MMRL-Research

Lamar University Micro Manufacturing Research Lab

Dr. Liu's research expertise is in the micro/meso-scale machine tool system design (mMT) and process modeling and analysis of micro-machining process. He is also interested in precision engineering, metrology and statistical quality control. He is actively pursuing funding opportunities. The recent sponsored research program as well as some previous research work are summarized here.

Ongoing Research Projects

Dr. Liu has setup a Micro-Manufacturing Research Lab in Lucas Engineering Building, Room 141 with the startup fund. The lab hosts a Microlution 310S precision 3-axis micro-milling machine and other experimentation facilities.
Dr. Liu received a research contract from Schlumberger Research Center. The proposal is entitled " Manufacturing Process Innovation: Development of a non-contact Metrology System for Dimension Measurement and Surface Characterization of Deep Holes". ($105,000)
The pre-proposal "Bridging the Gap between Nano- and Macro-World: Fundamental Study of Micro-machining Accuracy" has received the invitation for full proposal from Texas ARP. The pre-proposal was prepared by Dr. Xinyu Liu and Dr. Weihang Zhu to compete in the 2008 Texas ARP. The success rate for the pre-proposal was around 28%. The full proposal is due January 29, 2008.

Previous Research Projects

Micro/Meso-Scale Machine Tool Systems (mMT) and Microfacotory
The global trends of miniaturization in products and systems have created tremendous needs in manufacture of miniature components with critical dimensions ranging from 10 microns to 100 mm. A recent study by Northern Illinois University School of Business published in Cutting Tool Engineering Magazine estimated a $32.5B worldwide market for precision components smaller than 50mm². A few specific applications include: Precision miniature ball bearings for weapons systems; Miniature fluid dynamic bearings for defense and electronic applications Small, precision holes for fuel-injector nozzles; Mechanical components for hearing aids, pacemakers, stents, bone screws; Pumps and valves for micro-scale fuel cells; Precision turbines for micro-scale engines; The micro/meso-scale machine tool (mMT) is an emerging technology for cost-effective manufacture of small precision parts. The paradigm of using mMT for micromachining leverage many scientific and practical advantages over conventional size machine tools, such as favorable scaling law, lower machine cost and increased deployment opportunity due to increased portability. While a graduate research assistant at University of Illinois at Urbana-Champaign, Dr. Liu participated in the development of the 1st generation mMT, led the CNC control system design and implementation. After graduation, Dr. Liu worked as a research engineer at Microlution Inc, Chicago. He made significant contribution to the launch of the company's first commercial product: 310S 3-Axis Micro-milling machine. Current research activities target on improving the machining accuracy through comprehensive error measurement and compensation. Three major error source will be considered: Machine tool error; Cutting tool geometry error due to spindle runout and fabrication error: Surface location error due to process forces and vibrations.	1st Generation mMT Testbed Microlution 310S

Mathematical Modeling and Analysis of Micro-endmilling Process

The overarching objective of this work is to enlarge and enhance the science base of micro/meso-scale machining to accelerate the development of models and methods that will lead to the significant improvements in both quality and productivity. Research has been done in three sub-areas: 1) Cutting Mechanisms at Micro-Meso Scale Machining; 2) Dynamics of Micro-endmilling; 3) Surface Generation of Micro-endmilling.

Cutting Mechanisms at Micro-scale - Minimum Chip Thickness Effect and Elastic Recovery

In micro-machining, the uncut chip thickness is comparable or even less than the tool edge radius and as a result a chip will not be generated if the uncut chip thickness is less than a critical value, viz., the minimum chip thickness . The minimum chip thickness effect significantly affects machining process performance in terms of cutting forces, tool wear, surface integrity, process stability, etc. In this work, an analytical model has been developed to predict the minimum chip thickness values, which are critical for the process model development and process planning and optimization. The model accounts for the effects of thermal softening and strain hardening on the minimum chip thickness. The influence of cutting velocity and tool edge radius on the minimum chip thickness has been taken into account. The model has been experimentally validated with 1040 steel and Al6082-T6 over a range of cutting velocities and tool edge radii. The developed model has then been applied to investigate the effects of cutting velocity and edge radius on the normalized minimum chip thickness for various carbon steels with different carbon contents and Al6082-T6.

SEM image of edge radius	Slipline Model considering MCT
Surface topography for measuring MCT	Model Prediction for 1040 Steel

Dynamics of Micro-endmilling

A dynamic cutting force and vibration model of the micro-endmilling process that account for the dynamics of the micro-endmill, influences of the stable built-up-edge, and the effect of minimum chip thickness, leastic recovery, and the elastic-plastic nature in ploughing/rubbing was developed. The model predict the cutting forces and tool vibrations within 20%. The results indicated that the large edge radius relative to the feedrate causes the process stability to be sensitive to the feedrate, resulting in the low feedrate instability phenomenon.

Effects of Elastic recovery and dynamic vibration on cutting forces	Time domain vibration prediction under different feedrate to show the low feedrate instability
Specific Cutting Energy vs. Chip Thickness

Surface Generation of Micro-endmilling

In this research, the influence of the unique cutting mechanisms in micro-endmilling on surface generation have been studied. Comprehensive surface generation models for both the sidewall and floor surfaces have been developed that combine both deterministic and stochastic models by superposition. Six factors were identified as having important effects on surface generation in micro-endmilling. They are: (1) process kinematics; (2) process dynamics; (3) cutting edge geometry; (4) elastic recovery of the workpiece material; (5) minimum chip thickness effect and ploughing/rubbing; (6) micro-burr formation. The factors (1)- (4) affect the deterministic surface roughness and the factors (5)-(6) affect the stochastic surface roughness.

For the sidewall surface generation model, the deterministic model characterizes the surface topography generated from the relative motion between the cutting edge and the workpiece material. The model includes the effects of the process kinematics, dynamics, tool edge serration, and spindle runout. The stochastic model predicts the increased surface roughness generated from ploughing due to the minimum chip thickness effect. For the floor surface generation model, the deterministic model characterizes the 3D surface topography over the entire floor surface and considers the effects of the minimum chip thickness, the elastic recovery and the transverse vibration. The variation of the ploughing amount across the swept arc of the cutter due to the varying chip load conditions is accounted for in the stochastic model.

The deterministic sidewall surface generation model is also capable of predicting the surface location error due to tool/workpiece vibrations.


Floor Surface Topography (Experiment)	Floor Surface Topography (Simulation)
Sidewall Surface Topography (Experiment)	Sidewall Surface Topography (Simulation)