application of quality improvement techniques to the powder coat process joan burtner, chris durre...

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Application of Quality Improvement Techniques to the Powder Coat Process Joan Burtner, Chris Durre & Nikki Smith Department of Mechanical and Industrial Engineering Mercer University, Macon, GA

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Application of Quality Improvement Techniques to

the Powder Coat Process

Joan Burtner, Chris Durre & Nikki Smith

Department of Mechanical and Industrial Engineering

Mercer University, Macon, GA

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 2

The Six Sigma Approach in the Business Community

Six Sigma - a comprehensive system for achieving, sustaining and maximizing business success

Drivers a close understanding of customer needs, disciplined use of facts, data, and statistical

analysis diligent attention to managing, improving, and

reinventing the business process

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 3

Benefits of the Six Sigma Approach

cost reduction productivity improvement market-share growth customer retention cycle-time reduction defect reduction culture change product/service development

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 4

The Six Sigma PhilosophyDesigned to foster data-driven

management decisions

The Three C’s common metrics “constant” communication culture change

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 5

Selection Criteria for Six Sigma Improvement Projects

There is a gap between current and desired/needed performance.

The cause of the problem is not clearly understood.

The solution isn’t predetermined, nor is the optimal solution apparent.

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 6

School of Engineering Senior Design Course

Two semester course required for graduation with a bachelor’s degree in engineering or industrial management

Student Teams Two or three students Often interdisciplinary

Management Senior design course instructor Departmental technical advisor

Client – internal or external

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 7

Paint Cell Project

Interdisciplinary team Industrial management Industrial engineering

Technical advisor - Joan Burtner

External client Georgia manufacturer Practices Six Sigma philosophy

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 8

Powder Coat Process Overview

Material - powdered paintTwo basic application methods

Part is lowered into a fluidized bed of the powder, which is electrostatically charged

Powdered paint is electrostatically charged and sprayed onto the part

Curing Part placed in an oven - powder particles melt

and form a continuous film

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 9

Powder Coat EquipmentSpray Gun

Corona charging guns -electric power used to generate the electrostatic charge

Tribot charging guns - electrostatic charge generated by friction between the powder and the gun barrel

“Bell” charging guns -powder charged by being "flung" from the perimeter of the "bell

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 10

Powder Coat Facility

Typical

Spray

Booth

Courtesy: www.thefabricator.com

Accessed March 12, 2004

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 11

Quality IssuesSurface preparationOperators

Training Skill

CoverageColor changeCleanliness/ contamination

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 12

Six Sigma Methodology

DefineMeasureAnalyze ImproveControl

Project Scope D-M-A

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 13

Preliminary Process Map

Load

Wash

Unload

Paint

Cure

Dry

Rework Accept

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 14

Process Step

# Input Measure System

C/U

Type

Output Measure System

Load 4

Wash 4

Dry 2 Drying oven Visual inspection

C Dry panel Visual inspection

Paint 6

Cure 2

Unload 1

Rework 2

Paint Cell Process Matrix

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 15

Key Customer Requirements

Minimal paint thickness

Even coverage

Scratch-free parts

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 16

Preliminary Data Collection

Student teams Observer Recorder

Random sampling75 observations for control chartsCollection sheet variables determined

by client

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 17

Revised Data Collection

Student teams Observer – voltage, temperature, etc Thickness gauge operator Thickness gauge recorder

Revised data collection form Limited variables – panel, color, hook, 5

locations Larger cells for recording data

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 18

# Process Step

Process

Input

Paint

Thickness

Even

Coverage

Damage

FreeTotal

Customer Imp 7

Customer Imp 9

Customer Imp 10

1 Load Hook 3* 3 3 78**

2 Load Conveyor 3 3 3 78

3 Paint Spray Gun 9 9 1 154

4 Cure Temp 3 3 1 58

Cause and Effect Matrix

* Correlation values 0, 1, 3, 9 **Sample calculation 7*3+9*3+10*3=78

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 19

Control Charting Deliverables

Target Factor - paint thickness Data collection plan Documentation of plan as standard

operating procedure Control chart training materials Control charts of baseline data

