A review of in-situ monitoring and process control system in metal-based laser additive manufacturing

Metal-based laser additive manufacturing (MLAM) is receiving significant attention in industrial fields due to its capacity to manufacture complex and high-performance metal components directly from three-dimensional models. However, as-built components are still subjected to various issues, such as dimension accuracy, surface quality, and internal defects, seriously hindering the development of MLAM. To overcome these issues, process monitoring and control in MLAM should be emphasized to achieve high-quality parts. Taking the critical segments of a closed-loop control system in MLAM as the research route, this paper aims to develop an in-depth survey of in-situ process sensing and control strategies in MLAM. Various signal monitoring methods are described, principles of induced defects and corresponding scientific control strategies are introduced, and closed-loop control strategies in MLAM are summarized. The current development status and limitations of sensing methods and closed-loop control frameworks are discussed. The paper concludes by advising the future research directions for in-situ monitoring, process control, and performance of machine learning models in MLAM. This review provides a valuable reference and a blueprint for developing advanced intelligent control of MLAM in industrial applications.