Comparison between least square & Newton Raphson for estimation parameters of an autonomous threaded fastenings

The principle of the thread fastenings have been known and used for decades. Its long applications become to a common manufacturing with the purpose of joining one component to another. Screw insertions are typically carried out manually with having the purpose of joining one component to another. It is more complex to automate, and hence has admitted relatively very small research attention on automating threaded fastenings, and most automated assembly research is focused on the peg-in-hole assembly problem. This paper investigates the problem of an intelligence monitoring strategy for automated screw insertion process based on the parameter estimation. The identification problem deals with quality monitoring strategy, which make use a fastening signature that formed by the torque signal vs. insertion angle curve during the screw insertions. This paper tries to generalise previous works [M. Klingajay et al., 2002] giving a new complete estimation strategy and evaluating its performances in such a way to present the possible developments of next on-line estimation process.