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Fuzzy-nets-based in-process surface roughness adaptive control system in end-milling operations

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Abstract

A fuzzy-nets-based in-process adaptive surface roughness control (FN-ASRC) system was developed to be able to adapt cutting parameters in-process and in a real time fashion to improve the surface roughness of machined parts when the surface roughness quality was not meeting customer requirements in the end-milling operations. The FN-ASRC system was comprised of two sub-systems: (1) fuzzy-nets in-process surface roughness recognition (FN-IPSRR); and (2) fuzzy-nets adaptive feed rate control (FN-AFRC) sub-system. To test the system, while the machining process was taking place, the FN-IPSRR system predicted the surface roughness, which was then compared to the desired surface roughness. If the desired surface roughness was not met, then, the FN-AFRC system proposed a new feed rate for the machining process. Once the feed rate was changed, and the cutting continued, the output of the surface roughness of the new feed rate was compared with the desired surface roughness. This proposed FN-ASRC system has been demonstrated to be successful using 25 experimental tests with 100% success rate.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, Nankai Institute of Technology, 542, Tsauton, Nantou, Taiwan

    Lieh-Dai Yang

  2. Department of Industrial Education and Technology, Iowa State University, Ames, IA, 50011, USA

    Joseph C. Chen

  3. Department of Mechanical Engineering, Nankai Institute of Technology, 542, Tsauton, Nantou, Taiwan

    Han-Ming Chow & Ching-Tien Lin

Authors
  1. Lieh-Dai Yang
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  2. Joseph C. Chen
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  3. Han-Ming Chow
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  4. Ching-Tien Lin
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Correspondence to Lieh-Dai Yang.

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Yang, LD., Chen, J., Chow, HM. et al. Fuzzy-nets-based in-process surface roughness adaptive control system in end-milling operations. Int J Adv Manuf Technol 28, 236–248 (2006). https://doi.org/10.1007/s00170-004-2361-7

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  • DOI: https://doi.org/10.1007/s00170-004-2361-7

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