Bayesian Process Monitoring, Control and Optimization

CRC Press

This reference presents a state-of-the-art survey of the applications of Bayesian statistics in process monitoring, control, and optimization. Addressing challenges faced by engineers, the book adopts Bayesian approaches for actual industrial practices. It solves these problems through modern computational techniques, such as Markov chain Monte Carlo (MCMC) and other Monte Carlo simulation-based approaches. The book illustrates MCMC with the variance component model, using WinBUGS\u00AE and CODA. The authors also explore the advantages and the disadvantages of Bayesian techniques and frequentist approaches. Additional coverage includes inferential problems and response surface methods (RSM). > Although there are many Bayesian statistical books that focus on biostatistics and economics, there are few that address the problems faced by engineers. Bayesian Process Monitoring, Control and Optimization resolves this need, showing you how to oversee, adjust, and optimize industrial proco