Reliability science experiments

This article reviews the development history of reliability testing, and points out the historical limitations of the existing reliability research paradigm, which is centered on the probability distribution of failure time. This paradigm is only applicable in situations with failure observation data and proves ineffective for the development of innovative products. Specifically, reliability indicators exhibit characteristics of small samples, dynamic behavior, and subjectivity, while quality characteristics are large-sample, static, and objective. Consequently, traditional reliability statistical testing has erroneously adopted the probability sampling acceptance methods for quality management. Moreover, accelerated life testing and accelerated degradation testing, due to their reliance on empirical acceleration models based on failure physics in micro dimensions, are not suitable for true system-level products with function requirements. This paper analyzes the necessity of reliability science experiments aimed at validating causal laws from the perspective of reliability science principles. Reliability experiments are then defined as controlled experiments intended for verification of opportunity causation laws between system margins and performance and performance requirements. The connotations of reliability experiments, including the clarity of laws, black-box epistemology, and opportunity causation, are explored, and fundamental principles for reliability experimental methods—system integration, classification judgement, and optimization equilibrium—are proposed. Furthermore, a model-centered spatiotemporal reliability verification and testing system is established based on the principles of reliability experiments, demonstrating that this system is the only one that is derived based on the connotation of reliability characteristic and meets engineering demands. Finally, the scope of application of reliability scientific experiments is discussed, and developmental ideas for the spatiotemporal reliability verification and testing system are proposed.