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Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel

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Abstract

In this study, the effect of four different machining methods consisting of “Trochoidal,” “Follow Part,” “Zig,” and “Zig-Zag” which are common in CAM package programs and used often in the industry has been investigated. Firstly, the 3D model of samples is produced in the CAD program. Models are machined in CNC milling workbench. In order to examine the effect of tool path strategies on tool life, the amount of wear loss as a criterion and the SEM images of tool wear as a supporting criterion are taken into account. According to the results, the “Zig-Zag” tool path strategy is the tool path that causes the highest weight loss in the cutting tool, while the “Trochoidal” tool path strategy causes in the least weight loss in the cutting tool. In addition, the surface roughness of the samples taken from different regions of the model and the operation time of the different tool paths are determined. In this context, the operation time of the test sample is maximum in “Zig” team path strategy, while it is at least in “Follow part” team path strategy. By examining the surface roughness, the best surface roughness values are obtained with the strategy of “Follow Part” and “Trochoidal” tool path, while the worst values are obtained in the “Zig” tool path strategy. As a result of the examination, the optimum tool path strategy for cutting tool life was found to be “Trochoidal” tool path. This work differs from the counterparts as handling the AISI X210Cr12 steel which make the paper first in determining the effect of tool path strategies on machinability. Lastly, obtained findings are useful for the organization of this type of steel in manufacturing chain of industrial companies.

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References

  1. Singh G, Gupta MK, Mia M, Sharma VS (2018) Modeling and optimization of tool wear in MQL-assisted milling of Inconel 718 superalloy using evolutionary techniques. Int J Adv Manuf Technol 97(1):481–494

    Article  Google Scholar 

  2. Gupta MK, Mia M, Pruncu CI, Kapłonek W, Nadolny K, Patra K, Mikolajczyk T, Pimenov DY, Sarikaya M, Sharma VS (2019) Parametric optimization and process capability analysis for machining of nickel-based superalloy. Int J Adv Manuf Technol 102(9):3995–4009

    Article  Google Scholar 

  3. Gupta MK, Mia M, Singh G, Pimenov DY, Sarikaya M, Sharma VS (2019) Hybrid cooling-lubrication strategies to improve surface topography and tool wear in sustainable turning of Al 7075–T6 alloy. Int J Adv Manuf Technol 101(1):55–69

    Article  Google Scholar 

  4. Salur E, Acarer M, Şavkliyildiz İ (2021) Improving mechanical properties of nano-sized TiC particle reinforced AA7075 Al alloy composites produced by ball milling and hot pressing. Mater Today Commun: 102202

  5. Pillai JU, Sanghrajka I, Shunmugavel M, Muthuramalingam T, Goldberg M, Littlefair G (2018) Optimisation of multiple response characteristics on end milling of aluminium alloy using Taguchi-Grey relational approach. Measurement 124:291–298

    Article  Google Scholar 

  6. Edem IF, Balogun VA, Mativenga PT (2017) An investigation on the impact of toolpath strategies and machine tool axes configurations on electrical energy demand in mechanical machining. Int J Adv Manuf Technol 92(5):2503–2509

    Article  Google Scholar 

  7. Thepsonthi T, Özel T (2014) An integrated toolpath and process parameter optimization for high-performance micro-milling process of Ti–6Al–4V titanium alloy. Int J Adv Manuf Technol 75(1–4):57–75

    Article  Google Scholar 

  8. Kuntoğlu M, Sağlam H (2019) Investigation of progressive tool wear for determining of optimized machining parameters in turning. Measurement 140:427–436

    Article  Google Scholar 

  9. Sukvittayawong S, Inasaki I (1991) Optimization of turning process by cutting force measurement. Jsme Int J Iii-Vib C 34(4):546–552. https://doi.org/10.1299/jsmec1988.34.546

    Article  Google Scholar 

  10. Toh CK (2006) Cutter path strategies in high speed rough milling of hardened steel. Mater Design 27(2):107–114. https://doi.org/10.1016/j.matdes.2004.09.021

    Article  Google Scholar 

  11. Toh CK (2005) Design, evaluation and optimisation of cutter path strategies when high speed machining hardened mould and die materials. Mater Design 26(6):517–533. https://doi.org/10.1016/j.matdes.2004.07.019

    Article  Google Scholar 

  12. Kaymakci M, Lazoglu I (2008) Tool path selection strategies for complex sculptured surface machining. Mach Sci Technol 12(1):119–132. https://doi.org/10.1080/10910340801913979

    Article  Google Scholar 

  13. Finzer T (1999) High speed machining (HSC) of sculptured surfaces in die and mold manufacturing. In: Olling GJ, Choi BK, Jerard RB (eds) Machining impossible shapes: IFIP TC5 WG5.3 International Conference on Sculptured Surface Machining (SSM98) November 9–11, 1998 Chrysler Technology Center, Michigan, USA. Springer US, Boston, MA, pp 333–341. https://doi.org/10.1007/978-0-387-35392-0_34

