Lloyd-Lipow model
  • Musa’s basic model
  • Musa’s Logarithmic model
  • Goel-Okumoto model
  • Historical data collection model
  • Weibull models
• Test coverage model
  • IEEE test coverage model
  • Leone’s test coverage model
  • Test success model
• Tagging models
  • Seeding
  • Dual test group model
• Bayesian models
• Thompson and Chelson’s model
• Goodness of fit

Software Reliability Metrics

• Objectives
• Metrics to apply according to your process capability
• Metrics applied in industry
• Wrong-used metrics

Software Fault Trees

• Why Fault Tree is used?
• Applying fault trees to software

Software FMEAs

• Why FMEA is used?
• Applying FMEAs to software

System Reliability Software Redundancy

• Series configuration
• Mission oriented
• Semi-Markov
• Parallel concurrent
• Voting redundancy

Improving Software Reliability

• Evaluating your product and process
• Techniques to improve software reliability

Managing Software Reliability

• Matrix of responsibilities
• Cost benefit of improvement

Numerical Reliability

• Framework reference
• Errors in a single arithmetic operation
• Computing errors for an entire computation

Reliability Management

• Roots of reliability management
• Planning a reliability management organization
• General management considerations
• Logistics support and repair philosophy
• Reliability management activities
• Performance requirements
• Specification targets
• Field studies
• Human reliability
• Analysis methods
• Human errors
• Presentation of reliability

Additional Metrics

• Availability
• Other metrics

Warranty and Maintenance

• Product warranties review
• A review of maintenance
• Warranty and corrective maintenance
• Warranty and preventive maintenance
• Extended warranties and service contracts
• Stochastic point processes
• Perfect maintenance
• Minimal repair
• Imperfect or worse repaid
• Complex maintenance policy
• Reliability growth

Preventive Maintenance Models

• Block replacement models
• Age replacement models
• Ordering models
• Inspection models

Maintenance and Optimum Policy

• Replacement policies
• Preventive maintenance policies
• Inspection policies

Accelerated Life Testing

• Design of accelerated life testing plans
• Accelerated life testing models
• Extensions of the proportional hazards model

Reliability, Availability and Maintainability Crash Course