Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

doi:10.1007/s40436-018-0231-z

Advances in Manufacturing ›› 2018, Vol. 6 ›› Issue (4): 419-429.doi: 10.1007/s40436-018-0231-z

Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

Ali Kalyon¹, Mustafa Günay², Dursun Özyürek¹

1 Department of Manufacturing Engineering, Karabük University, 078050 Karabük, Turkey;
2 Department of Mechanical Engineering, Karabük University, 078050 Karabük, Turkey

收稿日期:2018-02-17 修回日期:2018-07-09 出版日期:2018-12-25 发布日期:2018-12-08
通讯作者: Mustafa Günay,mgunay@karabuk.edu.tr E-mail:mgunay@karabuk.edu.tr
基金资助:
The authors would like to acknowledge the financial support provided by Karabük University Scientific Research Project Unit (Grant No. KBÜ-BAP-13/1-DR-007) for the successful implementation of this study.

Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

Ali Kalyon¹, Mustafa Günay², Dursun Özyürek¹

1 Department of Manufacturing Engineering, Karabük University, 078050 Karabük, Turkey;
2 Department of Mechanical Engineering, Karabük University, 078050 Karabük, Turkey

Received:2018-02-17 Revised:2018-07-09 Online:2018-12-25 Published:2018-12-08
Contact: Mustafa Günay,mgunay@karabuk.edu.tr E-mail:mgunay@karabuk.edu.tr
Supported by:
The authors acknowledge the support of Turkish National Science Foundation (Grant No. 108M340).

摘要/Abstract

摘要： High chrome white cast iron is particularly preferred in the production of machine parts requiring high wear resistance. Although the amount of chrome in these materials provides high wear and corrosion resistances, it makes their machinability difficult. This study presents an application of the grey relational analysis based on the Taguchi method in order to optimize chrome ratio, cutting speed, feed rate, and cutting depth for the resultant cutting force (F_R) and surface roughness (R_a) when hard turning high chrome cast iron with a cubic boron nitride (CBN) insert. The effect levels of machining parameters on F_R and R_a were examined by an analysis of variance (ANOVA). A grey relational grade (GRG) was calculated to simultaneously minimize F_R and R_a. The ANOVA results based on GRG indicated that the feed rate, followed by the cutting depth, was the main parameter and contributed to responses. Optimal levels of parameters were found when the chrome ratio, cutting speed, feed rate, and cutting depth were 12%, 100 m/min, 0.05 mm/r, and 0.1 mm, respectively, based on the multiresponse optimization results obtained by considering the maximum signal to noise (S/N) ratio of GRG. Confirmation results were verified by calculating the confidence level within the interval width.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-018-0231-z

关键词: High chrome cast iron, Hard turning, Grey relational analysis, Multi-response optimization, Taguchi method

Abstract: High chrome white cast iron is particularly preferred in the production of machine parts requiring high wear resistance. Although the amount of chrome in these materials provides high wear and corrosion resistances, it makes their machinability difficult. This study presents an application of the grey relational analysis based on the Taguchi method in order to optimize chrome ratio, cutting speed, feed rate, and cutting depth for the resultant cutting force (F_R) and surface roughness (R_a) when hard turning high chrome cast iron with a cubic boron nitride (CBN) insert. The effect levels of machining parameters on F_R and R_a were examined by an analysis of variance (ANOVA). A grey relational grade (GRG) was calculated to simultaneously minimize F_R and R_a. The ANOVA results based on GRG indicated that the feed rate, followed by the cutting depth, was the main parameter and contributed to responses. Optimal levels of parameters were found when the chrome ratio, cutting speed, feed rate, and cutting depth were 12%, 100 m/min, 0.05 mm/r, and 0.1 mm, respectively, based on the multiresponse optimization results obtained by considering the maximum signal to noise (S/N) ratio of GRG. Confirmation results were verified by calculating the confidence level within the interval width.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-018-0231-z

Key words: High chrome cast iron, Hard turning, Grey relational analysis, Multi-response optimization, Taguchi method

Ali Kalyon, Mustafa Günay, Dursun Özyürek. Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron[J]. Advances in Manufacturing, 2018, 6(4): 419-429.

