Developing a Sustainability Assessment Model for Coolant Impacts on Surface Quality in Ball End Milling
DOI:
https://doi.org/10.15282/mekatronika.v7i1.11840Keywords:
Sustainable machining, Coolant performance, Surface roughness, Regression analysisAbstract
Cutting fluids play a critical role in machining operations, yet excessive or inefficient use poses environmental challenges and affects workers' health, highlighting the need for optimised and sustainable practices. This study addresses the challenge of balancing machining performance and sustainability by experimentally investigating ball end milling of AISI 1040 steel using uncoated HSS tools under dry, mist, 4% coolant, and 8% coolant conditions with constant cutting parameters. Machining performance was evaluated based on surface roughness, with mist coolant in down milling achieving the best results (average roughness of 0.462 μm), followed by mist coolant in up milling, 8% coolant, and 4% coolant in up milling. The research highlights the significant impact of coolant conditions on machining performance and surface quality while integrating sustainability principles. A regression-based model was developed to predict interactions between sustainability parameters and machining attributes, offering insights to optimise processes with environmental and societal considerations, thereby supporting sustainable manufacturing practices.
References
[1] Altintas, Y. (2012). Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design (2nd ed.). Cambridge University Press.
[2] Davim, J. P. (2021). Modern Manufacturing Engineering (1st ed.). Springer. https://doi.org/10.1007/978-3-642-45176-8
[3] Gajrani, K.K., & Sankar, M.R. (2020). Role of Eco-friendly Cutting Fluids and Cooling Techniques in Machining. In K. Gupta (Ed.), Materials Forming, Machining and Post Processing, 159–181. Springer. https://doi.org/10.1007/978-3-030-18854-2_7
[4] Hiran Gabriel, D.J., Parthiban, M., Kantharaj, I., & Beemkumar, N. (2023). A review on sustainable alternatives for conventional cutting fluid applications for improved machinability. Machining Science and Technology, 27(2), 157–207. https://doi.org/10.1080/10910344.2023.2194966
[5] Pusavec, F., Krajnik, P., & Kopac, J. (2010). Transitioning to sustainable production – Part I: application on machining technologies. Journal of Cleaner Production, 18(2), 174–184. https://doi.org/10.1016/j.jclepro.2009.08.010
[6] Gajrani, K.K., Prasad, A., Kumar, A. (2022) Advances in Sustainable Machining and Manufacturing Processes (1st ed.). Taylor & Francis. https://doi.org/10.1201/9781003284574
[7] Kumar, P., Jain, A.K., Chaurasiya, P.K., Rushman, J.F et al. (2022) Sustainable Machining Using Eco-Friendly Cutting Fluids: A Review. Advances in Materials Science and Engineering, 2022(2), 1–16. https://doi.org/ 10.1155/2022/5284471
[8] Gupta, M.K., Jamil, M., Wang, X., Song, O., Liu, Z., Mia, M., Hegab, H., Khan, A.M., Collado, A.G., Pruncu, C.I., Imran, G.M.S. (2019) Performance Evaluation of Vegetable Oil-Based Nano-Cutting Fluids in Environmentally Friendly Machining of Inconel-800 Alloy. Materials, 12(17), 2792. https://doi.org/ 10.3390/ma12172792
[9]Gaurav, G., Sharma, A., Dangayach, G.S., Meena, M.L. (2021). A Review of Minimum Quantity Lubrication (MQL) Based on Bibliometry. Current Materials Science, 14(1),13–39. https://doi.org/10.2174/2666145413999201222104811
[10] Wang L, Cai W, He Y, et al (2023) Equipment-process-strategy integration for sustainable machining: a review. Frontiers of Mechanical Engineering 18:36. https://doi.org/10.1007/s11465-023-0752-4
[11] Fernando R, Gamage J, Karunathilake H (2022) Sustainable machining: environmental performance analysis of turning. International Journal of Sustainable Engineering 15, 15–34. https://doi.org/10.1080/19397038.2021.1995524
[12] R. Bertolini, S. Bruschi, A. Ghiotti, E. Savio, L. Ceseracciu, I.S. Jawahir. (2023) Surface integrity and superelastic response of additively manufactured Nitinol after heat treatment and finish machining. CIRP Annals 72(1), 501–504. . https://doi.org/10.1016/j.cirp.2023.04.025
[13] Soori M, Arezoo B (2024) The effects of coolant on the cutting temperature, surface roughness and tool wear in turning operations of Ti6Al4V alloy. Mechanics Based Design of Structures and Machines 52:3277–3299. https://doi.org/10.1080/15397734.2023.2200832
[14] Rajmohan T, Kalyan Chakravarthy VV, Nandakumar A, Satish Kumar SD (2020) Eco Friendly Machining Processes for Sustainability - Review. IOP Conf Ser Mater Sci Eng 954:012044. https://doi.org/10.1088/1757-899X/954/1/012044
[15] Selamat SN, Nor NHM, Rashid MHA, et al (2017) Review of CO2 Reduction Technologies using Mineral Carbonation of Iron and Steel Making Slag in Malaysia. J Phys Conf Ser 914:012012. https://doi.org/10.1088/1742-6596/914/1/012012
[16] Halim NHA, Haron CHC, Ghani JA, Azhar MF (2019) Tool wear and chip morphology in high-speed milling of hardened Inconel 718 under dry and cryogenic CO2 conditions. Wear 426–427:1683–1690. https://doi.org/10.1016/j.wear.2019.01.095
