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  • 1.
    Devotta, Ashwin Moris
    University West, Department of Engineering Science, Research Enviroment Production Technology West.
    Characterization & modeling of chip flow angle & morphology in 2D & 3D turning process2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Within manufacturing of metallic components, machining plays an important role and is of vital significance to ensure process reliability. From a cutting tool design perspective,  tool macro geometry  design  based on physics based  numerical modelling  is highly needed  that can predict chip morphology.  The chip morphology describes the chip shape geometry and the chip curl geometry. The prediction of chip flow and chip shape is vital in predicting chip breakage, ensuring good chip evacuation and lower surface roughness.  To this end, a platform where such a  numerical model’s chip morphology prediction  can be compared with experimental investigation is needed and is the focus of this work. The studied cutting processes are orthogonal cutting process and nose turning process. Numerical models that simulate the chip formation process are employed to predict the chip morphology and are accompanied by machining experiments. Computed tomography is used  to scan the chips obtained from machining experiments and its ability to capture the variation in  chip morphology  is evaluated.  For nose turning process,  chip  curl parameters during the cutting process are to be calculated. Kharkevich model is utilized in this regard to calculate the  ‘chip in process’ chip curl parameters. High speed videography is used to measure the chip side flow angle during the cutting process experiments and are directly compared to physics based model predictions. The results show that the methodology developed provides  the framework where advances in numerical models can be evaluated reliably from a chip morphology prediction capability view point for nose turning process. The numerical modeling results show that the chip morphology variation for varying cutting conditions is predicted qualitatively. The results of quantitative evaluation of chip morphology prediction shows that the error in prediction is too large to be used for predictive modelling purposes.

  • 2.
    Devotta, Ashwin Moris
    et al.
    University West, Department of Engineering Science, Research Enviroment Production Technology West.
    Beno, Tomas
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Characterization of Chip Morphology in Oblique Nose Turning employing High Speed Videography and Computed Tomography Technique2016In: Proceedings International Conference on Competitive manufacturing: January 27, 2016 – January 29, 2016 Stellenbosch, South Africa, Conference on Assembly Technologies & Systems (CIRP), 2016, p. 249-254Conference paper (Refereed)
  • 3.
    Devotta, Ashwin Moris
    et al.
    University West, Department of Engineering Science, Research Enviroment Production Technology West. R&D Turning, Sandvik Coromant, Sandviken.
    Beno, Tomas
    University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing.
    Löf, Ronnie
    R&D Turning, Sandvik Coromant, Sandviken.
    Finite element modelling and characterisation of chip curl in nose turning process2017In: International Journal of Machining and Machinability of Materials, E-ISSN 1748-572X, Vol. 19, no 3, p. 277-295Article in journal (Refereed)
    Abstract [en]

    Finite element (FE) modelling of machining provide valuable insights into its deformation mechanics. Evaluating an FE model predicted chip morphology requires characterisation of chip shape, chip curl and chip flow angles. In this study, a chip morphology characterisation methodology is developed using computed tomography (CT), high-speed imaging and Kharkevich model equations enabling evaluation of FE model’s chip morphology prediction accuracy. Chip formation process in nose turning of AISI 1045 steel is simulated using a 3D FE model for varying feed rate and depth of cut and evaluated against experimental investigations using the employed methodology. The study shows that the methodology is able to characterise chip morphology in nose turning process accurately and enables evaluation of FE model’s chip morphology prediction accuracy. This can enable the finite element model to be deployed in cutting tool design for chip breaker geometry design.

  • 4.
    Devotta, Ashwin Moris
    et al.
    University West, Department of Engineering Science, Research Enviroment Production Technology West.
    Beno, Tomas
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Löf, Ronnie
    Sandvik Coromant AB, Sandviken, Sweden.
    Modeling of Chip curl in Orthogonal Turning using Spiral Galaxy describing Function2016Conference paper (Refereed)
  • 5.
    Devotta, Ashwin Moris
    et al.
    University West, Department of Engineering Science, Research Enviroment Production Technology West. Sandvik Coromant AB, Sandviken, Sweden.
    Beno, Tomas
    University West, Department of Engineering Science, Division of Production Engineering.
    Löf, Ronnie
    Sandvik Coromant AB, Sandviken, Sweden.
    Espes, Emil
    Sandvik Coromant AB, Stockholm, Sweden.
    Quantitative Characterization of Chip Morphology Using Computed Tomography in Orthogonal Turning Process2015In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 33, p. 299-304Article in journal (Refereed)
    Abstract [en]

    Abstract The simulation of machining process has been an area of active research for over two decades. To fully incorporate finite element (FE) simulations as a state of art tool design aid, there is a need for higher accuracy methodology. An area of improvement is the prediction of chip shape in FE simulations. Characterization of chip shape is therefore a necessity to validate the FE simulations with experimental investigations. The aim of this paper is to present an investigation where computed tomography (CT) is used for the characterization of the chip shape obtained from 2D orthogonal turning experiments. In this work, the CT method has been used for obtaining the full 3D representation of a machined chip. The CT method is highly advantageous for the complex curled chip shapes besides its ability to capture microscopic features on the chip like lamellae structure and surface roughness. This new methodology aids in the validation of several key parameters representing chip shape. The chip morphology’s 3D representation is obtained with the necessary accuracy which provides the ability to use chip curl as a practical validation tool for FE simulation of chip formation in practical machining operations. The study clearly states the ability of the new CT methodology to be used as a tool for the characterization of chip morphology in chip formation studies and industrial applications.

  • 6.
    Devotta, Ashwin Moris
    et al.
    University West, Department of Engineering Science, Research Enviroment Production Technology West.
    Beno, Tomas
    University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing.
    Siriki, Ravendra
    Sandvik Materials Technology, Sandviken, Sweden.
    Löf, Ronnie
    Sandvik Coromant AB, Sandviken, Sweden.
    Eynian, Mahdi
    University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing.
    Finite Element Modeling and Validation of Chip Segmentation in Machining of AISI 1045 Steel2017In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 58, p. 499-504Article in journal (Refereed)
    Abstract [en]

    The finite element (FE) method based modeling of chip formation in machining provides the ability to predict output parameters like cutting forces and chip geometry. One of the important characteristics of chip morphology is chip segmentation. Majority of the literature within chip segmentation show cutting speed (vc) and feed rate (f) as the most influencing input parameters. The role of tool rake angle (α) on chip segmentation is limited and hence, the present study is aimed at understanding it. In addition, stress triaxiality’s importance in damage model employed in FE method in capturing the influence of α on chip morphology transformation is also studied. Furthermore, microstructure characterization of chips was carried out using a scanning electron microscope (SEM) to understand the chip formation process for certain cutting conditions. The results show that the tool α influences chip segmentation phenomena and that the incorporation of a stress triaxiality factor in damage models is required to be able to predict the influence of the α. The variation of chip segmentation frequency with f is predicted qualitatively but the accuracy of prediction needs improvement. © 2017 The Authors.

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