Six-Sigma: It’s a Dirty Job Andrew Gonce, McKinsey Bob Landel and Jitendra Gupta MBA ‘08, Darden.

Six-Sigma: It’s a Dirty JobSix-Sigma: It’s a Dirty Job

Andrew Gonce, McKinsey

Bob Landel and Jitendra Gupta MBA ‘08, Darden

Six-sigma approach

Practical

Problem

Practical

Problem

Practical

Solution

Practical

Solution

StatisticalProblem

StatisticalProblem

StatisticalSolution

StatisticalSolution

TraditionalTraditionalApproachApproach

Six-sigmaSix-sigmaApproachApproach

Six-sigma is a systematic data-driven approach, which leads to a sustainable solution for any problem 2

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Narrowing the Project Scope: F(x)

DMAIC Example – It’s a Dirty Job

What are the customer expectations of the process?

The outcomes with defects are identified as red in the population

Purpose and scope of the project

Reduce the Incidence of Dirt in the Primer Coat that occurs on the Hood of the vehicles at the Lexington Assembly Plant between the E-Coat Scuff Booth and the Prime Scuff after Oven station

Six-sigma leaders have a mind-set for meeting customer needs5


Key Deliverables of Define Phase

• Project Scope and estimation of benefit based on customer requirements and bottom-line performance

• A team charter with defined roles and responsibilities• A high-level process map

Few of the applicable toolsBaseline Performance for Y, Customer Survey Methods (focus groups, interviews, etc.) Project Risk Assessment, Stakeholder Analysis, High Level Project Plan

Y

y

x

Dirt in Paint

Dirt in Primer spray area; Dirt in Ovens

Critical X’s to be determined in Analyze phase

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Narrowing the Project Scope: F(x)

• Y = Dirt in Paint (F20)= f(x) {Prime, E-Coat,

Base Coat, Clear Coat}

o X = Dirt in Prime (37%) = f(w) {Agglomerates,

Sealer, Fibers, Rust, Condensate, Pollen}

W = Agglomerates in Prime (33%)= f(v) {Primer Spray

Booth, Ovens}

Critical “X” Contribution = 8-10% of F20 Calls


• Perform Gauge R&R on Primary Measurement System

• Evaluate Critical “X” Process capability

• Determine controls in place for Critical “X”

If you can’t measure it accurately, you can’t improve it!8


• For a continuous metric (such as distance, time etc) capture the specification limits (LSL, USL) and the target to determine the tolerance band (for acceptable parts). For discrete metric, identify the characteristics of a part that result in it being acceptable/defective

• The total observed variation in the data is a sum of variation in the process and variation in the measurement system. If the latter is higher than a limit, we will not be able to differentiate between good and bad parts. A good measurement system has to be both repeatable and reproducible

What is a defect? Is the measurement system capable of separating acceptable from defective parts?

If you can’t measure it accurately, you can’t improve it!9

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Gauge R&R – Dirt Count at Spill Out

• The Gauge R&R was conducted on the Hoods alone.– The Hood area is the

easiest to see Dirt in Prime.

– 15% of Warranty Verbatims call out the Hood as the location of Dirt.


Key Deliverables of Measure Phase

• Defined Performance standards (Spec limits and target)• Gauge R&R analysis of measurement system

Few of the applicable toolsGR&R, FMEA, Pareto analysis, Data collection plan

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Attribute Control Chart

0

1

2

3

4

5

Time

Ave

rag

e D

PU

s

DPU

UCL: 3.1

MEAN: 2.3

LCL: 1.1

Dirt in Prime Count Prior to Prime Scuff

Baseline Data: Prime Dirt Count

• The Dirt Analysts report on 20 unit samples before each scuff station in daily inspections


Is a the process in statistical control?What is the current process capability?

• The practical problem is converted to a statistical one. Capability is measured in terms of Z score and Cpk, which captures the mean and variation relative to specifications.

Objective of six-sigma is to reduce variation and to center process

3.1 DPU Upper Spec. Limit 0 DPU Lower Spec. Limit

Current Sigma Level: 1.33

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Is a the process in statistical control?What is the current process capability?

• The practical problem is converted to a statistical one. Capability is measured in terms of Z score and Cpk, which captures the mean and variation relative to specifications.

Objective of six-sigma is to reduce variation and to center process

3.1 DPU Upper Spec. Limit 0 DPU Lower Spec. Limit

Current Sigma Level: 1.33

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The fundamental objective of analyze phase is to identify those key process inputs (critical X’s) that are different for the good and the defective ones (or are statistically significant).

Critical X’s for Dirty Job exampleFactor 1: Temperature and HumidityFactor 2: Weekday VariabilityFactor 3: Prime Automation EquipmentFactor 4: Prime Ovens Factor 5: Area Conditioning

What is the current and desired process capability? Why, when and where do the defects occur?

