Machining of titanium alloys is particularly challenging due to the inherent properties of these materials, which are characterized by high chemical reactivity, low thermal conductivity, low modulus of elasticity, and high strength at elevated temperatures. When dealing with such low-machinability materials, the development of smart monitoring procedures can significantly improve the machining process performance in the framework of zero-defect manufacturing as well as reduce manufacturing cost and increase productivity. For instance, tool condition monitoring (TCM) during machining allows decreasing tool costs by optimizing tool life and implementing condition-based tool replacement strategies (i.e., replacing tools only when they are close to their end of life) instead of conservative time-based tool replacement strategies (where the tool is replaced after a predetermined time independently of its real wear conditions) and it would help reduce machine and workpiece damage risk in case of tool breakage by allowing for fast emergency halting of the process. To improve and optimize machining processes applied to low-machinability materials such as titanium alloys, diverse studies in the literature have proposed the use of different sensor systems for online monitoring of tool conditions, chip formation, surface integrity, process conditions, chatter detection, etc. This chapter aims at presenting the most relevant sensor monitoring applications concerning the major machining processes applied to titanium alloys, classified on the basis of the specific sensor monitoring scope. Finally, the most recent developments of machining process monitoring in the Industry 4.0 framework are presented with reference to the implementation of cloud manufacturing for smart diagnosis services based on on-line sensor monitoring.