Process capability indices for skewed populations

Chang, Young Soon; Choi, In Su; Bai, Do Sun

doi:10.1002/qre.489

Cited by 55 publications

(38 citation statements)

References 17 publications

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“…Many researchers have considered methods to determine the process capability of a non-normal process output. (See Chan, Cheng & Spiring [5]; Clements [6]; Rodrigues [7]; English & Taylor [8]; Castagliola [9]; and Chang, Choi & Bai [10]. )…”

Section: Opsommingmentioning

confidence: 99%

Process Capability Index-Based Control Chart for Variables

Adeoti¹,

Olaomi²

2017

SAJIE

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This paper proposes a process capability index-based control chart for variables using the Downton estimator with a specified Cp value. The proposed chart is able to address the issue of control and capability simultaneously. We also provide a control chart constant to construct the process capability index-based control chart. A numerical example is presented to demonstrate the application of the proposed chart, and the effect of non-normality is discussed. The result shows that the proposed control chart performs better in monitoring and assessing processes, and eliminates the usual twostage procedure reflected in the literature. OPSOMMING'n Prosesvermoë indeksgebaseerde beheerkaart word voorgestel vir veranderlikes met gebruik van die 'Downton' beramer met 'n gespesifiseerde Cp waarde. Die voorgestelde beheerkaart kan die kwessie rondom die beheer en vermoë gelyktydig aanspreek. 'n Beheerkaartkonstante word ook verskaf om die prosesvermoë indeksgebaseerde beheerkaart te skep. 'n Numeriese voorbeeld word voorgehou om die toepassing van die voorgestelde beheerkaart te illustreer. Die effek van nie-normaliteit word ook bespreek. Die resultaat toon dat die voorgestelde beheerkaart beter vertoon in die monitering en assessering van prosesse en dit elimineer die gewone twee stap prosedure wat in die literatuur gevind word.

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Section: Opsommingmentioning

confidence: 99%

Process Capability Index-Based Control Chart for Variables

Adeoti¹,

Olaomi²

2017

SAJIE

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“…The mean θ and the standard deviation σ of the sample are computed. The probability P θ can be estimated by using the number of observations with value smaller than or equal to θ (Chang et al, 2002):…”

Section: The Burr Transformation Approachmentioning

confidence: 99%

“…On the other hand, according to Chang et al (2002), the value of C pk , corrected for skewness, can be estimated as follows. First, the upper and lower capability indices are defined as…”

Section: A Simulated Annealing Approach To Solve the Vehicle Routing mentioning

confidence: 99%

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Process capability index Cpk for monitoring the thermal performance in the distribution of refrigerated products

Novaes

Lima

Carvalho

et al. 2015

Prod.

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The temperature of refrigerated products along the cold chain must be kept within pre-defined limits to ensure adequate safety levels and high product quality. Because temperature largely influences microbial activities, the continuous monitoring of the time-temperature history over the distribution process usually allows for the adequate control of the product quality along both short-and medium-distance distribution routes. Time-Temperature Indicators (TTI) are composed of temperature measurements taken at various time intervals and are used to feed analytic models that monitor the impacts of temperature on product quality. Process Capability Indices (PCI), however, are calculated using TTI series to evaluate whether the thermal characteristics of the process are within the specified range. In this application, a refrigerated food delivery route is investigated using a simulated annealing algorithm that considers alternative delivery schemes. The objective of this investigation is to minimize the distance traveled while maintaining the vehicle temperature within the prescribed capability level.

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“…Process capability index (PCI) is developed to provide a common and easily understood language for quantifying process performance, and is a dimensionless function of process parameters and specifications (Chang, Choi & Bai, 2002). Process capability indices (PCIs) provide numerical measures on whether a process conforms to the defined manufacturing capability prerequisite.…”

mentioning

confidence: 99%

Comparing performances of clements, box-cox, Johnson methods with weibull distributions for assessing process capability

Şenvar

Şennaroğlu

2016

JIEM

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Abstract:Purpose: This study examines Clements' Approach (CA), Box-Cox transformation (BCT), and Johnson transformation (JT) methods for process capability assessments through Weibull-distributed data with different parameters to figure out the effects of the tail behaviours on process capability and compares their estimation performances in terms of accuracy and precision.Design/methodology/approach: Usage of process performance index (PPI) P pu is handled for process capability analysis (PCA) because the comparison issues are performed through generating Weibull data without subgroups. Box plots, descriptive statistics, the root-mean-square deviation (RMSD), which is used as a measure of error, and a radar chart are utilized all together for evaluating the performances of the methods. In addition, the bias of the estimated values is important as the efficiency measured by the mean square error. In this regard, Relative Bias (RB) and the Relative Root Mean Square Error (RRMSE) are also considered. Findings:The results reveal that the performance of a method is dependent on its capability to fit the tail behavior of the Weibull distribution and on targeted values of the PPIs. It is observed that the effect of tail behavior is more significant when the process is more capable.-634-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1703Research limitations/implications: Some other methods such as Weighted Variance method, which also give good results, were also conducted. However, we later realized that it would be confusing in terms of comparison issues between the methods for consistent interpretations. Practical implications:Weibull distribution covers a wide class of non-normal processes due to its capability to yield a variety of distinct curves based on its parameters. Weibull distributions are known to have significantly different tail behaviors, which greatly affects the process capability. In quality and reliability applications, they are widely used for the analyses of failure data in order to understand how items are failing or failures being occurred. Many academicians prefer the estimation of long term variation for process capability calculations although Process Capability Indices (PCIs) C p and C pk are widely used in literature. On the other hand, in industry, especially in automotive industry, the PPIs P p and P pk are used for the second type of estimations.Originality/value: Performance comparisons are performed through generating Weibull data without subgroups and for this reason, process performance indices (PPIs) are executed for computing process capability rather than process capability indices (PCIs). Box plots, descriptive statistics, the root-mean-square deviation (RMSD), which is used as a measure of error, and a radar chart are utilized all together for evaluating the performances of the methods. In addition, the bias of the estimated values is important as the efficiency measured by the mean square error.In this regard, Relative Bias (RB) and the Relativ...

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Process capability indices for skewed populations

Cited by 55 publications

References 17 publications

Process Capability Index-Based Control Chart for Variables

Process Capability Index-Based Control Chart for Variables

Process capability index Cpk for monitoring the thermal performance in the distribution of refrigerated products

Comparing performances of clements, box-cox, Johnson methods with weibull distributions for assessing process capability

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