The application of statistical methods for process control monitoring has become an essential activity to ensure process stability. The main objective of statistical process control is to recognize and identify the presence of abnormal control charts patterns that are disrupting the natural behaviour of processes. Most studies on the subject are aimed at recognizing a single abnormal pattern at a time. However, in many industrial processes is fairly common the existence of concurrent control chart patterns, which means, the occurrence of more than one abnormal control chart pattern at the same time. As a result, the following article organizes and analyzes existing information regarding concurrent control chart pattern recognition with the hope of providing a concise summary of the contributions to date and a useful guide to orientate further research. The methodological analysis follows a comprehensive classification framework whose categories were designed to assure an in-depth analysis of the most critical topics.