Experimental Modeling of the Experimental Modeling of the Sanding Process Sanding Process --

The Relationship Between Input and The Relationship Between Input and Output ParametersOutput Parameters

James B. TaylorJames B. TaylorRichard L. Richard L. LemasterLemasterAndres L. CarranoAndres L. Carrano

North Carolina State UniversityNorth Carolina State University

Project SponsorsProject Sponsors

United States Department of Agriculture (USDA)Wood Machining and Tooling Research Program (WMTRP) - NC State UniversityAmerican Furniture Manufacturer’s Association (AFMA)Furniture Manufacturing and Management Center (FMMC) - NC State University

Introduction Introduction

Abrasive finishing processes (sanding) – Production time– Cost

Impact perceived and actual quality of productRelationships between key input and responses have not been properly established Automation of process has been limited by lack of published information

ObjectivesObjectives

Identify key inputs and outputs

Model of process

Optimization

Automation

Modeling SchemeModeling Scheme

PressureMRRSurfaceRoughness

Grit SizeAbrasive

Species

Orientation

SANDINGPROCESS

Assessment of Surface QualityAssessment of Surface QualityMonitoring the Machining ProcessMonitoring Product QualityMachining Research

Objectives:• Measure and define surface topography• Quantify surface defects• Identify specific machining problems• Provide on-line surface quality monitoring

laser/camera optical profilometer

Experimental Setup and MethodsExperimental Setup and Methods

Statistical Design of Experiments– Split Plot Fractional Factorial– Full Factorial design– Response Surface

Stroke SanderCNC Router

Material Removal Rate Material Removal Rate -- MRRMRR

MATERIAL REMOVAL RATE

P-150 P-220

PINEOAK

MAPLE

CHERRY

Pressur

e (psi

)

MR

R (c

ubic

inch

/min

)

Z-Axis

Plot Title

Y-Axis

X-Axis

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50 0.450

0.6500.750

0.0

5.0

10.0

15.0

Plot Title

Z-Axis

20.0

Y-Axis

X-Axis 0.5500.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

0.450

0.550

0.650

0.750

0.0

10.0

15.0

20.0

X-Axis

Z-Axis

Plot Title

Y-Axis

5.0

P-100

MRRMRR

100 120 160 180 200 220 0

6090

0

2

6

8

10

Column3

Column2

Column5

4

14030

SiC

EFFECT OF GRAIN ORIENTATION IN MATERIAL REMOVAL RATE

MR

R (c

ubic

inch

es/m

in)

GRIT SIZE

Orienta

tion (

Degree

s)

Al2 O3

Surface RoughnessSurface Roughness

Column5

Column3

P-Spec2.PDW

P-100 P-150 P-220

0.501.00

1.50

2.002.50

3.00

3.504.00

4.500.45

0.60

0.75

70.0

117.5

165.0

212.5

Column2

Column4

Column3

P-Spec2.PDW

260.0

Rq

(mic

roin

ches

)

CHERRY

MAPLEOAK

PINE

0.501.00

1.50

2.002.50

3.00

3.504.00

4.50

0.600.75

70.0

117.5

165.0

212.5

260.0

P-Spec2.PDW

Column6

Column2

Column3

0.45

Pressur

e (psi

)

SURFACE ROUGHNESS

SurfaceSurface RoughnessRoughness

140 160 180 200 220 0.50

0.80100

150

200

250

Column2

Column3

Column5

Data3.PDW

300

100 1200.65

Al2 O3

SiC

SILICON CARBIDE Vs ALUMINUM OXIDE

GRIT SIZE

Rq

(mic

roin

ches

)

Pressur

e (psi

)

Future of SandingFuture of SandingMicro-Replicated AbrasivesCustom Sanding Tooling Designs– Minerals or combinations– Size and shape– Patterns / Directional

Control– Predictable performance– Wear– Monitoring

Proposed Modeling SchemeProposed Modeling Scheme

SANDINGPROCESS

GRIT SIZE

ABRASIVE

PRESSURE

SPECIES

ORIENTATION

MRR

ROUGHNESS

SUBSURFACE CRUSHING

BELT LOADING

FEED RATE

SPINDLE

RESILIENCE

CUTTERDIRECTION

ConclusionsConclusionsInput - Output Relationships

Surface Quality - Surface Roughness

Process Economics

Model for Optimization, Visualization and Robustness

Comments and Discussion