Process Yield, Process Centering and Capability Indices for One-Sided Tolerance Processes

Grau, Daniel

doi:10.1080/16843703.2012.11673283

Cited by 18 publications

(14 citation statements)

References 3 publications

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“…The quality of a process is defined by the centring process and the proportion of non-conforming manufactured items. Grau [7] gives the elements that will allow the user to choose the pair (u, v) that will meet his needs as best as possible. In this paper we show that gauge measurement errors have a significant impact on the estimation of a process capability.…”

Section: Resultsmentioning

confidence: 99%

“…The selected index is C l p (0.6, 0.2). So a value of C l p (0.6, 0.2) superior or equal to 1.33 enables us to say that the process is capable as far as the percentage of manufactured non conforming items is inferior or equal to 50 ppm, and the process mean does not move away for more than 42% of the distance between the target and the lower tolerance limit (Grau [7]). We propose to determine whether the process is capable when the risk k is equal to 3, and the degree of error contamination τ is equal to 0.25.…”

Section: Examplementioning

confidence: 99%

“…To illustrate our approach we go back to a study carried out within the Arkema company (Grau [7]). This company manufactures different sorts of polymer granulates which are transformed for many applications such as films or bottles used for food packaging.…”

Section: Examplementioning

confidence: 99%

“…Under the assumption of normality, and for (u, v) = (0, 0), Grau [7] gives the cumulative distribution function ofĈ u p (u, v) which can be rewritten as…”

Section: Sampling Distribution Ofĉ Ug P (U V) Andĉ Lg P (U V)mentioning

confidence: 99%

“…which is independent of μ, and which is nothing but the potential capability [7] suggests choosing parameters u and v according to the importance the user attaches to the process centring and/or to the percentage of non-conforming.…”

Section: Introductionmentioning

confidence: 99%

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Testing capability indices for one-sided processes with measurement errors

Grau

2013

Int. J. Metrol. Qual. Eng.

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Abstract. In the manufacturing industry, many product characteristics are of one-sided tolerances. The process capability indices C u p (u, v) and C l p (u, v) can be used to measure process performance. Most research work related to capability indices assumes no gauge measurement errors. This assumption insufficiently reflects real situations even when advanced measuring instruments are used. In this paper we show that using a critical value without taking into account these errors, severely underestimates the α-risk which causes a less accurate testing capacity. In order to improve the results we suggest the use of an adjusted critical value, and we give a Maple program to get it. An example in a polymer granulates manufactory is presented to illustrate this approach.

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Section: Resultsmentioning

confidence: 99%

Section: Examplementioning

confidence: 99%

Section: Examplementioning

confidence: 99%

“…Under the assumption of normality, and for (u, v) = (0, 0), Grau [7] gives the cumulative distribution function ofĈ u p (u, v) which can be rewritten as…”

Section: Sampling Distribution Ofĉ Ug P (U V) Andĉ Lg P (U V)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Testing capability indices for one-sided processes with measurement errors

Grau

2013

Int. J. Metrol. Qual. Eng.

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Process Selection for Linear Profiles with One‐sided Specifications Based on the Ratio Test Statistic

Wang

Tamirat

Tsai

2014

Quality & Reliability Eng

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The quality of a process is characterized by a functional relationship between the response variable and one or more explanatory variables called a linear profile. In this study, the process selection problem that deals with comparing two linear profiles with one‐sided specifications and selecting the one that has a significantly higher capability value is presented. An exact approach based on the ratio test statistic to tackle the supplier selection problem is proposed. Testing hypotheses with two cases for comparing two processes is considered. Critical values of the tests are calculated to determine the selection decisions. The number of profiles required for a designated selection power and confidence level is also provided. The results provide useful information to practitioners. One real example is used to illustrate the application of our proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.

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Supplier Selection for Multiple Linear Profiles with One-Sided Specifications

Wang

2014

Qual. Reliab. Engng. Int.

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When the quality of a process is represented by a relationship between one response variable and one or more independent variables called a multiple linear profile with in statistical control, the process capability analysis is widely used to measure the capability of the process to manufactured item within the required tolerance. In this paper, we propose the difference test statistic to compare two processes for multiple linear profiles with one-sided specifications. The number of profiles required for a designated selection power and confidence level is also provided. The performance of the proposed method is assessed using simulation study. The results provide useful information to practitioners. A real data from the logistic service shows that our method performs well in the application. Process yield indices for multiple linear profiles with one-sided specificationsA multiple linear profile is usually defined by a linear regression model. When the process is in statistical control, the relationship between the response variable and the two independent variables is modeled as

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Process Yield, Process Centering and Capability Indices for One-Sided Tolerance Processes

Cited by 18 publications

References 3 publications

Testing capability indices for one-sided processes with measurement errors

Testing capability indices for one-sided processes with measurement errors

Process Selection for Linear Profiles with One‐sided Specifications Based on the Ratio Test Statistic

Supplier Selection for Multiple Linear Profiles with One-Sided Specifications

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