Monitoring of Automated Screw Insertion Processes-A Soft Computing Approach

Abstract A soft computing monitoring approach for automated screw insertions is presented. A model based monitoring method is developed with systematically collected experimental data and fundamental process knowledge to verify the quality of assemblies. The model for quality monitoring is based on Linguistic Equations (LE)-a non-linear scaling framework for model variables. Fuzzy reasoning and basic statistical methods are combined to interpret the model residuals and faults. Preliminary tests indicate that the proposed method could successfully cope with changes in manufacturing parameters. Based on the results, the method seems to provide valuable information for quality control of the screw insertion task.

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