  14. Schulz H, Geist J (1999) HSC-appropriate NC programming in die and mould manufacturing. Int Fed Info Proc 18:325–332

    Google Scholar 

  15. Rangarajan A, Dornfeld D (2004) Efficient tool paths and part orientation for face milling. Cirp Ann-Manuf Techn 53(1):73–76

    Article  Google Scholar 

  16. Zerti O, Yallese MA, Belhadi S, Bouzid L (2017) Taguchi design of experiments for optimization and modeling of surface roughness when dry turning X210Cr12 steel. In: Applied Mechanics, Behavior of Materials, and Engineering Systems. Springer, pp 275–288

  17. Sakarya N, Gologlu C (2006) Determination of cutter path strategies and the effects of cutter path strategies on surface roughness in pocket milling by Taguchi method. J Fac Eng Arch Gazi Univ 21(4):603–611

    Google Scholar 

  18. Choi BK, Jerard RB (1998) Sculptured surface machining: theory and applications. Kluwer Academic Publishers

    Book  Google Scholar 

  19. Park SC (2004) Sculptured surface machining using triangular mesh slicing. Comput Aided Design 36(3):279–288. https://doi.org/10.1016/S0010-4485(03)00114-3

    Article  Google Scholar 

  20. Kim BH, Choi BK (2002) Machining efficiency comparison direction-parallel tool path with contour-parallel tool path. Comput Aided Design 34(2):89–95

    Article  Google Scholar 

  21. Kardes N, Altintas Y (2004) Prediction of cutting forces in circular milling. In: Third International Conference and Exhibition on Design and Production of Dies and Molds, pp 1–5

  22. Marinac D (2000) Tool path strategies for high speed machining. MMS Online 72:104–110

    Google Scholar 

  23. Rauch M, Duc E, Hascoet JY (2009) Improving trochoidal tool paths generation and implementation using process constraints modelling. Int J Mach Tool Manu 49(5):375–383. https://doi.org/10.1016/j.ijmachtools.2008.12.006

    Article  Google Scholar 

  24. Coleman G (2006) A closer look at toolpath strategies. MMS Online

  25. Otkur M, Lazoglu I (2007) Trochoidal milling. Int J Mach Tool Manu 47(9):1324–1332. https://doi.org/10.1016/j.ijmachtools.2006.08.002

    Article  Google Scholar 

  26. Altinkaya E, Gullu A (2008) The effect of the form of chip breaker on tool wear and surfaces roughness during machining of AISI 316 austenitic stainless steel. J Polytech 11(1):13–17. https://doi.org/10.2339/2008.11.1.13-1

    Article  Google Scholar 

  27. Mamalis AG, Grabchenko AI, Fedorovich VA, Kundrak J (2009) Methodology of 3D simulation of processes in technology of diamond-composite materials. Int J Adv Manuf Tech 43(11–12):1235–1250

    Article  Google Scholar 

  28. Toh CK (2004) A study of the effects of cutter path strategies and orientations in milling. J Mater Process Tech 152(3):346–356. https://doi.org/10.1016/j.jmatprotec.2004.04.382

    Article  Google Scholar 

  29. InovaTools (2017) Solid carbide tools. German Tools Groups

  30. Ali RA, Mia M, Khan AM, Chen W, Gupta MK, Pruncu CI (2019) Multi-response optimization of face milling performance considering tool path strategies in machining of Al-2024. Materials 12(7):1013

    Article  Google Scholar 

  31. Koklu U, Basmaci G (2017) Evaluation of tool path strategy and cooling condition effects on the cutting force and surface quality in micromilling operations. Metals 7(10):426

    Article  Google Scholar 

  32. Edem IF, Mativenga PT (2017) Energy demand reduction in milling based on component and toolpath orientations. Procedia Manuf 7:253–261

    Article  Google Scholar 

  33. De Souza AF, Berkenbrock E, Diniz AE, Rodrigues AR (2015) Influences of the tool path strategy on the machining force when milling free form geometries with a ball-end cutting tool. J Braz Soc Mech Sci Eng 37(2):675–687

    Article  Google Scholar 

  34. Mert F, Uluer O, Guldas A, Ozdemir A (2008) The effects of computer aided tool path generation methods on the machining times and surface. J Polytech 11(3):215–227. https://doi.org/10.2339/2008.11.3.215-227

    Article  Google Scholar 

  35. Monreal M, Rodriguez CA (2003) Influence of tool path strategy on the cycle time of high-speed milling. Comput Aided Design 35(4):395–401

