A transformation technique to estimate the process capability index for non-normal processes

Hosseinifard, Zahra; Abbasi, Babak; Ahmad, Shafiq; Abdollahian, Mali

doi:10.1007/s00170-008-1376-x

Cited by 35 publications

(25 citation statements)

References 12 publications

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“…In cases where a normal distribution is not observed, data is transformed using the Box-Cox method [55], as recommended by Hosseinifard et al [56]. To do this, each individual value from the dataset, y i , is raised to the power of λ, which is found by searching for the optimum value between -5 and 5 to achieve normality according to A 2 , excluding zero where the natural logarithm of the dataset is taken.…”

Section: Experimental Data Analysismentioning

confidence: 99%

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Barnfather

Goodfellow

Abram

2017

Int J Adv Manuf Technol

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Portable robotic machine tools potentially allow feature machining processes to be brought to large parts in various industries, creating an opportunity for capital expenditure and operating cost reduction. However, robots lack the machining capability of conventional equipment, which ultimately results in dimensional errors in parts. This work showcases a low-cost hexapod-based robotic machine tool and presents experimental research conducted to investigate how the widely researched robotic machining challenges, e.g. structural dynamics and kinematics, translate to achievable tolerance ranges in real-world production to highlight currently feasible applications and provide a context for considering technology improvements. Machining trials assess the total dimensional errors in the final part over multiple geometries. A key finding is error variation which is in the sub-millimetre range, although, in some cases, upper tolerance limits < 100 μm are achieved. Practical challenges are also noted. Most significantly, it is demonstrated that dimensional machining error is mainly systematic in nature and therefore that the total error can be dramatically reduced with in situ measurement and compensation. Potential is therefore found to achieve a flexible, highperformance robotic machining capability despite complex and diverse underlying scientific challenges. Overall, the work presented highlights achievable tolerances in lowcost robotic machining and opportunities for improvement, also providing a practical benchmark useful for process selection.

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Section: Experimental Data Analysismentioning

confidence: 99%

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Barnfather

Goodfellow

Abram

2017

Int J Adv Manuf Technol

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“…A diferencia de otros trabajos realizados como el de Hosseinifard et al [11], en donde se hace comparación entre los métodos de transformaciones y los de ajuste de distribución de datos; el de Ahmad y Abdollahian [10], donde se compara los métodos de Clements, Burr y BoxCox, los autores del presente trabajo presentan una comparación más completa.…”

Section: Metodología De Comparaciónunclassified

“…Mediante estudios de simulación comparativos, Ahmad y Abdollahian recomiendan el uso de las distribuciones de Burr XII [10], mientras que Hosseinifard et al proponen el método de transformaciones de potencia como el más adecuado [11].…”

Section: Introductionunclassified

Metodología Para La Estimación De Índices De Capacidad en Procesos Para Datos No Normales

Montalván¹,

Romero²,

Ortiz³

et al. 2017

TECNIA

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“…The alternate approach is to use non-normal percentiles to calculate the PCI. The latter approach is not easy to implement and a deviation in estimating the distribution of the process may affect the efficacy of the estimated PCI (Hosseinifard et al, 2009).…”

Section: Process Capability Analysis (Pca)mentioning

confidence: 99%

“…Weibull distributions are known to have significantly different tail behaviours, which greatly affects the process capability. Hosseinifard, Abbasi, Ahmad and Abdollahian (2009) assessed the efficacy of the root transformation technique by conducting a simulation study using gamma, Weibull, and beta distributions. The root transformation technique is used to estimate the PCI for each set of simulated data.…”

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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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A transformation technique to estimate the process capability index for non-normal processes

Cited by 35 publications

References 12 publications

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Metodología Para La Estimación De Índices De Capacidad en Procesos Para Datos No Normales

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

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