Smart manufacturing had a high impact in recent years within the inspection and quality assurance processes, providing innovative technologies in machine learning. Consequently, the article presents a systematic review of the applications of automation to statistical quality control in companies in the industrial sector, deriving subtopics such as artificial vision, intelligent manufacturing, inspection in the different production processes, neural networks, automation through statistical process control techniques and finally quality assurance, in addition, a general analysis of them is shown. Additionally, it is shown that these technologies improve automated manufacturing processes, making them more efficient, with better performance and productivity, also contributing to the optimization of time, cost reduction, strengthening of inspection, and quality assurance. Finally, future research opportunities for industrial applications are identified.