参考文献

1. Chung RJ, Tang X, Hinckley DYLB et al (2013) Microstructure refinement of hypereutetic high Cr cast iron using hard carbideforming elements for improved wear resistance. Wear 301:695-706
2. Çetinkaya C (2006) An investigation of the wear behaviour of white cast irons under different compositions. Mater Des 27:437-445
3. El-Aziz KA, Zohdy K, Saber D et al (2015) Wear and corrosion behavior of high-Cr white cast iron alloys in different corrosive media. J Bio Tribo Corros 1:25
4. Sallam HEM, El-Aziz KA, El-Raouf HA et al (2013) Failure analysis and flexural behavior of high chromium white cast iron and AISI4140 Steel bimetal beams. Mater Des 52:974-980
5. Günay M, Korkmaz ME, Yaşar N (2017) Finite element modeling of tool stresses on ceramic tools in hard turning. Mechanika 23(3):432-440
6. Zhou JM, Andersson M, Stahl JE (2004) Identification of cutting error in precision hard turning process. J Mater Process Technol 153:746-750
7. Klocke F, Brinksmeier E, Weinert K (2005) Capabilty profile of hard cutting and grinding process. CIRP Ann Manuf Technol 54:22-45
8. Smith S, Melkote SN, Curzio EL et al (2007) Effect of surface integrity of hard turned AISI 52100 steel on fatigue performance. Mater Sci Eng A 459:337-346
9. Fallbohmer P, Rodriguez CA, Ozel T et al (2000) High-speed machining of cast iron and alloy steel for die and mould manufacturing. J Mater Process Technol 98:104-115
10. Aslan E, Camuscu N, Birgören B (2007) Design optimisation of cutting parameter when turning hardened AISI 4140 steel (63 HRC) with Al₂O₃+TiCN mixed ceramic tool. Mater Des 28:1618-1622
11. Huang Y, Chou YK, Liang SY (2007) CBN tool wear in hard turning:a survey on research progresses. Int J Adv Manuf Technol 35:443-453
12. Sing D, Rao PV (2006) A surface roughness prediction model for hard turning process. Int J Adv Manuf Technol 32:1115-1124
13. Çoğun C, Özses B (2002) Bilgisayar sayisal denetimli takim tazgahlarinda değişik işleme koşullarinin yüzey pürüzlülüğüne etkisi. J Fac Eng Arch Gazi Univ 17(1):59-75
14. Korkmaz ME, Günay M (2018) Finite element modelling of cutting forces and power consumption in turning of AISI 420 martensitic stainless steel. Arab J Sci Eng. https://doi.org/10.1007/s13369-018-3204-4
15. Bartarya G, Choudhury SK (2012) Effect of cutting parametes on cutting force and surface roughness during finish hard turning AISI52100 grade steel. Procedia CIRP 1:651-656
16. Rao CJ, Rao DN, Srihari P (2013) Influence of cutting parameters on cutting force and surface finish in turning operation. Procedia Eng 64:1405-1415
17. Rafai NH, Islam MN (2009) An investigation in to dimensional accuracy and surface finish achieveble in dry turning. Mach Sci Technol 13:571-589
18. Bouacha K, Yallese MA, Mabrouki T et al (2010) Statistical analysis of surface roughness and cutting force using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool. Int J Refract Met Hard Mater 28:349-361
19. Chavoshi SZ, Tajdari M (2010) Surface roughness modelling in hard turning operation of AISI 4140 using CBN cutting tool. Int J Mater Form 3:233-239
20. Masood SH, Armitage K, Brandt M (2011) An experimental study of laser-assisted machining of hard-to-wear white cast iron. Int J Mach Tool Manuf 51:450-456
21. Ravi AM, Murigendrappa SM, Mukunda PG (2014) Machinability investigation on high chrome white cast iron using multicoated hard carbide tools. Trans Indian Inst Met 67(4):485-502
22. Jiang W, More AS, Brown WD et al (2006) A CBN-TiN composite coating for carbide insert:coating characterisation and its application for finish hard turning. Surf Coat Technol 201:2443-2449
23. Manivel D, Gandhinathan R (2016) Optimization of surface roughness and tool wear in hard turning of austempered ductile iron using Taguchi method. Meas 93:108-116
24. Kır D, Öktem H, Çöl M et al (2016) Determination of the cutting tool performance of high-alloyed white cast iron (Ni-Hard 4) using the Taguchi method. Mater Technol 50(2):239-246
25. KYOCERA Precision Tools, Inc. http://www.kyocer aprecisiontools.com/indexable/pdf/Turning_Catalog_2017.pdf. Accessed 16 Jan 2017
26. Taguchi G, Chowdhury S, Wu Y (2004) Taguchi's quality engineering handbook. Wiley, Hoboken
27. Sarıkaya M, Güllü A (2015) Multiresponse optimization of minimum quantity lubrication parameter using Taguchi-based grey relational analysis in turning of difficult-to-cut alloy Haynes 25. J Clean Prod 91:347-357
28. Deng JL (1989) Introduction to grey system theory. J Grey Syst 1:1-24
29. Sahoo AK, Sahoo B (2013) Performance studies of multilayer hard surface coating (TiN/TiCN/Al₂O₃/TiN) of indexeble carbide insert in hard machining:part-Ⅱ (RSM, grey relational and techno economical approach). Measurement 46:2868-2884
30. Kalyon A, Özyürek D, Günay M et al (2015) Dry sliding wear behaviour of valve seat insert produced from high chromium white iron. High Temp Mater Process 34:635-641
31. Grzesik W, Rech J, Wanat T (2007) Surface finish on hardened bearing steel part produced by superhard and abrasive tools. Int J Mach Tools Manuf 47:255-262
32. Savaş V, Ozay C, Ballikaya H (2016) Experimental investigation of cutting parameter in machining of 100Cr6 with tangential turnmilling method. Adv Manuf 4:97-104

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Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

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