大家好,
我們最近從 JMP 14 升級到 15。
完成能力分析後,我們的一個腳本目前顯示不同的結果。
在 JMP 14 中,我們得到以下結果:

在 JMP 15 中,完全相同的表達式突然顯示 PPx 值(注意 - 這是來自不同的分析,因此限制不同):

我們用來產生圖表的程式碼:
Distribution(
Uniform Scaling( 1 ),
Stack( 1 ),
Arrange in Rows( 6 ),
Automatic Recalc( 1 ),
Continuous Distribution(
Column( Eval( Column( i ) ) ), // i = loopcounter
Quantiles( 0 ),
Horizontal Layout( 1 ),
Histogram( 0 ),
Vertical( 0 ),
Axes on Left( 1 ),
Outlier Box Plot( 0 ),
Customize Summary Statistics(
Std Err Mean( 0 ),
Upper Mean Confidence Interval( 0 ),
Lower Mean Confidence Interval( 0 ),
Maximum( 1 )
),
Capability Analysis(
// Column # in Limits table doesn't match columns # in result table
USL( Num( Eval( dtDistLimits:_USL[i - 1] ) ) ),
LSL( Num( Eval( dtDistLimits:_LSL[i - 1] ) ) )
)
),
SendToReport(
Dispatch( {}, "Distributions", OutlineBox, {Set Title( "Distributions" )} ),
Dispatch(
{},
"Mean(Result",
OutlineBox,
{Set Title(
sComponentName || " Specification: (LSL " || sLslDisplayValue || ", USL " || sUslDisplayValue
|| ")"
)}
),
Dispatch(
{"Distributions", "Mean(Result", "Summary Statistics"},
"",
NumberColBox,
{Set Format( 9, 3 )}
),
Dispatch( {"Distributions", "Mean(Result"}, "Capability Analysis", OutlineBox, {Set Title( "" )} ),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis"},
"Specification",
StringColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis"},
"Value",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis"},
"Portion",
StringColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis"},
"% Actual",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis", "Long Term Sigma"},
"1",
ScaleBox,
{Min( Eval( iMinScale ) ), Max( Eval( iMaxScale ) ), Inc( 0.5 ), Minor Ticks( 5 )}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis", "Long Term Sigma"},
"Lower CI",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis", "Long Term Sigma"},
"Upper CI",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(Result", "Capability Analysis", "Long Term Sigma"},
"Portion",
StringColBox,
{Name( "Hide/Unhide" )(1)}
),
// THIS DISPATCH GENERATES ERRORS
Dispatch(
{"Distributions", "Mean(RESULT", "Capability Analysis", "Long Term Sigma"},
"Percent",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
),
// THIS DISPATCH GENERATES ERRORS
Dispatch(
{"Distributions", "Mean(RESULT", "Capability Analysis", "Long Term Sigma"},
"PPM",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
),
Dispatch(
{"Distributions", "Mean(RESULT", "Capability Analysis", "Long Term Sigma"},
"Sigma Quality",
NumberColBox,
{Name( "Hide/Unhide" )(1)}
)
)
); // Distribution我可以做些什麼來再次獲得正確的(舊的)結果嗎?
謝謝你,
揚
您可以使用PkK 功能標籤訊息關閉 Ppk 標籤。
任何一個
Names Default To Here( 1 );
dt = Open( "$SAMPLE_DATA/Quality Control/Coating.jmp" );
obj = dt << Distribution( Column( :Weight ) );
obj << PpK Capability Labeling( 0 );
obj << Capability Analysis( LSL( 16 ), USL( 24 ), Target( 20 ) );
或者
Names Default To Here( 1 );
dt = Open( "$SAMPLE_DATA/Quality Control/Coating.jmp" );
obj = dt << Distribution( Column( :Weight ),
PpK Capability Labeling( 0 ),
Capability Analysis( LSL( 16 ), USL( 24 ), Target( 20 ) )
);
將現代能力分析的混亂歸咎於AAIG。
我最喜歡的名言:
相對較新的 Pp 和 Ppk 符號的引入以及在利益相關者沒有共識的情況下重新定義 Cp 和 Cpk 造成了相當大的混亂。根據我們的經驗,許多審核員和從業人員並不知道 AIAG 所稱的 Ppk 已在該行業中作為 Cpk 使用了大約 30 年。
http://www.sematech.org/docubase/document/Semiconductor_Industry_SPC_Practices.pdf
或者,換一種方式
過程表現指數d Pp 和Ppk 是倒退了一步。它們是對工程工作和管理工作的浪費——它們什麼也沒告訴你。
- DC蒙哥馬利
或者說得更強烈
通過品質標準或行業指南強制使用 Pp 和 Ppk 屬於“統計恐怖主義”
- 科茨和洛夫萊斯
幸運的是,我們有一個開關,可以將它們關閉:)