The optimization of an autonomous real-time process using curve fitting signature signal

The thread fastening operations have been used for decades with the purpose of joining one component to another. Its tasks are popular because they permit easy to disassembly for maintenance, relocation and recycling. The threaded fastening process is typically carried out manually since it is very difficult problem to automate. As a result, there is very little published research on automating threaded fastenings. This paper investigates the problem of automated monitoring on the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw fastening. The proposed strategy is integrated with the automating threaded assembly system. The monitoring task needs to be identified and fitted the required signal from the online and optimization process. Its results are shown with up-to five insertion stages can be identified over three different fasteners.