ReliabilityEngineering

Reliability engineering is an engineering discipline dedicated to ensuring that a system or component performs its intended function without failure under specified conditions for a defined period. It involves predicting, measuring, preventing, and mitigating failures to maximize system availability and lifecycle value. Reliability engineering is closely linked with maintainability, availability, and safety, and RAM analysis is often used to assess overall performance and risk.

Key methods include reliability prediction and life data analysis (such as Weibull, exponential, and lognormal distributions), failure modes and effects analysis (FMEA or FMECA), and fault tree analysis (FTA). Practices like reliability-centered maintenance (RCM), design for reliability (DfR), redundancy, and risk assessment are common. Data-driven techniques rely on field data, accelerated life testing, reliability growth testing, and survival analysis. Common metrics include MTBF, MTTR, overall availability, failure rate, and reliability growth factors used to quantify performance and guide improvements.

In practice, reliability engineering influences product design, materials selection, manufacturing processes, and maintenance planning. Early-stage activities include requirements allocation and reliability predictions; later stages focus on testing, reliability demonstration, and field monitoring. The field aims to reduce downtime, extend service life, lower life-cycle costs, and satisfy safety and regulatory requirements across industries such as aerospace, automotive, electronics, energy, and process industries.

Standards and guidance from international and industry bodies shape methods and reporting. Widely referenced frameworks include MIL-HDBK-217, IEC 61508, ISO 26262, and IEC 60300, with ongoing advances in prognostics, data analytics, and reliability growth modeling.