Real-time quality monitoring continues to gain interest within the manufacturing domain as new and faster sensors are being developed. Unfortunately, most quality monitoring solutions are still based on collecting data from the end product. From a process improvement point of view, it is definitely more advantageous to proactively monitor quality directly in the process instead of the product, so that the consequences of a defective part can be minimized or even eliminated. In this dissertation, new methods for in-line process monitoring are explored using multiple sensors. In the first case, a new cutting force-based monitoring methodology was developed to detect out of control conditions in a broaching operation. The second part of this thesis focusses on the development of a test bed for monitoring the tool condition in a turning operation. The constructed test bed includes the combination of multiple sensors signals including, temperature, vibrations, and energy measurements.

Here, the proposed SPC strategy integrates sensor data with engineering knowledge to produce quick, reliable results using proven profile monitoring techniques. While, the already existing methods are based on raw process data which requires more features to monitor without any loss of information. This technique is straight forward and able to monitor the process comprehensively with less number of features. Consequently, this also adds to the group of tools that are available for the practitioner.