Abstract
Achieving a more robust and reliable product using intelligent and emerging tools and technologies relying on systems engineering is not only a progress key for any organization but also a durability factor in today's competitive industrial environment. The reliability and productivity go back to the Six Sigma concept in the early 1990s to alleviate the high failure rate of products. While reliability has progressively been considered in industrial applications, many researchers are still trying to push the boundaries of the reliability field of research. Depending on the problem's complexity, dimension, uncertainties, etc., each method has its pros and cons. To promote the level of performance various approaches have been adopted. Concurrent engineering (CE), uncertainty-based design optimization (UDO), their combination with machine learning (ML) techniques on one side, and recently popular procedures such as digitalization and model-based systems engineering (MBSE) are on the other side of reliability progress. This chapter presents a systematic survey of the past and indicates future trends in the reliability-based design optimization field.