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TECHNICAL BRIEFS

Monitoring of Self-Tapping Screw Fastenings Using Artificial Neural Networks

[+] Author and Article Information
Kaspar Althoefer

Department of Mechanical Engineering, King’s College London, Strand, London WC2R 2LS, United Kingdom e-mail: k.althoefer@kcl.ac.uk

Bruno Lara

Cognitive Robotics, Max Planck Institute for Psychological Research, Amalienstrasse 33, D-80799 Munich, Germany e-mail: lara@psy.mpg.de

Lakmal D. Seneviratne

Department of Mechanical Engineering, King’s College London, Strand, London WC2R 2LS, United Kingdome-mail: lakmal.seneviratne@kcl.ac.uk

J. Manuf. Sci. Eng 127(1), 236-243 (Mar 21, 2005) (8 pages) doi:10.1115/1.1831286 History: Received December 05, 2002; Revised April 21, 2004; Online March 21, 2005
Copyright © 2005 by ASME
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References

Nevis,  J. L., and Whitney,  D. E., 1978, “Computer-Controlled Assembly,” Sci. Am., 238, No. 2, pp. 62–74.
Smith, S. K., 1980, “Use of Microprocessor in the Control And Monitoring of Air Tools while Tightening Thread Fasteners,” Eaton Corporation, Autofact West, Proc. Society of Manufacturing Engineers, Dearborn, MI, 2 .
Tsujimura,  T., and Yabuta,  T., 1991, “Adaptive Force Control of Screwdriving with a Positioning-controlled Manipulator,” Rob. Auton. Syst., 7, pp. 57–65.
Matsumura, M., Itou, S., Hibi, H. and Hottori, M., 1995, “Tightening Torque Estimation of a Screw Tightening Robot,” Proc. IEEE International Conference on Robotics and Automation, IEEE, Nagoya, Japan, 1–3 , pp. 2108–2112.
Althoefer,  K., Seneviratne,  L. D., and Shields,  R., 2000, “Mechatronic Strategies for Torque Control of Electric Powered Screwdrivers,” Proc. Institution of Mechanical Engineers, Part C, J. Mech. Eng. Sci., 214, No. 12, pp. 1485–1501.
Ogiso, K., and Watanabe, M., 1982, “Increase of Reliability in Screw Tightening,” Proc. 4th International Conference on Assembly Automation, Tokyo, Japan.
Dhayagude,  N., Gao,  Z., and Mrad,  F., 1996, “Fuzzy Logic Control Of Automated Screw Fastening,” Rob. Comput.-Integr. Manufact., 12, No. 3, pp. 235–242.
Ngemoh, F. A., 1997, “Modelling the Automated Screw Insertion Process,” Ph.D. thesis, King’s College, University of London, UK.
Seneviratne,  L. D., Ngemoh,  F. A., Earls,  S. W. E., and Althoefer,  K., 2001, “Theoretical Modelling of the Self-Tapping Screw Fastening Process,” Proc. Institution of Mechanical Engineers, J. Mech. Eng. Sci., 215, No. 2, pp. 135–154.
Ngemoh, F. A., Seneviratne, L. D., and Earles, S. W. E., 1992, “Theoretical Modeling of Screw Tightening Operations,” Proc. ASME European Joint Conference on Systems, Design and Analysis, London, UK, 1 , pp. 189–195.
Seneviratne,  L. D., Ngemoh,  F. A., and Earles,  S. W. E., 2000, “An Experimental Investigation of Torque Signature Signals for Self-tapping Screws,” Proc. Institution of Mechanical Engineers, Part C, J. Mech. Eng. Sci., 214, No. 2, pp. 399–410.
Bishop, C. M., 1995, Neural Networks for Pattern Recognition, Clarendon, Oxford, UK.
Bruzzone,  L., and Prieto,  D. F., 1998, “Supervised Training for Radial Basis Function Neural Networks,” Electron. Lett., 34, No. 11, pp. 1115–1116.
Lara, B., Althoefer, K., and Seneviratne, L. D., 2000, “Artificial Neural Networks for Screw Insertions Classification,” Proc. IEEE Robotics and Automation Conference (ICRA’2000), San Francisco, CA, pp. 1912–1917.
Lara, B., Althoefer, K., and Seneviratne, L. D., 1999, “Use of Artificial Neural Networks for the Monitoring of Screw Insertions,” Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’99), Kyongiu, Korea, 1 , pp. 579–584.
Lara Guzman, B., 2000, “Intelligent Monitoring of Screw Insertions,” Ph.D. thesis, King’s College, University of London, UK.
Zell, A., Mamier, G., Vogt, M., Mache, N., Hübner, R., Döring, S., Herrmann, K.-U., Soyez, T., Schmalzl, M., Sommer, T., Hatzigeorgiou, A., Posselt, D., Schreiner, T., Kett, B., Clemente, G., and Wieland, J., 1995, “SNNS. Stuttgart Neural Network Simulator,” User manual, Ver. 4.1., Report No. 6/95, University of Stuttgart, Germany.
Klingajay, M., Seneviratne, L. D., and Althoefer, K., 2003, “Identification of Threaded Fastening Parameters Using the Newton Raphson Method,” Proc. IEEE/RSJ Intl. Conference on Intelligent Robots and Systems (IROS’03), Las Vegas, Nevada, pp. 2055–2060.

Figures

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Key stages during an insertion of a self-tapping screw, progressing in the following order: T0, TE, TP, TB, TF, TF2
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Experimental torque profiles for 12 insertions on polycarbonate plate (thin lines) and the corresponding theoretical prediction (bold line)
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Output values as training evolves (simulated insertion signals). Single case experiment.
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Output values as training evolves (simulated insertion signals). Variation of hole diameter experiment.
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Activation output on test set after 20 training cycles. Four-output classification experiment using simulated signals.
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The screwdriver, torque sensor, and instrumentation used for the acquisition of experimental data
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Output values as training evolves (real insertion signals). Single case experiment.
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Insertion signals from screwdriver. Variation of hole diameter.
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Output values as training evolves (real insertion signals). Variation of hole diameter experiment.
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Insertion signals from screwdriver. Four-output classification experiment.
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Network activation output for the test set after 200 training cycles. Four-output classification experiment using real insertion signals. All signals are correctly attributed.

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