Nanofluids, micro-lubrications and machining process optimisations − a review

Chakule, Rahul; Chaudhari, Sharad S.; Chandratre, Kailas V.; Patole, P.B.; Talmale, Poonam

doi:10.1051/mfreview/2022034

Cited by 7 publications

(2 citation statements)

References 88 publications

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“…To improve thermal and heat transmission, a nanofluid is used as a cutting fluid in machining. For enhancing efficiency, micro-lubrication methods and method modification play similar roles [15]. During machining, manufacturing heat is an essential occurrence.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Significance of Temperature-Dependent Density on Dissipative and Reactive Flows of Nanofluid along Magnetically Driven Sheet and Applications in Machining and Lubrications

Ullah,

Hussain,

Aldhabani

et al. 2023

Lubricants

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Nanofluid lubrication and machining are challenging and significant tasks in manufacturing industries that are used to control the removal of a material from a surface by using a cutting tool. The introduction of a nanofluid to the cutting zone provides cooling, lubricating, and chip-cleaning benefits that improve machining productivity. A nanofluid is a cutting fluid that is able to remove excessive friction and heat generation. Chemical reactions and temperature-dependent density are essential in the thermal behavior of a nanofluid. The present study presents a careful inspection of the chemical reactions, temperature-dependent density, viscous dissipation, and thermophoresis during the heat and mass transfer of a nanofluid along a magnetically driven sheet. The physical attitude of viscous dissipation and the chemical reaction improvement rate in magneto-nanofluid flow is the primary focus of the present research. By applying the proper transformation, nonlinear partial differential expressions are introduced to the structure of the ordinary differential framework. The flow equations are simplified into nonlinear differential equations, and these equations are then computationally resolved via an efficient computational technique known as the Keller box technique. Flow factors like the Eckert number, reaction rate, density parameter, magnetic force parameter, thermophoretic number, buoyancy number, and Prandtl parameter governing the velocity, temperature distribution, and concentration distribution are evaluated prominently via tables and graphs. The novelty of the current study is in computing a heat transfer assessment of the magneto-nanofluid flow with chemical reactions and temperature-dependent density to remove excessive friction and heating in cutting zones. Nanofluids play significant roles in minimum quantity lubrication (MQL), enhanced oil recovery (EOR), drilling, brake oil, engine oil, water-miscible cutting fluids, cryogenic cutting fluids, controlled friction between tools and chips and tools and work, and conventional flood cooling during machining processes.

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Section: Introduction and Literature Reviewmentioning

confidence: 99%

Significance of Temperature-Dependent Density on Dissipative and Reactive Flows of Nanofluid along Magnetically Driven Sheet and Applications in Machining and Lubrications

Ullah,

Hussain,

Aldhabani

et al. 2023

Lubricants

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“…-The position of the elite solutions used in the revision method helps maintain the diversity of solutions, and demonstrate strength and high convergence. While, some optimization algorithms omitted this methodology, or this the problem about other remaining algorithms like PSO and GA [7][8][9] results in a pre-mature convergence of algorithm and plighting in local optima.…”

Section: Introductionmentioning

confidence: 99%

Development of OCMNO algorithm applied to optimize surface quality when ultra-precise machining of SKD 61 coated Ni-P materials

2023

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In this paper, a new algorithm developing to solve optimization problems with many nonlinear factors in ultra-precision machining by magnetic liquid mixture. The presented algorithm is a collective global search inspired by artificial intelligence based on the coordination of nonlinear systems occurring in machining processes. Combining multiple nonlinear systems is established to coordinate various nonlinear objects based on simple physical techniques during machining. The ultimate aim is to create a robust optimization algorithm based on the optimization collaborative of multiple nonlinear systems (OCMNO) with the same flexibility and high convergence established in optimizing surface quality and material removal rate (MRR) when polishing the SKD61-coated Ni-P material. The benchmark functions analyzing and the established optimization polishing process SKD61-coated Ni-P material to show the effectiveness of the proposed OCMNO algorithm. Polishing experiments demonstrate the optimal technological parameters based on a new algorithm and rotary magnetic polishing method to give the best-machined surface quality. From the analysis and experiment results when polishing magnetic SKD 61 coated Ni-P materials in a rotating magnetic field when using a Magnetic Compound Fluid (MCF). The technological parameters according to the OCMNO algorithm for ultra-smooth surface quality with Ra = 1.137 nm without leaving any scratches on the after-polishing surface. The study aims to provide an excellent reference value in optimizing the surface polishing of difficult-to-machine materials, such as SKD 61 coated Ni-P material, materials in the mould industry, and magnetized materials.

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