Your Reliability Engineering Professional Development Site
Root Cause Analysis (RCA) is the step that turns failure into learning.
Corrective and preventive actions are only effective if they address the real causes of failure, not just the symptoms. RCA provides the structured approach needed to understand why the system allowed the failure to occur in the first place.
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Corrective and preventive action (CAPA) is often considered to be a process with forms to complete, actions to track and audits to satisfy.
In reliability engineering, CAPA is much more fundamental than that. It’s about whether organisations actually learn from failure, or simply respond to it.
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We previously looked at reliability requirements and targets, and where the numbers behind them often come from. Before those numbers are defined, however, there is a more fundamental question to consider:
What outcomes is reliability actually intended to support?
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Reliability requirements are often treated as if they simply exist as numbers in a specification, contract or statement of work.
In reality, every reliability requirement comes from a set of assumptions, trade-offs and constraints, whether those are explicitly recognised or not.
Reliability engineering has a shared language, but not always a shared understanding. Terms are often used loosely or interchangeably, particularly in cross-functional teams.
It would obviously be impractical to cover every term here. From experience however, a few distinctions often cause confusion.
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Reliability engineering rarely happens in isolation. More often, it sits within a project environment shaped by cost, schedule, scope and competing priorities.
In many projects, reliability engineering can be seen primarily as a quantitative exercise that is applied once evidence is needed to validate a design. By then, the opportunity to influence architecture, technology choices, or support concepts may be limited.
The greatest impact of reliability engineering often comes much earlier, through structured questioning and risk-informed thinking. Helping teams recognise that reliability engineering influences design and decision-making throughout the project, not just when evidence is required, is part of the reliability engineer’s contribution within a project environment.
Performance monitoring is often where reliability intent meets operational reality and where many well-intentioned reliability programmes quietly lose focus.
Most organisations monitor something, such as failures, availability, response times or costs. The challenge is choosing indicators that genuinely reflect system performance, rather than those that are simply easy to collect or report.
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Supplier reliability is often treated as something that can be contracted out. When systems fail, the instinct is to point to the supplier, the specification, the warranty, or the contract. In practice, reliability is rarely owned by one party alone.
Suppliers design, build and deliver products, but customers define requirements, operating context, acceptance criteria and support concepts. Reliability outcomes sit in the space between those responsibilities.
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When people hear ethics, they often think of formal codes of conduct, professional standards, or exam topics. In reliability engineering, ethics is usually much more practical – and sometimes uncomfortable.
Ethical issues rarely present themselves as clear right or wrong decisions. They tend to appear as trade-offs, pressures and grey areas, often under time, cost or schedule constraints.
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The role of the reliability engineer is often associated with specific activities or phases of the lifecycle, such as prediction during design, testing during development or data analysis in-service. In practice, reliability engineering is a through-life responsibility, even though its focus changes over time.
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Reliability engineering is viewed by many as a technical discipline focused on analysis, modelling, and prediction. While those skills matter, they are only part of the role.
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Reliability, safety, and quality are commonly considered separate disciplines, each with their own people, processes and tools. In practice, they are deeply interconnected and decisions made in one area almost always influence the others, particularly once systems are in service.
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Reliability, Availability and Maintainability are often discussed together. While closely related in practice, they are not the same thing and the distinctions are not always well understood.
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In Part 2 of Beyond the Numbers, I explored how human reliability principles can be integrated into traditional reliability artefacts such as Reliability Block Diagrams (RBDs), Fault Tree Analysis (FTA) and Failure Modes, Effects and Criticality Analysis (FMECA). Those tools help us understand how systems fail and how different failure paths interact.
But reliability engineering does not end with failure analysis.
In practice, the outputs of FMECA flow directly into the Reliability Centred Maintenance (RCM) process, where failure modes are translated into maintenance strategies such as inspections, condition monitoring, restorations or replacements.
If assumptions about human performance are simplified during reliability analysis, those assumptions do not disappear. They are carried forward, and often amplified, when maintenance requirements are defined.
Maintenance is where reliability modelling becomes an operational commitment.
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Many people associate reliability engineering with metrics, and while they can be helpful when used correctly, they are not the primary benefit of reliability engineering. The real value lies in the thinking and decisions that shape those numbers.
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