In this study, a Mahalanobis-Taguchi system (MTS)-based diagnostic and root cause analysis scheme for monitoring grip length of pull-type fasteners in real-time is presented. The proposed approach is implemented on a fastening tool integrated with a strain gage, a linear variable differential transformer, a pressure sensor, and a mote for wireless communication. Experiments show that the process signature of strain-over-displacement ratio versus displacement has unique features that can be used to determine the grip length related deviations. The proposed approach takes as input various characteristics, such as peak strain, peak displacement, and depth and width of a bowl-shaped dip on the process signature in order to make real-time decisions. The experiments show that the proposed approach is effective in determining grip length deviations and in communicating the decision in real-time via a wireless network to a base station. Overall, the proposed architecture has merits to (1) detect quality problems in real-time during the fastening process and (2) reduce post-process inspection, thereby improving quality while reducing cost. In addition, the approach facilitates 100% data collection on each fastener as opposed to traditional statistical process control (SPC) techniques, which rely on sampling.