case study 6

Clearing SPC Hurdles Six obstacles threaten statistical process control success

STATISTICAL PROCESS control (SPC) has provided significant cost savings for

companies that are fortunate enough to

implement it fully. Implementation chal-

lenges, however, can waylay the best of

intentions.

When you consider the steps needed

to begin using productive control charts,

certain critical hurdles become apparent.

These hurdles apply to all SPC programs,

whether pencil and paper or automated,

and whether simple or complex analytical

techniques are employed.

Hurdle 1—Adequate training: After

management support for the overall SPC

program is obtained and the program’s

purpose is publicized, training must be

done. At least three levels of training are

beneficial:

• Comprehension training for upper

management, so the reasons for SPC

can be defended, supported and tied to

the bottom line.

• Competency training for engineers

who are responsible for the processes

and products that require the control

charts.

• Awareness training for operators who

are responsible for the day-to-day main-

tenance of the charts. Operators need

to be able to collect the required data

and react to what the resulting control

chart data indicates.

The participants’ comprehension of the

training should be verified, and rewards

can be given to all who demonstrate an

understanding of the techniques.

Hurdle 2—Process definition: The

processes selected for SPC should be up-

wardly traceable to an important company

metric, such as overall cost of quality,

customer complaints or yield. Processes

can be chosen based on whether they

produce high percentage of sales or profit

margin, or exhibit a gap between current

and expected performance.

Hurdle 3—Variable selection:

Critical process outputs need to be first

identified, because SPC can be applied

to these outputs to protect the customer.

Typically, outputs are product characteris-

tics, such as tensile strength, appearance

or dimensions. Critical process inputs are

then identified, often through an analytical

tool or matrix that quantitatively allows

prioritization by defining the importance

and strength of the relationships between

inputs and outputs.

Hurdle 4—Process stability veri-

fication: Process instability will create

out-of-control points, leading to numer-

ous corrective actions. If the process is

not stable, an investigation should be

performed to determine and correct the

assignable cause. Careful data collection

is of the utmost importance, as is expert

analysis to ensure the absence of unusual

trends and unexplainable data points.

Hurdle 5—Process capability deter-

mination: Once the process is demonstrat-

ed to be stable, the data can be compared

to a specification. Capability indexes are

calculated, and the results should meet

company requirements. If the process is not

capable, several options exist:

• Improve the process.

• Change the specification.

• Make a business decision to accept the

low yield.

• Do not make the product.

Hurdle 6—Benefits demonstration:

In cost-of-quality terms, SPC is a prevention

cost. Implementing the program is an invest-

ment that will pay dividends later. The cost

savings created by SPC should be calculated

and publicized, stating reductions in:

• External failure cost of customer

complaints.

• Internal failure costs of rework and pro-

cess yield, including material and labor.

• Appraisal cost of final inspection.

Ultimately, a better understanding of a

company’s processes through SPC should

lead to higher profits, better job security

and more opportunity for all employees.

By identifying and clearing these hurdles,

the chance of long-term success is much

higher. QP

Implementation challenges can overcome the best of intentions.

SCOTT A. LAMAN is a global quality systems senior manager for Teleflex Medical Inc. in Reading, PA. He earned a master’s degree in chemical engineering from Syracuse University. He is a senior member of ASQ and is a certified quality engineer, reliability engineer, quality manager, Six Sigma

Black Belt and quality auditor.

READ MORE ABOUT THE BASICS Visit www.qualityprogress.com to read more Back to Basics articles on topics such as root cause analysis, data collection and fishbone diagrams.

BACK TO BASICS BY SCOTT A. LAMAN

January 2016 • QP 55

Best of NOVEMBER 2008