Probability and Its Applications to Reliability, Quality Control, and Risk Assessment
MIT OpenCourseWare offers this graduate-level course on probability theory applied to engineering risk and reliability. Topics cover basic probability rules, random variables and distribution functions, and statistical methods, building toward reliability assessment of mechanical and electrical components, simple structures, and redundant systems. Students learn Bayesian methods in engineering, event-tree and fault-tree analysis, common-cause failure modeling, and human reliability models for complex systems. The course also covers uncertainty propagation techniques including Monte Carlo methods and Latin Hypercube Sampling, plus an introduction to Markov models. Examples are drawn from nuclear engineering, waste repositories, and mechanical systems, reflecting its origin in MIT's Nuclear Science and Engineering department. Materials include lecture notes and assignments freely available through MIT OpenCourseWare, with no certificate offered. The course suits engineering students needing rigorous quantitative tools for assessing risk and reliability in complex technical systems.