Keywords

Mechanical micro machining, heterogeneous materials, metal matrix composites (mmcs), ceramic particle reinforcement, strengthening mechanism, ductile fracture model, finite element (fe), cutting simulation, chip formation

Abstract

This study focuses on developing explicit analytical and numerical process models for mechanical micro-machining of heterogeneous materials. These models are used to select suitable process parameters for preparing and micro-machining of these advanced materials. The material system studied in this research is Magnesium Metal Matrix Composites (Mg-MMCs) reinforced with nano-sized and micro-sized silicon carbide (SiC) particles. This research is motivated by increasing demands of miniaturized components with high mechanical performance in various industries. Mg-MMCs become one of the best candidates due to its light weight, high strength, and high creep/wear resistance. However, the improved strength and abrasive nature of the reinforcements bring great challenges for the subsequent micro-machining process. Systematic experimental investigations on the machinability of Mg-MMCs reinforced with SiC nano-particles have been conducted. The nanocomposites containing 5 Vol.%, 10 Vol.% and 15 Vol.% reinforcements, as well as pure magnesium, are studied by using the Design of Experiment (DOE) method. Cutting forces, surface morphology and surface roughness are characterized to understand the machinability of the four materials. Based on response surface methodology (RSM) design, experimental models and related contour plots have been developed to build a connection between different materials properties and cutting parameters. Those models can be used to predict the cutting force, the surface roughness, and then optimize the machining process. An analytical cutting force model has been developed to predict cutting forces of MgMMCs reinforced with nano-sized SiC particles in the micro-milling process. This model is iv different from previous ones by encompassing the behaviors of reinforcement nanoparticles in three cutting scenarios, i.e., shearing, ploughing and elastic recovery. By using the enhanced yield strength in the cutting force model, three major strengthening factors are incorporated, including load-bearing effect, enhanced dislocation density strengthening effect and Orowan strengthening effect. In this way, the particle size and volume fraction, as significant factors affecting the cutting forces, are explicitly considered. In order to validate the model, various cutting conditions using different size end mills (100 µm and 1 mm dia.) have been conducted on Mg-MMCs with volume fraction from 0 (pure magnesium) to 15 Vol.%. The simulated cutting forces show a good agreement with the experimental data. The proposed model can predict the major force amplitude variations and force profile changes as functions of the nanoparticles’ volume fraction. Next, a systematic evaluation of six ductile fracture models has been conducted to identify the most suitable fracture criterion for micro-scale cutting simulations. The evaluated fracture models include constant fracture strain, Johnson-Cook, Johnson-Cook coupling criterion, Wilkins, modified Cockcroft-Latham, and Bao-Wierzbicki fracture criterion. By means of a user material subroutine (VUMAT), these fracture models are implemented into a Finite Element (FE) orthogonal cutting model in ABAQUS/Explicit platform. The local parameters (stress, strain, fracture factor, velocity fields) and global variables (chip morphology, cutting forces, temperature, shear angle, and machined surface integrity) are evaluated. Results indicate that by coupling with the damage evolution, the capability of Johnson-Cook and Bao-Wierzbicki can be further extended to predict accurate chip morphology. Bao-Wierzbiki-based coupling model provides the best simulation results in this study. v The micro-cutting performance of MMCs materials has also been studied by using FE modeling method. A 2-D FE micro-cutting model has been constructed. Firstly, homogenized material properties are employed to evaluate the effect of particles’ volume fraction. Secondly, micro-structures of the two-phase material are modeled in FE cutting models. The effects of the existing micro-sized and nano-sized ceramic particles on micro-cutting performance are carefully evaluated in two case studies. Results show that by using the homogenized material properties based on Johnson-Cook plasticity and fracture model with damage evolution, the micro-cutting performance of nano-reinforced Mg-MMCs can be predicted. Crack generation for SiC particle reinforced MMCs is different from their homogeneous counterparts; the effect of micro-sized particles is different from the one of nano-sized particles. In summary, through this research, a better understanding of the unique cutting mechanism for particle reinforced heterogeneous materials has been obtained. The effect of reinforcements on micro-cutting performance is obtained, which will help material engineers tailor suitable material properties for special mechanical design, associated manufacturing method and application needs. Moreover, the proposed analytical and numerical models provide a guideline to optimize process parameters for preparing and micro-machining of heterogeneous MMCs materials. This will eventually facilitate the automation of MMCs’ machining process and realize high-efficiency, high-quality, and low-cost manufacturing of composite materials.

Notes

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Graduation Date

2012

Semester

Fall

Advisor

Xu, Chengying

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Mechanical Engineering

Format

application/pdf

Identifier

CFE0004570

URL

http://purl.fcla.edu/fcla/etd/CFE0004570

Language

English

Release Date

December 2013

Length of Campus-only Access

1 year

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

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