State-of-the-art in-suit process monitoring and control for additive manufacturing (AM) is getting more attention in pursuit of improving the quality of AM products. Moreover, the advanced manufacturing system of Industry 4.0 comprises a large number of data collecting and feedback units to operate it functionally. They are interconnected with machines, control units and computing devices. The working of these devices needs to be understood by the end-users to understand their function as well as their troubleshooting. As these devices are new in the manufacturing workplaces, their breakdown may lead to several losses in productivity when they malfunction while in operation. This paper deals with various in situ process monitoring and control devices such as vision sensors, thermal sensors and acoustic sensors used in various research and development for metal additive manufacturing (MAM). In situ monitoring in AM could help in process parameters optimization, defect detections, troubleshooting of machine parts, temperature monitoring, residual stress control, process improvement, etc. Moreover, instruments used in in situ process monitoring also help in the collection of a huge amount of data required for applying artificial intelligence (AI) in AM. AI can further help in improving the process capabilities of AM by improving the accuracy and providing real-time monitoring and control of process parameters.