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Application of Fuzzy Logic in the Analysis of Surface Roughness of Thin-Walled Aluminum Parts

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Abstract

This paper presents the development and application of fuzzy logic in the milling of thin-walled parts for the purpose of analyzing surface roughness. Surface roughness is an important performance indicator of finished components. Depending on conditions such as feed ratio and wall thickness, different machining strategies can be applied. The objective was to analyze and determine the influence of the machining conditions on surface roughness. The model for analyzing and determining surface roughness of the aluminum alloy AL 7075 was trained (design rules) and compared by using the experimental data. The average deviation of the compared data for surface roughness was 12.3%. The effect of the feed ratio, wall thickness and machining strategy as well as their interactions in machining are thoroughly analyzed and presented in this study.

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Abbreviations

MRR:

Material removal rate

Ra:

Surface roughness—arithmetic mean roughness (µm)

Rz:

Surface roughness—max. height roughness (µm)

CNC:

Computer numerical control

MISO:

Multi-input–single-output

MIMO:

Multi-input–multiple-output

Al:

Aluminum

ANN:

Artificial neural network

MMC:

Metal matrix composites

MLP:

Multi-layer perceptron

RBF:

Radial basis function

PSO:

Particle swarm optimization

ANFIS:

Adaptive network-based fuzzy interface system

FIS:

Fuzzy interface system

MF:

Membership functions

3D:

Three dimensional

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Acknowledgement

This paper is part of a research on projects—TR 35025 and TR 35015 supported by the Ministry of Education, Science and Technological Development, Republic of Serbia.

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Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovica 6, Novi Sad, 21000, Serbia

    Jovan Vukman, Dejan Lukic, Dragan Rodic & Mijodrag Milosevic

  2. Faculty of Mechanical Engineering, University of Banja Luka, Vojvode Stepe Stepanovica 71, 78000, Banja Luka, Bosnia and Herzegovina

    Stevo Borojevic

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  1. Jovan Vukman
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Correspondence to Jovan Vukman.

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Vukman, J., Lukic, D., Borojevic, S. et al. Application of Fuzzy Logic in the Analysis of Surface Roughness of Thin-Walled Aluminum Parts. Int. J. Precis. Eng. Manuf. 21, 91–102 (2020). https://doi.org/10.1007/s12541-019-00229-3

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