PHASE III: RECOMMEND YESNO FOR ACCEPTANCE - A STUDY PREDICTING LONG-TERM CAPABILITY


PHASE III: RECOMMEND YES/NO FOR ACCEPTANCE ”A STUDY PREDICTING LONG- TERM CAPABILITY

Description: The purpose of Phase III is to finally conclude "accept" or "reject" for the machine by predicting long-term stability and capability. The main difference from Phase II is that the 125 parts ( n = 125) are collected over a much greater time period (at least 8 hours). The increased time period of data collection gives the study more validity in predicting future production performance. The reason for the increased validity in Phase III is that potentially additional sources of special variation are allowed into the data collection time frame.

Objectives: The objectives of Phase III are to

  • Analyze data to determine control and potential capability (using an Xbar and R chart with 5 parts per subgroup ).

  • Confirm investigations of distribution shape.

  • Predict long-term production performance of process.

Phase III participants include the

  • Machine acceptance team

  • Supplier of the machine

  • Maintenance and setup personnel

  • Material suppliers

Phase III method (Figure 16.10): Before data collection, set up the process using all the information that was collected in Phase I and any additional information from Phase II. Make sure to use the same gages and measurement process as in Phases I and II.

click to expand
Figure 16.10: Phase III flow chart.

Data collection: Collect 125 parts ( n = 125) over a period of at least 8 hours. The parts are to be collected in groups of five consecutive parts spaced evenly over the 8 hours (number the subgroups in time order). Measure the 125 parts and record them in their time order.

Data analysis: Plot the parts on an Xbar and R chart with the subgroup sizes of five. Assess control or out of control with the best possible chance of performing competently in production. If the control chart exhibits out-of-control conditions, an action plan must be developed with the supplier and the customer team. Using the action plan, the problem needs to be identified and removed from the process. After the changes, start back at Phase I.

If the control chart exhibits control, then investigate the distribution of the 125 parts. If they appear to have a normal distribution, then calculate C pk . If the distribution is not normal, calculate the capability with appropriate techniques such as mirror imaging and probability paper for nonnormal data.

If C p and C pk are <1.33, instruct the supplier to reduce the variation (reduce Rbar) in the process. If C p > 1.33 but C pk < 1.33, then the distribution needs to be centered on the middle of the specification. In either case, do not recommend acceptance of this machine. If the supplier can correct the problem, then go back to a Phase I study (after the vendor has made appropriate changes).

If the process shows potential capability (i.e., C pk > 1.33 99.994% in specifications), then recommend accepting the machine. A good way to make sure that Phase III has met all the requirements is to use a checklist such as the one in Table 16.4.

Table 16.4: A Typical Checklist Before Moving to the Next Phase

If at least 99.994% of the distribution is not within the specification limits, then develop an action plan based on the following questions.

 

Yes

No

Action required

Is the lack of capability because of the average?

_____

_____

__________

Is the lack of capability because of the range?

_____

_____

__________

Were there any trends or patterns over the time window of the study?

_____

_____

__________

Does the histogram suggest any unusual conditions such as nonnormality?

_____

_____

__________

Does the study log show any unusual occurrences that would help explain apparent incapability?

_____

_____

__________

Does either of the control charts give signals of unusual variation that would suggest stratification?

_____

_____

__________

Should the study be rerun?

_____

_____

__________

PHASE III EXAMPLE

These data were collected during a Phase III study (continuing the previous example). The Xbar and R charts show control, and the histogram indicates that a normal distribution is appropriate for a model of the population. Notice that the +4 sigma interval is not contained inside of the specification of 16 to 17; hence, this process would not be deemed potentially capable (i.e., C pk < 1.33). The distribution is too wide for the specifications, so just centering the process would not solve the problem. Because there is a wider window to the data collection in this study as compared with that in the Phase II study, more common variability was picked up. Material changes or ambient temperature changes are two examples of variables that change over longer periods of time. In any case, the variability of the process must be reduced, and an action plan for the supplier must be created and executed before any more work can be done.

Statistical (SQC) Data Analysis Phase III Example

Sample size

125

 

Actual

EST

Limits

       

99.730%

 

Target

16.5000

Low

15.9275

15.6634

16.0000

Average

16.4808

High

17.1796

17.2981

17.0000

Std. Dev.

