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International Journal of Precision Engineering and ManufacturingVolume 21, Issue 1, 1 January 2020, Pages 91-102

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

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  • aFaculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovica 6, Novi Sad, 21000, Serbia
  • bFaculty of Mechanical Engineering, University of Banja Luka, Vojvode Stepe Stepanovica 71, Banja Luka, 78000, Bosnia and Herzegovina

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. © 2019, Korean Society for Precision Engineering.

Author keywords

AluminumDesign of experimentsFuzzy logicSurface roughnessThin-walled parts

Indexed keywords

Engineering controlled terms:AluminumAluminum alloysComputer circuitsDesign of experimentsFuzzy logicThin walled structures
Engineering uncontrolled termsAluminum partsAverage deviationDevelopment and applicationsMachining conditionsMachining strategyPerformance indicatorsThin-walled partsWall thickness
Engineering main heading:Surface roughness

Funding details

Funding sponsor Funding number Acronym
35025
  • ISSN: 22347593
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1007/s12541-019-00229-3
  • Document Type: Article
  • Publisher: SpringerOpen

  Vukman, J.; Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovica 6, Novi Sad, Serbia;
© Copyright 2021 Elsevier B.V., All rights reserved.

Cited by 13 documents

Draz, U. , Hussain, S.
Machining-induced geometric errors in thin-walled parts—a review of mitigation strategies and development of application guidelines
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Prediction of energy efficiency, power factor and associated carbon emissions of machine tools using soft computing techniques
(2023) International Journal on Interactive Design and Manufacturing
Bolar, G. , Joshi, S.N. , Das, S.
Sustainable thin-wall machining: holistic analysis considering the energy efficiency, productivity, and product quality
(2023) International Journal on Interactive Design and Manufacturing
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