    Article  Google Scholar 

  36. Kuntoğlu M, Aslan A, Pimenov DY, Giasin K, Mikolajczyk T, Sharma S (2020) Modeling of cutting parameters and tool geometry for multi-criteria optimization of surface roughness and vibration via response surface methodology in turning of AISI 5140 steel. Materials 13(19):4242

    Article  Google Scholar 

  37. Haq S, Srivastava R (2016) Measuring the influence of materials composition on nano scale roughness for wood plastic composites by AFM. Measurement 91:541–547

    Article  Google Scholar 

  38. Gao Q, Gong Y, Zhou Y, Wen X (2017) Experimental study of micro-milling mechanism and surface quality of a nickel-based single crystal superalloy. J Mech Sci Technol 31(1):171–180

    Article  Google Scholar 

  39. Wang C, Xie Y, Zheng L, Qin Z, Tang D, Song Y (2014) Research on the chip formation mechanism during the high-speed milling of hardened steel. Int J Mach Tools Manuf 79:31–48

    Article  Google Scholar 

  40. de Souza AF, Machado A, Beckert SF, Diniz AE (2014) Evaluating the roughness according to the tool path strategy when milling free form surfaces for mold application. Procedia CIRP 14:188–193

    Article  Google Scholar 

  41. Aslan A (2020) Optimization and analysis of process parameters for flank wear, cutting forces and vibration in turning of AISI 5140: a comprehensive study. Measurement 107959

  42. Shankar S, Mohanraj T, Rajasekar R (2019) Prediction of cutting tool wear during milling process using artificial intelligence techniques. Int J Comput Integr Manuf 32(2):174–182

    Article  Google Scholar 

  43. García-Nieto PJ, García-Gonzalo E, Vilán JV, Robleda AS (2016) A new predictive model based on the PSO-optimized support vector machine approach for predicting the milling tool wear from milling runs experimental data. Int J Adv Manuf Technol 86(1):769–780

    Article  Google Scholar 

  44. Nouri M, Fussell BK, Ziniti BL, Linder E (2015) Real-time tool wear monitoring in milling using a cutting condition independent method. Int J Mach Tools Manuf 89:1–13

    Article  Google Scholar 

  45. Zhu Z, Guo X, Ekevad M, Cao P, Na B, Zhu N (2017) The effects of cutting parameters and tool geometry on cutting forces and tool wear in milling high-density fiberboard with ceramic cutting tools. Int J Adv Manuf Technol 91(9):4033–4041

    Article  Google Scholar 

  46. Lizzul L, Sorgato M, Bertolini R, Ghiotti A, Bruschi S (2020) Influence of additive manufacturing-induced anisotropy on tool wear in end milling of Ti6Al4V. Tribol Int 146:106200

    Article  Google Scholar 

  47. Manimaran G, Anwar S, Rahman MA, Korkmaz ME, Gupta MK, Alfaify A, Mia M (2020) Investigation of surface modification and tool wear on milling Nimonic 80A under hybrid lubrication. Tribol Int 106762

  48. de Souza AF, Machado A, Beckert SF, Diniz AE (2014) Evaluating the roughness according to the tool path strategy when milling free form surfaces for mold application. Proc Cirp 14:188–193. https://doi.org/10.1016/j.procir.2014.03.089

    Article  Google Scholar 

  49. Ramos AM, Relvas C, Simoes JA (2003) The influence of finishing milling strategies on texture, roughness and dimensional deviations on the machining of complex surfaces. J Mater Process Tech 136(1–3):209–216. https://doi.org/10.1016/S0924-0136(03)00160-2

    Article  Google Scholar 

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Funding

This study was financially supported by Development Ministry, coordinated by Council of Higher Education and organized by The Scientific Research Projects Coordination Unit of Bingöl University (Project Number: BAP-MMF.2016.00.004).

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Authors and Affiliations

  1. Department of Mechanical Engineering, Faculty of Engineering, Inonu University, Malatya, Turkey

    Mahir Uzun

  2. Department of Mechanical Engineering, Faculty of Engineering and Architecture, Bingöl University, Bingol, Turkey

    Üsame Ali Usca

  3. Technology Faculty, Mechanical Engineering Department, Selcuk University, Konya, 42130, Turkey

    Mustafa Kuntoğlu

  4. Faculty of Mechanical Engineering, Opole University of Technology, 76 Proszkowska St., Opole, 45-758, Poland

    Munish Kumar Gupta

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  1. Mahir Uzun
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  2. Üsame Ali Usca
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All the authors contribute equally.

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Correspondence to Munish Kumar Gupta.

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Uzun, M., Usca, Ü.A., Kuntoğlu, M. et al. Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel. Int J Adv Manuf Technol 119, 2709–2720 (2022). https://doi.org/10.1007/s00170-021-08365-9

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