Parameter Optimization of ASSAB XW 42 Tool Steel on End Milling Process with MQCL Using Taguchi-WPCA

Dian Ridlo Pamuji (1), M. Abdul Wahid (2), Abdul Rohman (3), Achmad As’ad Sonief (4), Moch. Agus Choiron (5)
(1) Mechanical Engineering Department, State Polytechnic of Banyuwangi, Jl. Raya Jember Km. 13 Kabat, Banyuwangi, Indonesia
(2) Mechanical Engineering Department, State Polytechnic of Banyuwangi, Jl. Raya Jember Km. 13 Kabat, Banyuwangi, Indonesia
(3) Mechanical Engineering Department, State Polytechnic of Banyuwangi, Jl. Raya Jember Km. 13 Kabat, Banyuwangi, Indonesia
(4) Mechanical Engineering Department, Brawijaya University, Jl. MT. Haryono, Malang, Indonesia
(5) Mechanical Engineering Department, Brawijaya University, Jl. MT. Haryono, Malang, Indonesia
Fulltext View | Download
How to cite (IJASEIT) :
Pamuji, Dian Ridlo, et al. “Parameter Optimization of ASSAB XW 42 Tool Steel on End Milling Process With MQCL Using Taguchi-WPCA”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 6, Dec. 2020, pp. 2402-9, doi:10.18517/ijaseit.10.6.7394.
Determination of a combination of process variables that are not appropriate in the end milling process will result in high surface roughness and can reduce the metal removal rate. Therefore, it is necessary to adjust the end milling process variables with the appropriate minimum quantity cooling lubrication. This study aims to obtain a combination of end milling process variables on ASSAB XW-42 material using the Taguchi-WPCA method to minimize arithmetic roughness (Ra), quadratic roughness average (Rq), and average roughness from peak to valley (Rz), and maximize metal removal rate (MRR) simultaneously. The cooling fluid method used is the minimum quantity of cooling lubrication (MQCL). The end milling process variable that is varied is the cutting fluid (soluble oil and vegetable oil), spindle speed (178 rpm, 310 rpm, and 570 rpm), feed rate (33.5 mm / minute, 59.4 mm / minute and 111.9 mm / minute) and the cutting depth (0.125 mm, 0.25 mm and 0.5 mm). The cutting tool used in this study is solid carbide end mill having four cutting edges with a diameter of 10 mm. The experimental design of the L18 orthogonal array was used in this study. The results showed that the optimal roughness of the workpiece surface and metal removal rate (MRR) was given by vegetable oil cutting fluid, 570 rpm of spindle speed, 33.5 mm / minute of feed rate, and 0.25 mm of the cutting depth. The Cutting fluid, spindle speed, and feed rate have a significant effect on the response variables observed simultaneously.

Jagadish and A. Ray, “Cutting Fluid Selection for Sustainable Design for Manufacturing: An Integrated Theory,” Procedia Mater. Sci., vol. 6, no. Icmpc, pp. 450-459, 2014.

E. Benedicto, D. Carou, and E. M. Rubio, “Technical, Economic and Environmental Review of the Lubrication / Cooling Systems used in Machining Processes,” Procedia Eng., vol. 184, pp. 99-116, 2017.

J. Dahlin and M. Isaksson, “Occupational contact dermatitis caused by N -butyl-1,2-benzisothiazolin-3-one in a cutting fluid,” Contact Dermatitis, vol. 73, no. 1, pp. 60-62, 2015.

N. T. Mathew and L. Vijayaraghavan, “Environmentally friendly drilling of intermetallic titanium aluminide at different aspect ratio,” J. Clean. Prod., 2016.

A. H. Abdelrazek, I. A. Choudhury, Y. Nukman, and S. N. Kazi, “Metal cutting lubricants and cutting tools: a review on the performance improvement and sustainability assessment,” pp. 4221-4245, 2020.

