Chris Weir — Active Contributor

Most engineering projects operate within the familiar constraints of cost, time and quality. Decisions are constantly made to balance these three, often under pressure.

This relationship can be illustrated as the quality triangle, sometimes summarised as “faster, cheaper, better – pick any two.”

Reliability sits right at the centre of this trade space.

When cost or schedule is compressed, reliability is frequently treated as something that can be “managed later”. In the short term, that can appear to work. In the long term, it rarely does.

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The cost of poor reliability is often underestimated because much of it is hidden.

What organisations tend to see first are the immediate costs of repair, such as parts, labour and downtime. What is less visible, but often far more significant, is everything that follows.

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In practice, no system is failure-free. What often matters most is how quickly and effectively the system can be restored, and whether it is available when actually needed.

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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.

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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.

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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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