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Statistical study of surface texture and chip formation during turning of AISI 1020 steel: Emphasis on parameters Rsk, Rku, and Rk family and on the chip thickness ratio


Turning is recognized as one of the main manufacturing processes. Feed and cutting depth are investigated by researchers who aim to continuously improve this process. Faced with sustainability challenges, “greener” manufacturing engineering is sought, using statistical methods and machining techniques with minimal or no use of cutting fluid. Generally, roughness quantifies the quality of the machined surface, an important property in tribology. Classical amplitude parameters are insufficient to determine functional properties and are necessary to associate them with more significant ones. Chip formation also influences surface quality, as it is related to the interaction at the chip/tool interface. This study investigated the influence of the feed rate and cutting depth on the Rq, Rsk, Rku, Rk, Rpk and Rvk roughness parameters, and the chip thickness ratio during longitudinal dry turning of AISI 1020 steel. Trend measurements, a normality test, factorial analysis of variance and linear correlation were used in the methodology. Results showed predominant influence and correlation of the feed on the roughness parameters and the chip thickness ratio compared to the cutting depth. The analysis performed on the insert rake surface led to the hypothesis that the chip breaker geometry provides changes in chip deformation as the cutting depth increases. Through linear and polynomial trend lines drawn on the graphs, it was found that the roughness and the chip thickness ratio have a positive correlation with the feed, but in different proportions.

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Availability of data and materials

The datasets obtained during the current work are available from the corresponding author upon request.

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The authors would like to thank the Centro Federal de Educação Tecnológica de Minas Gerais (Belo Horizonte, Minas Gerais - Brazil) for supporting the study; Guilherme Euler da Silva, Miriane Cristina Silva Souza and Ana Luiza Ramos, for their support in machining tests, roughness measurement and statistical analysis; the Centro Universitário UNA (Belo Horizonte, Minas Gerais - Brazil), for supporting the machining tests and the roughness measurement process; the Application Technician André Epifânio and the Customer Service Representative Amauri Suga (WALTER Tools company, Sorocaba, São Paulo - Brazil) for supplying the cutting inserts and the tool holder; and Deynaba Kane Ba (Faculty of Letters, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais - Brazil) for proofreading the text in Portuguese.


This work was supported by the CEFET-MG Research Promotion Agency in the Master’s Program/CEFET-MG for the Postgraduate Program in Materials Engineering and the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) - Finance Code 001.

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Elhadji Cheikh Talibouya Ba was responsible for the general development of the article, created the study proposal and carried out the laboratory activities and statistical analysis of the data. Paulo Sérgio Martins supervised the study, was responsible for acquiring the inputs used in the study, offered support in developing the methodology and analyzed the results, and also revised the structure and text of the final article. Marcello Rosa Dumont supervised the study, revised the structure and text of the final article, and was responsible for the financial support for research support from the Centro Federal de Educação Tecnológica Minas Gerias.

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Correspondence to Elhadji Cheikh Talibouya Ba.

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Talibouya Ba, E.C., Martins, P.S. & Dumont, M.R. Statistical study of surface texture and chip formation during turning of AISI 1020 steel: Emphasis on parameters Rsk, Rku, and Rk family and on the chip thickness ratio. Int J Adv Manuf Technol 121, 8257–8283 (2022).

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  • Factorial analysis of variance
  • Linear correlation analysis
  • Feed
  • Chip thickness ratio
  • Cutting depth
  • Roughness parameters