Reliability, Availability & Maintainability Analysis

Learn how to apply Reliability, Availability, and Maintainability (RAM) principles to optimise system performance, safety, and efficiency across the asset lifecycle. Gain practical skills to analyse, interpret, and apply RAM results to inform better design, maintenance, and investment decisions.

Course information

Reliability, Availability & Maintainability Analysis training is available in the following formats

Two Hour Awareness Module One Day Face-to-Face Course One Day Virtual Course

Delivery

Virtual Course

Level

Intermediate

Certificate

Attendance

Duration

1 day

CPD

7 hours

Learning objectives

Explain the purpose, scope, and benefits of RAM analysis in supporting system performance and decision-making
Define key RAM terms: reliability, maintainability, availability (including production availability), uptime, and downtime
Describe the steps of a RAM study, from data collection and modelling to interpretation and application
Understand how system configuration, redundancy, and bottlenecks affect overall availability and performance
Apply failure and repair data to estimate system performance over time
Perform basic RAM calculations (e.g., series/parallel reliability, MTBF, MTTR, availability formulas)
Understand the role of simulation tools for complex systems (e.g., Isograph Availability Workbench)
Interpret RAM study results to identify key performance drivers, critical components, and improvement opportunities
Apply RAM outcomes to support investment decisions, debottlenecking, maintenance strategies, and lifecycle planning
Recognise common challenges, data limitations, and uncertainties in RAM analysis
Apply RAM principles through practical exercises or case studies

Key contents

Introduction to RAM: purpose, benefits, and industrial applications
Core concepts and definitions: reliability, maintainability, availability, production availability
Overview of RAM modelling approaches: block diagrams, Markov models, Monte Carlo simulation
Understanding system configurations: redundancy, series-parallel systems, bottlenecks
Data requirements: failure rates, repair times, operating profiles
Basic RAM calculations and techniques: MTBF, MTTR, availability formulas
Overview of RAM software tools: Isograph Availability Workbench, Reliability Workbench
Interpreting RAM results: criticality analysis, improvement strategies, performance optimisation
Using RAM analysis to support business cases, investment planning, and maintenance optimisation
Challenges, uncertainties, and best practices in RAM analysis
Practical workshop or case study: applying RAM principles to a real-world example

Prerequisites

Basic understanding of engineered systems or industrial operations is recommended. No prior experience with RAM analysis or software tools is required.

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Related Services

Reliability, Availability, Maintainability (RAM) Studies

Reliability, Availability, and Maintainability (RAM) modelling evaluates how often plant components and systems fail, how long repairs take, and how these factors affect production availability and uptime. Using RAM insights, operators can improve system design, select reliable equipment, optimise maintenance plans, and align with key standards like IEC 61508, ISO 14224, ISO 20815, and API 581 to minimise downtime, optimise production, and meet performance targets.

Quantitative Risk Assessment (QRA)

Quantitative Risk Assessment (QRA) systematically estimates the likelihood and consequences of hazardous events, including fires, explosions, and toxic releases. QRA provides a robust, data-driven basis for managing safety, environmental, and economic risks in high-hazard industries, supporting ALARP demonstration and informed decision-making.

Safety Cases and Safety Reports

A Safety Case or HSSE (Health, Safety, Security & Environmental) Case demonstrates that a high-hazard facility has identified its major accident hazards, assessed the associated risks, and implemented sufficient controls to reduce those risks to a tolerable or ALARP level. Safety cases are tailored to industry, site-specific, and regulatory requirements, providing assurance to regulators, workforce, and stakeholders that risks to people, the environment, and assets are systematically identified, managed, and continuously monitored. They play a central role in regulatory regimes such as the Nuclear Installations Act, UK Offshore Installations (Safety Case) Regulations, COMAH Regulations, and Seveso III Directive.

DSEAR Risk Assessment

DSEAR (Dangerous Substances and Explosive Atmospheres Regulations) assessments are required in UK workplaces handling flammable gases, vapours, mists, dusts, or explosive atmospheres. These assessments instill the ALARP principle, starting with inherent safety, ventilation, ignition control and mitigation. By focusing on both technical and organisational controls, DSEAR risk assessments help protect people (as well as property) from fire, explosion, and related hazards.

Failure Modes and Effects Analysis (FMEA)

Failure Modes and Effects Analysis (FMEA) is a systematic approach to identifying potential failure modes in components, equipment, systems, procedures, or software, assessing their consequences (i.e. local and global effects), and prioritising actions to mitigate or eliminate associated risks. FMEA is widely used across industries to improve design robustness, enhance reliability, optimise maintenance, and strengthen operational resilience. When combined with criticality assessment (FMECA), it provides quantitative prioritisation to inform decision-making and risk management in alignment with international standards such as IEC 60812, ISO 31000, and IEC 61511.

Bowtie Analysis

Bowtie analysis provides a visually intuitive, structured approach to understanding how hazards can lead to major accident events and how barriers prevent or mitigate these outcomes. By mapping threats, consequences, and barriers, bowtie diagrams foster engagement, ownership, and accountability at all organisational levels. Our expertise in bowtie analysis helps organisations strengthen barrier management, demonstrate ALARP, and proactively manage operational risk.

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