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 20

Control Charting Locations Factor - paint

thickness 5 locations Repeated

measures 25 samples for

baseline chart

North

West Middle East

South

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 21

Control Charting Sample Preliminary

Range not in control

252015105Subgroup 0

4.54.03.53.02.52.01.51.00.5

0.0

Sam

ple

Mea

n

1

6 5 5 6 5 6

1

Mean=1.818

UCL=3.186

LCL=0.4504

6

5

4

3

2

1

0

Sam

ple

Ran

ge

1

1

R=0.7272

UCL=2.376

LCL=0

Xbar/R Chart f or SB

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 22

Control Charting Sample Results - Revised

Range in control Xbar not in control

2010Subgroup 0

3.5

2.5

1.5

0.5

Sam

ple

Mea

n

51 1

15

12

2

56 6

65

22

2

1

Mean=1.698

UCL=2.511

LCL=0.8855

1.5

1.0

0.5

0.0

Sam

ple

Ran

ge

R=0.4322

UCL=1.412

LCL=0

Xbar/R Chart f or SBrev ised

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 23

Designed Experiments

Dependent variable - paint thicknessFactor 1 - locationFactor 2 - shiftStatistical software package - Minitab

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 24

Failure Modes and Effects Analysis (FMEA) Techniques

48 process steps selected for investigation 4 experts polled

Operators Management

Ratings entered into basic FMEA worksheet RPNs calculated Process steps ranked by RPN (high to low)

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 25

Failure Modes and Effects Analysis - Category Ratings 1

Severity of Effect (10-1) Hazardous without warning Hazardous with warning Loss of primary function Reduced primary function performance Loss of secondary function Reduced secondary function performance Minor defect noticed by most customers Minor defect noticed by some customers Minor defect noticed by discriminating customers No effect

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 26

Failure Modes and Effects Analysis - Category Ratings 2

Likelihood of Occurrence 9 Very High: Almost inevitable 7 High: repeated failures 4 Moderate: Occasional failures 2 Low: Relatively few failures 1 Remote: Failure is unlikely

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 27

Failure Modes and Effects Analysis - Category Ratings 3

Ability to Detect (10-1) Cannot detect Very remote chance of detection Remote chance of detection Very low chance of detection Low chance of detection Moderately high chance of detection High chance of detection Very high chance of detection Almost certain detection

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 28

Risk Priority Number Example Calculations

Paint Material – accident or transport failure Potential Failure Effect

Lack of paint consistency Severity of Effect rating 4

Potential Cause Dropped powder Likelihood of Occurrence rating 3

Current Control Lifting procedures Ability to Detect rating 3

Severity*Likelihood*Detection = 36 = RPN

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 29

Failure Modes and Effects Analysis Results

Ratings ranged from 300s to 20sUncontrolled process steps eliminatedCritical controlled process steps

Powder application - operator Cure process Powder application - spray gun Loading Unloading

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 30

Control Plan Worksheet Critical to Quality (CTQs) factors listed

according to RPN ranking Process step as listed in process map Inputs/outputs Process specifications Measurement system Current control plan

Control method Who Where When Reaction plan

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 31

Control Plan Follow-up

Revision of current standard operating procedures (SOP)

Establishment of standard operating procedures for CTQs that do not already have an SOP

Periodic review

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 32

Future Work Phase 1

Development of plan for constant metrics Implementation of new SOPs

Phase 2 Periodic process review Implementation of new metrics as needed

Phase 3 Project closure Implementation of related Six Sigma projects

IIE Annual Conference May 2004 Presenter: Dr. Joan Burtner, Mercer University 33

Contact Information

[email protected] 105D, School of EngineeringPhone (478) 301- 4127Fax (478) 301- 2331