Def Acceptable

ToolsFish bone, normality test, Hypothesis testing (for mean, median and variation), Regression, chi-square

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Factor 4: Prime Ovens

A Dirt Count was conducted for 28 vehicles, immediately before and after the Prime Ovens

The average increase in counted dirt was 10 defects per vehicle hood

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The 28 units that were counted were also tracked by which Prime Oven they passed through

There was a significant difference between the Oven Dirt Contribution, with Oven 2 adding the most defects

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The ANOVA Analysis for Smoke Primed Vehicles only shows that there is a greater than 95% significance between the change in dirt counts for each oven.

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Factor 4: Oven Cleaning

The Ovens are not covered in the Existing Work Order System – there is a gap


How can we fix the process?

• Identify the relationship of X’s on Y by developing the transfer function for Y=F(X), using tools such as DOE

• Determine the optimal settings and tolerance limits for X’s inputs to achieve the desired Z-score for Y.

• Run a test plan to confirm the causal relationship and to validate the improvement in Y

Improvement plan for X’sNo Description Improvement Plan

1 Temperature and Humidity Automatic booth balance

2 Weekday Variability Weekend PM schedule revisions

3 Prime Automation Equipment

Tracking process initiated, PM revisions

4 Prime Ovens Oven cleaning

5 Area Conditioning Update PM sheets, follow procedures22

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Reduction or Elimination of Contaminants in all Systems – Lower Agitation, Overhead Structure, Air Seals and inside Burner Units

Eliminate Mounds of charred dirt and Paint Chips visible inside of Conveyor Chain Track

Eliminate Dirt from rear side of High Temperature Recirculating Filters

Eliminate Rust and Dirt lying inside of Air Seals Eliminate Dirt blowing out of Lower Convection Hot Air Supply

Ducts Eliminate Dirt and Fibers on rear side of Panel Filters Eliminate Rust and Dirt Particles falling off Overhead Ceiling and

Hardware onto vehicles traveling through the ovens

BASF Recommendations

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Oven Cleaning is best conducted in a cycle that allows the oven to:be cleaned with dry ice, vacuum, and ragsbe heated to operating temperatures for 4-8 hoursbe inspected and re-cleanedand be re-heated for 4-8 hours prior to use

Action TakenDiscussion with Sam Lemay to standardize Oven Cleaning Procedure and sign-off. A Gap Analysis shows that the Prime Ovens do not have the level of standardized cleaning that the Prime Spray Booth, Sealer Deck and Vestibule have.

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The 3rd Pass Oven Cleaning that occurred in October ’02 resulted in a measurable improvement in dirt count per 20 units

Oven Cleanliness has a real effect on overall Dirt Count!

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Factor 5: Area Conditioning

A study was conducted in November 2002 following the Vehicle View through the entire Paint Process (BASF)

A number of Maintenance, Cleaning and Repair items were documented and recommendations were made

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Factor 5: Area Conditioning

Prime Spray Booth: Muck cleaning (grates and water) currently occurs annually. Entering this cleaning into the PM Work Order system is recommended.

Develop plan for additional humidity and water flow.

Trial an adhesive paper on the floor of the vestibule or oven entrance to trap airborne dirt and sprayed paint.

Eliminate Cotton Mops, Newspapers and Contaminants from the Spray Areas, follow the Dress Codes.

Recommendations


How did we improve the process?

Improvement plan for X’sNo Description Improvement Plan

1 Temperature and Humidity Automatic booth balance

2 Weekday Variability Weekend PM schedule revisions

3 Prime Automation Equipment

Tracking process initiated, PM revisions

4 Prime Ovens Oven cleaning

5 Area Conditioning Update PM sheets, follow procedures28

Actions already taken lowered the DPMO from 112,000 to 6000!

Booth Balance, External Environment and a reduction in environmental variability lowers the problems due to

Prime being out of spec.

Regular cleaning and Maintenance reduces fiber count and additional dirt in paint from airborne contamination.


How can we ensure that process stays fixed?• Establish post improvement capability and validate that

the pre and post difference is statistically significant• Run the MSA on X’s and establish control plan for Y and

X’sPre-Improvement Post-Improvement

Few of the applicable ToolsControl charts, Hypothesis testing, Mistake Proofing,, FMEA

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How can we ensure that process stays fixed?Control Chart: Defect Tracking “Y”

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How can we ensure that process stays fixed?

Control Chart: Action Plan “X”

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How can we ensure that process stays fixed?Control Chart: Defect Tracking “Y”

Control Chart: Action Plan “X”

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Lessons Learned

The walk-through by BASF, the dirt analysts, filter rep’s

et al. was instrumental in discovering a number of

system problems. This should be an annual occurrence

to maintain the systems.

Improvement efforts need to be quantified with data

(dirt count, operator comments, efficiency etc.) in order

for the results to be weighed.

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Lessons Learned

There are many, many factors that effect how clean a

particular vehicle is on any given day.

There are no easy, cheap or obvious solutions, all will

take some effort to discover and some effort to resolve.

The Sealer Deck and Prime personnel understand the

issues that they face in producing clean vehicles.

Six-Sigma: It’s a Dirty Job Andrew Gonce, McKinsey Bob Landel and Jitendra Gupta MBA ‘08, Darden.

Documents

fx slide

paint dirt

primer coat

phase project scope

darden slide

incidence of dirt

customer expectations

primer spray area dirt