[17] Pereira O, Celaya A, Urbikaín G, et al (2020) CO2 cryogenic milling of Inconel 718: cutting forces and tool wear. Journal of Materials Research and Technology 9:8459–8468. https://doi.org/10.1016/j.jmrt.2020.05.118
[18] Dhar NR, Kamruzzaman M, Ahmed M (2006) Effect of minimum quantity lubrication (MQL) on tool wear and surface roughness in turning AISI-4340 steel. J Mater Process Technol 172:299–304. https://doi.org/10.1016/j.jmatprotec.2005.09.022
[19] Gupta MK, Niesłony P, Sarikaya M, et al (2023) Studies on Geometrical Features of Tool Wear and Other Important Machining Characteristics in Sustainable Turning of Aluminium Alloys. International Journal of Precision Engineering and Manufacturing-Green Technology 10:943–957. https://doi.org/10.1007/s40684-023-00501-y
[20] Wang X, Li C, Zhang Y, et al (2020) Vegetable oil-based nanofluid minimum quantity lubrication turning: Academic review and perspectives. J Manuf Process 59:76–97. https://doi.org/10.1016/j.jmapro.2020.09.044
[21] Turan FM, Johan K (2016) Assessing sustainability framework of automotive related industry in the Malaysia context based on GPM P5 standard. ARPN Journal of Engineering and Applied Sciences 11:7606–7611
[22] Sahimi NS, Turan FM, Johan K (2017) Development of Sustainability Assessment Framework in Hydropower sector. IOP Conf Ser Mater Sci Eng 226:012048. https://doi.org/10.1088/1757-899X/226/1/012048
[23] Turan FM, Johan K, Nor NHM (2016) Criteria Assessment Model for Sustainable Product Development. In: IOP Conference Series: Materials Science and Engineering 160:0124. https://doi.org/10.1088/1757-899X/160/1/012004
[24] Wan Lanang WNS, Turan FM, Johan K (2017) Systematic Assessment Through Mathematical Model for Sustainability Reporting in Malaysia Context. In: IOP Conference Series: Materials Science and Engineering 226:012049. https://doi.org/10.1088/1757-899X/226/1/012049
[25] Turan FM, Johan K, Lanang WNSW, Nor NHM (2016) Development of Systematic Sustainability Assessment (SSA) for the Malaysian Industry. In: IOP Conference Series: Materials Science and Engineering 160:012047. https://doi.org/10.1088/1757-899X/160/1/012047
[26] Sahimi NS, Turan FM, Johan K (2018) Framework of Sustainability Assessment (FSA) method for manufacturing industry in Malaysia. In: IOP Conference Series: Materials Science and Engineering 342:012079. https://doi.org/10.1088/1757-899X/342/1/012079
[27] Salonitis K, Stavropoulos P (2013) On the Integration of the CAx Systems Towards Sustainable Production. Procedia CIRP 9:115–120. https://doi.org/10.1016/j.procir.2013.06.178
[28] Bunse K, Vodicka M, Schönsleben P, et al (2011) Integrating energy efficiency performance in production management – gap analysis between industrial needs and scientific literature. J Clean Prod 19:667–679. https://doi.org/10.1016/j.jclepro.2010.11.011
[29] Davé A, Salonitis K, Ball P, et al (2016) Factory Eco-Efficiency Modelling: Framework Application and Analysis. Procedia CIRP 40:214–219. https://doi.org/10.1016/j.procir.2016.01.105
[30] Davé A, Ball P, Salonitis K (2017) Factory Eco-Efficiency Modelling: Data Granularity and Performance Indicators. Procedia Manuf 8:479–486. https://doi.org/10.1016/j.promfg.2017.02.061
[31] Saxena P, Stavropoulos P, Kechagias J, Salonitis K (2020) Sustainability Assessment for Manufacturing Operations. Energies (Basel) 13:2730. https://doi.org/10.3390/en13112730
[32] John A. Schey (2000) Introduction to Manufacturing Processes, 3rd ed. McGraw-Hill
[33] Steve F. Krar, Arthur R. Gill, Peter Smid, et al (2024) Technology Of Machine Tools, 9th ed. McGraw Hill
[34] Aikhuele DO, Turan FM, Odofin SM, Ansah RH (2017) Interval-valued Intuitionistic Fuzzy TOPSIS-based model for troubleshooting marine diesel engine auxiliary system. Transactions of the Royal Institution of Naval Architects Part A: International Journal of Maritime Engineering 159:. https://doi.org/10.3940/rina.ijme.2016.al.402
[35] Aikhuele DO, Turan FM (2017) An intuitionistic fuzzy multi-criteria decision-making method based on an exponential-related function International Journal of Fuzzy System Applications 6: 33–46. https://doi.org/ 10.4018/IJFSA.2017100103
[36] Aikhuele DO, Turan FM (2016) A Hybrid Fuzzy Model for Lean Product Development Performance Measurement. In: IOP Conference Series: Materials Science and Engineering 114: 012048. https://doi.org/10.1088/1757-899X/114/1/012048
[37] Aikhuele DO, Turan FM (2018) A modified exponential score function for troubleshooting an improved locally made Offshore Patrol Boat engine. Journal of Marine Engineering and Technology 17:. https://doi.org/10.1080/20464177.2017.1286841
[38] Aikhuele DO, Turan FM (2016) Proposal for a Conceptual Model for Evaluating Lean Product Development Performance: A Study of LPD Enablers in Manufacturing Companies. In: IOP Conference Series: Materials Science and Engineering 114:012047. https://doi.org/10.1088/1757-899X/114/1/012047
Downloads
Published
Issue
Section
License
Copyright (c) 2025 The Author(s)

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