Parametric analysis of turning HSLA steel under minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL) : a concept of one-step sustainable machining

Javid, Hassan and Jahanzaib, Mirza and Jawad, Muhammad and Ali, Muhammad Asad and Farooq, Muhammad Umar and Pruncu, Catalin I. and Hussain, Salman (2021) Parametric analysis of turning HSLA steel under minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL) : a concept of one-step sustainable machining. International Journal of Advanced Manufacturing Technology, 117 (5-6). pp. 1915-1934. 167. ISSN 1433-3015 (https://doi.org/10.1007/s00170-021-07776-y)

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Abstract

Abstract: The requirement of cost-effective and ecological production systems is crucial in the competitive market. In this regard, the focus is shifted towards sustainable and cleaner machining processes. Besides the clean technologies, effective parametric control is required for machining materials (such as High Strength Low Alloy Steels) specifically designed for high strength applications having superior physio-chemical properties. Therefore, the machinability complexities require optimized solutions to reduce temperature elevation and tooling costs and improve machining of these materials. Complying to the market needs, this research examines the effectiveness of nanofluid on tool life, wear mechanisms, surface roughness (Ra), surface morphology, and material removal rate (MRR) in turning of 30CrMnSiA (HSLA) using minimum quantity lubrication (MQL) and SiO2-H2O nanofluids (NF-MQL). A systematic investigation based on physical phenomena involved is carried out considering four process parameters (cutting speed (VC), feed rate (Fr), depth of cut (DOC), and mode of lubrication for machining. Fr is found as the vital parameter for surface roughness while MRR is highly influenced by DOC regardless of lubrication approach. One-step sustainability technique is applied, in which process variables used for roughing conditions are analogous to attain surface comparable to finished machining without compromising process efficiency and demonstrate its feasibility through optimal settings under NF-MQL. Multi-response optimization proved the NF-MQL machining condition as the best alternative which result in 28.34% and 5.09% improvements for surface roughness and MRR, respectively. Moreover, the use of SiO2 is recommended over MQL due to lower energy consumption, low tool wear, and better surface integrity, sustainable liquid, and related costs.

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