Degradation models play a critical role in quality engineering by enabling the assessment and prediction of system reliability based on data. The objective of this paper is to provide an accessible introduction to degradation models. We explore commonly used degradation data types, including repeated measures degradation data and accelerated destructive degradation test data, and review modeling approaches such as general path models and stochastic process models. Key inference problems, including reliability estimation and prediction, are addressed. Applications across diverse fields, including material science, renewable energy, civil engineering, aerospace, and pharmaceuticals, illustrate the broad impact of degradation models in industry. We also discuss best practices for quality engineers, software implementations, and challenges in applying these models. This paper aims to provide quality engineers with a foundational understanding of degradation models, equipping them with the knowledge necessary to apply these techniques effectively in real-world scenarios.

翻译：退化模型在质量工程中发挥着关键作用，其能够基于数据实现系统可靠性的评估与预测。本文旨在提供关于退化模型的简明导论。我们探讨了常用的退化数据类型，包括重复测量退化数据和加速破坏性退化试验数据，并综述了通用路径模型和随机过程模型等建模方法。文中重点讨论了可靠性估计与预测等关键推断问题。通过材料科学、可再生能源、土木工程、航空航天及制药等不同领域的应用案例，阐明了退化模型在工业界的广泛影响。我们还探讨了质量工程师的最佳实践、软件实现以及应用这些模型时面临的挑战。本文旨在为质量工程师提供对退化模型的基础性理解，使其掌握在实际场景中有效应用这些技术所需的知识。