Implementation of Cognitive Chips in Machining Error Attenuation

Maki K. Rashid

Abstract

Machining is a complex process that requires a high degree of precision with tight geometrical tolerance and surface finish. Those are confronted by the existence of vibration in the turning machine tool. Overcoming a micro level vibration of a cutting tool using smart materials can save old machines and enhance development in designing new generations of machine tools. Using smart materials to resolve such problems represent one of the challenges in this area. As a continuation from previous work for the transient solution for a tool tip displacement using pulse width modulation (PWM) technique that was implemented for smart material activation to compensate for radial disturbing cutting forces. A Fuzzy algorithm is developed to control the actuator voltage level to improve dynamic performance. Such technique together with the finite element method as dynamic model proved a great successfulness. To implement such results in real life industrial system we may use chips that mimic human brain as developed recently by IBM which is intelligent to learn through incidents, find patterns, generate ideas and understand the outcomes to reduce tool vibration error.

References

  1. Abboud, N. N., Wojcik, G. L., Vaughan, D. K., Mould, J., Powell, D. J., and, Nikodym, L., (1998), Finite Element Modeling for Ultrasonic Transonic Transducers, Proceedings SPIE Int. Symposium on Medical Imaging, San Diego, Feb 21-27, 1-24.
  2. Dold, G., (1996), Design of a Microprocessor-Based Adaptive Control System for Active Vibration Compensation Using PMN Actuators, MS Thesis, University of Maryland at College Park.
  3. Eshete, Z., (1996), In Process Machine Tool Vibration Cancellation Using Electrostrictive Actuators, Ph.D. Thesis, University of Maryland at College Park.
  4. Frankpitt, B. A., (1995), A Model of the Dynamics of a Lathe Toolpost that Incorporates Active Vibration Suppression, Institute for System Research, University of Maryland at College Park.
  5. Gopalakrishnan, V., Fedewa, D., Mehrabi, M. G., Kota, S. and Orlandea, N., (2002), Design of Reconfigurable Machine Tools, ASME J. Manuf. Sci. Eng., Technical Briefs, 124, 483-485.
  6. Hurtado, J. F., and Melkote, S. N., (2001), Improved Algorithm for Tolerance-Based Stiffness Optimization of Machining Fixtures, ASME J. Manuf. Sci. Eng., 123, 720-730.
  7. Luan, J., and, Lee, F. C., (1998), Design of a High Frequency Switching Amplifier for Smart Material Actuators with Improved Current Mode Control, PESC 98, Vol. 1, Fukuoka, 59-64.
  8. Moon, Y., and, Kota, S., (2002), Design of Reconfigurable Machine Tools, ASME J. Manuf. Sci. Eng., Technical Briefs, 124, 480-483.
  9. Passino, K. M., and Yurkovich, S., (1998), Fuzzy Control, Addison Wesley Longman, Inc.
  10. Piefort, V., (2001), Finite Element Modeling of Piezoelectric Active Structures, Ph.D. Thesis, ULB, Active Structures Laboratory- Department of Mechanical Engineering and Robotics.
  11. Rashid, M. K. (2011). Neurofuzzy Implementation in Smart Toolpost To Improve Performances. Global Journal of Researches in Engineering (A), Volume XI, Issue VII, Version 1.0 December, 1-10.
  12. Rashid, M. K., (2004), Smart Actuator Stiffness and Switching Frequency in Vibration Suppression of a Cutting Tool, Smart Materials and Structures, Vol.13: 1-9.
  13. Zhang, G., Ko, W., Luu, H., and Wang, X. W., (1995), Design of a smart Tool Post for Precision Machining, Proceedings of the 27th CIRP International Seminar on Manufacturing Systems, Ann Arbor, MI, 157-164.
  14. Zienkiewicz, O. C., and, Taylor, R. L., (2001), The Finite Element Method, Fifth edition Vol.1: The Basis, Butterworth-Heinemann.
Download


Paper Citation


in Harvard Style

K. Rashid M. (2012). Implementation of Cognitive Chips in Machining Error Attenuation . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 262-267. DOI: 10.5220/0004106302620267


in Bibtex Style

@conference{icinco12,
author={Maki K. Rashid},
title={Implementation of Cognitive Chips in Machining Error Attenuation},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2012},
pages={262-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004106302620267},
isbn={978-989-8565-21-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Implementation of Cognitive Chips in Machining Error Attenuation
SN - 978-989-8565-21-1
AU - K. Rashid M.
PY - 2012
SP - 262
EP - 267
DO - 10.5220/0004106302620267