A. Shokrani, “A New Cutting Tool Design for Cryogenic Machining,” pp. 1-14, 2019.

K. K. Gajrani, D. Ram, and M. Ravi Sankar, “Biodegradation and hard machining performance comparison of eco-friendly cutting fluid and mineral oil using flood cooling and minimum quantity cutting fluid techniques,” J. Clean. Prod., vol. 165, pp. 1420-1435, 2017.

A. Naskar, B. B. Singh, A. Choudhary, and S. Paul, “Effect of different grinding fluids applied in minimum quantity cooling- lubrication mode on surface integrity in cBN grinding of Inconel 718,” vol. 36, no. September, pp. 44-50, 2018.

R. W. Maruda, G. M. Krolczyk, E. Feldshtein, P. Nieslony, B. Tyliszczak, and F. Pusavec, “Tool wear characterisations in finish turning of AISI 1045 carbon steel for MQCL conditions,” Wear, vol. 372-373, pp. 54-67, 2017.

S. Pervaiz, A. Rashid, I. Deiab, and C. M. Nicolescu, “An experimental investigation on effect of minimum quantity cooling lubrication (MQCL) in machining titanium alloy,” Int. J. Adv. Manuf. Technol., 2016.

S. H. Tomadi, J. A. Ghani, C. H. C. Haron, H. M. Ayu, and R. Daud, “Effect of Cutting Parameters on Surface Roughness in End Milling of AlSi/AlN Metal Matrix Composite,” Procedia Eng., vol. 184, pp. 58-69, 2017.

M. K. Das, K. Kumar, T. K. Barman, and P. Sahoo, “Optimisation of surface roughness and MRR in EDM using WPCA,” Procedia Eng., vol. 64, pp. 446-455, 2013.

A. Panda, A. K. Sahoo, and A. K. Rout, “Investigations on surface quality characteristics with multi-response parametric optimisation and correlations,” Alexandria Eng. J., vol. 55, no. 2, pp. 1625-1633, 2016.

B. Bijeta Nayak, K. Abhishek, S. Sankar Mahapatra, and D. Das, “Application of WPCA based taguchi method for multi-response optimisation of abrasive jet machining process,” Mater. Today Proc., vol. 5, no. 2, pp. 5138-5144, 2018.

A. R. Shinge and U. A. Dabade, “ScienceDirect ScienceDirect ScienceDirect The Effect of Process Parameters on Material Removal Rate and The Effect of Variation Process Parameters on Width Material Rate and Dimensional of Channel in Removal Micro-milling of Dimensional Variation of Channel Width in Micro-milling of Aluminium Alloy 6063 2017, Aluminium Alloy 6063 A. R. Shinge T6 Costing models for capacity,” Procedia Manuf., vol. 20, pp. 168-173, 2018.

B. R. Kumar, S. Saravanan, and K. Rajaram, “Combined effect of oxygenates and injection timing for low emissions and high performance in a diesel engine using multi-response optimisation,” Alexandria Eng. J., vol. 58, no. 2, pp. 625-636, 2019.

V. S. Jatti, “Multi-characteristics optimisation in EDM of NiTi alloy, NiCu alloy and BeCu alloy using Taguchi’s approach and utility concept,” Alexandria Eng. J., vol. 57, no. 4, pp. 2807-2817, 2018.

D. M. D. Costa, G. Belinato, T. G. Brito, A. P. Paiva, J. R. Ferreira, and P. P. Balestrassi, “Weighted principal component analysis combined with Taguchi’s signal ”‘ to ”‘ noise ratio to the multiobjective optimisation of dry end milling process : a comparative study,” J. Brazilian Soc. Mech. Sci. Eng., vol. 39, no. 5, pp. 1663-1681, 2017.

A. K. Sehgal and Meenu, “Grey relational analysis coupled with principal component analysis to optimise the machining process of ductile iron.,” Mater. Today Proc., vol. 5, no. 1, pp. 1518-1529, 2018.

M. Mia, M. Al Bashir, A. Khan, and N. R. Dhar, “Optimisation of MQL flow rate for minimum cutting force and surface roughness in end milling of hardened steel ( HRC 40 ),” pp. 675-690, 2017.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).