0.2724

Range

1.2520

1.6346

1.0000

Skewness

0.3247

% < Low limit

3.20

3.88

 

Kurtosis

-0.2329

% > High limit

4.80

2.83

 

Normality test made

 

% Out of range

8.00

6.71

 

Normality assumed

     

C P

0.6118

Subgroup size = 5

     

C pk

0.5883

Cum Prob

Midpoint

Frequency

0.001

15.6000

0 +

0.002

15.7000

0 +

0.006

15.8000

0 +

0.017

15.9500

1 + *.

0.039

16.0000

7 + *** *** ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ”

0.081

16.1000

5 + ***** .

0.151

16.2000

14 + **********. ***

0.253

16.3000

14 + **************.

0.383

16.4000

19 + ***************.**

0.528

16.5000

19 + ****************.*

0.669

16.6000

15 + **************.

0.790

16.7000

13 + ***********.

0.879

16.8000

4 + ****.

0.938

16.9000

6 + *****.

0.972

17.0000

4 + **.* ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ” ”

0.988

17.1000

2+.*

0.996

17.2000

2 +.*

0.999

17.3000

0 +

1.000

17.4000

0 +

1.000

17.5000

0 +

Note: Histogram 1 "*" = 1 sample (actual data); "." = estimated distribution.

Statistical (SQC) Data Analysis Xbar Chart

LCL = 16.1070 Center = 16.4808 UCL = 16.8546

Subgroup size used: 5

Mean

SN

15.9200

16.3200

16.7200

   

+ ” ” ” ” ” + ” ” ” ” ” + ” ” ” ” ” + ” ” ” ” ” + ” ” ” ”

16.5719

 

I

:

   

+

*

:

16.2993

 

I

:

*

 

+

 

:

16.5259

 

I

:

   

+ *

 

:

16.4122

 

I

:

 

*

+

 

:

16.4357

5

I

:

   

* +

 

:

16.3791

 

I

:

 

*

+

 

:

16.5422

 

I

:

   

+

*

:

16.5326

 

I

:

   

+ *

 

:

16.3176

 

I

:

 

*

+

 

:

16.4736

10

I

:

   

*

 

:

16.6442

 

I

:

   

+

*

:

16.5625

 

I

:

   

+

*

:

16.4957

 

I

:

   

*

 

:

16.6789

 

I

:

   

+*

 

:

16.4741

15

I

:

   

*

 

:

16.3787

 

I

:

 

*

+

 

:

16.4047

 

I

:

 

*

+

 

:

16.6267

 

I

:

   

+

*

:

16.4170

 

I

:

 

*

+

 

:

16.5325

20

I

:

   

+

*

:

16.4492

 

I

:

   

* +

 

:

16.3410

 

I

:

 

*

+

 

:

16.5392

 

I

:

   

+ *

 

:

16.6133

 

I

:

   

+

*

:

16.3708

25

I

:

 

*

+

 

:

Statistical (SQC) Data Analysis Range Chart

LCL = 0.000 Center = 0.6445 UCL = 1.3599

Subgroup size used: 5

Range

SN

0.0000

0.4000

0.8000

1.2000

   

+ ” ” ” ” ” + ” ” ” ” ” + ” ” ” ” ” + ” ” ” ” ” + ” ” ” ” ”

0.9349

 

I

   

+ *

   

:

0.4814

 

I

   

* +

   

:

0.7988

 

I

   

+ *

   

:

0.4467

 

I

   

* +

   

:

0.5174

5

I

   

* +

   

:

0.8532

 

I

   

+ *

   

:

1.1206

 

I

   

+

*

 

:

0.4441

 

I

 

*

+

   

:

0.6426

 

I

   

*

   

:

0.4631

10

I

 

*

+

   

:

0.8453

 

I

   

+

*

 

:

0.5785

 

I

 

*

+

   

:

0.7972

 

I

   

+

 

*

:

0.7131

 

I

   

+

*

 

:

0.2194

15

I

*

 

+

   

:

0.8213

 

I

   

+

*

 

:

1.0042

 

I

   

+

 

*

:

0.5416

 

I

   

* +

   

:

0.5488

 

I

   

* +

   

:

1.0093

20

I

   

+

 

*

:

0.3880

 

I

 

*

+

   

:

0.3068

 

I

 

*

+

   

:

0.6682

 

I

   

+ *

   

:

0.1909

 

I

*

 

+

   

:

0.7767

25

I

   

+

*

 

:




Six Sigma and Beyond. Statistical Process Control (Vol. 4)
Six Sigma and Beyond: Statistical Process Control, Volume IV
ISBN: 1574443135
EAN: 2147483647
Year: 2003
Pages: 181
Authors: D.H. Stamatis

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