Understanding the Mechanism of Abrasive-Based Finishing Processes Using Mathematical Modeling and Numerical Simulation

Abstract

Recent advances in technology and refinement of available computational resources paved the way for the extensive use of computers to model and simulate complex real-world problems difficult to solve analytically. The appeal of simulations lies in the ability to predict the significance of a change to the system under study. The simulated results can be of great benefit in predicting various behaviors, such as the wind pattern in a particular region, the ability of a material to withstand a dynamic load, or even the behavior of a workpiece under a particular type of machining. This paper deals with the mathematical modeling and simulation techniques used in abrasive-based machining processes such as abrasive flow machining (AFM), magnetic-based finishing processes, i.e., magnetic abrasive finishing (MAF) process, magnetorheological finishing (MRF) process, and ball-end type magnetorheological finishing process (BEMRF). The paper also aims to highlight the advances and obstacles associated with these techniques and their applications in flow machining. This study contributes the better understanding by examining the available modeling and simulation techniques such as Molecular Dynamic Simulation (MDS), Computational Fluid Dynamics (CFD), Finite Element Method (FEM), Discrete Element Method (DEM), Multivariable Regression Analysis (MVRA), Artificial Neural Network (ANN), Response Surface Analysis (RSA), Stochastic Modeling and Simulation by Data Dependent System (DDS). Among these methods, CFD and FEM can be performed with the available commercial software, while DEM and MDS performed using the computer programming-based platform, i.e., “LAMMPS Molecular Dynamics Simulator,” or C, C++, or Python programming, and these methods seem more promising techniques for modeling and simulation of loose abrasive-based machining processes. The other four methods (MVRA, ANN, RSA, and DDS) are experimental and based on statistical approaches that can be used for mathematical modeling of loose abrasive-based machining processes. Additionally, it suggests areas for further investigation and offers a priceless bibliography of earlier studies on the modeling and simulation techniques for abrasive-based machining processes. Researchers studying mathematical modeling of various micro- and nanofinishing techniques for different applications may find this review article to be of great help.

A comprehensive review on surface quality improvement methods for additively manufactured parts

“…software simulation-based techniques such as discrete element method, molecular dynamics simulation, finite element method, CFD and experimental techniques based on statistical software such as stochastic modeling & simulation by the data-dependent system, artificial neural network (ANN), response surface analysis and multivariable regression analysis (MVRA). The classification of modeling and simulation techniques for the evaluation and optimization of AFM process parameters (Hashmi et al , 2022b) is shown in Figure 35.…”

“…As a result, it was found that a better surface finish could be achieved at 50% abrasive concentrations over a long finishing period. Similarly, Hashmi et al have also investigated the postprocessing of FDM-printed parts using the AFM process to improve their surface finish (Hashmi et al, 2021;Hashmi et al, 2022aHashmi et al, , 2022b. Leong et al (1998) have used the abrasive jet deburring process for surface finishing of SLA-based jewelry models.…”

Mechanical properties of carbon fiber reinforced with carbon nanotubes and graphene filled epoxy composites: experimental and numerical investigations

“…The percentage of elements and the quantity of alloying elements used in magnesium determine its mechanical and corrosion behavior [21]. The outcomes of the simulations can be very helpful in forecasting a variety of behaviours material under static and dynamic conditions [22]. The mechanical and wear properties influencing parameters are explored for Al based metal matrix composites [23].…”

Parameter Optimization of RB-SiC Polishing by Femtosecond Laser

“…Nano-scale polishing of optical components can be realized by traditional polishing methods, including abrasive polishing [ 4 , 5 ], wet polishing [ 6 ], magnetorheological polishing [ 7 ], and ion beam machining [ 8 ]. H. Cheng et al put forward a magnetorheological fishing (MRF) [ 9 ] process for aspheric silicon carbide mirrors.…”