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Development of an expert system for optimal design of the grinding process

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Abstract

The physical or empirical modeling of the grinding process and the effects of its parameters on the workpiece quality is sophisticated. This is due to the extreme complexity of the process. So far, no remarkable success could be made by the proposed models to achieve a reliable and effective design and control of the process. This article introduces an expert system to enhance the design of the grinding process. A pilot system was built considering three main grinding outputs, including surface roughness, material removal rate and normal grinding force. Based on the primary experimental results, the system suggests the proper grinding and dressing parameters to obtain the desired surface roughness with the highest possible material removal rate and least normal force. The analysis is based on the regression correlation development and the “Non dominated Sorting Genetic Algorithm II” optimization method. The validation tests conducted in three different surface roughness and normal force ranges proved the reliability and effectiveness of the proposed expert system. The surface roughness was predicted with less than 7% deviations from the experiments. The predicted normal grinding forces, in most cases, were in good agreement with the experiments with higher than 75% accuracy. Although the wheel balancing issues at the highest cutting speed (vc = 35 m/s) caused large deviations between the predicted and measured forces.

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Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Arak University of Technology, Arak, Iran

    Mohammad Baraheni

  2. Institute for Precision Machining-KSF, Hochschule Furtwangen University, Tuttlingen, Germany

    Bahman Azarhoushang, Amir Daneshi & Mohammadi Kadivar

  3. Faculty of Mechanical Engineering, University of Kashan, Kashan, Iran

    Saied Amini

Authors
  1. Mohammad Baraheni
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  2. Bahman Azarhoushang
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  3. Amir Daneshi
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  4. Mohammadi Kadivar
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  5. Saied Amini
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Contributions

M.B. had 30% contribution in conducting the research and analyzing the results; B.A. had 25% contribution in supervising the research; A.D. had 20% contribution in providing facilities; M.A.K. had 20% contribution in providing materials and tests; S.A. had 5% contribution for financial aid.

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Correspondence to Mohammad Baraheni.

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It is approved that the paper is original and has been written based on the authors’ own finding. All the figures and tables are original, and every expression from other published works was acknowledged and referenced.

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Baraheni, M., Azarhoushang, B., Daneshi, A. et al. Development of an expert system for optimal design of the grinding process. Int J Adv Manuf Technol 116, 2823–2833 (2021). https://doi.org/10.1007/s00170-021-07493-6

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  • DOI: https://doi.org/10.1007/s00170-021-07493-6

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