A Modified Process Capability Index Using Loss Function Concept

Eslamipoor, Reza; Hosseini-Nasab, Hasan

doi:10.1002/qre.1761

Cited by 5 publications

(4 citation statements)

References 8 publications

(12 reference statements)

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“…For example, the first process capability index P C is first introduced by Juran in reference [3]. Then other PCIs: pk C , pm C , pmk C are proposed respectively [4][5][6]. The study and applications of PCIs have drawn great attention.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Test for Lifetime Performance Index of Exponential Distribution under Symmetric Entropy Loss Function

Fan¹

2018

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The task of this paper is to estimate the lifetime performance index of Exponential distribution. A Bayesian test procedure is established under symmetric entropy loss function. Firstly, Bayesian estimation of life performance index is obtained, then a Bayesian test procedure for lifetime performance index is proposed. Finally, an applied example is used to illustrate the effectiveness of the proposed test method.

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Section: Introductionmentioning

confidence: 99%

Bayesian Test for Lifetime Performance Index of Exponential Distribution under Symmetric Entropy Loss Function

Fan¹

2018

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“…Further on, Kane [12] introduces some applications of these indices and discusses how to evaluate univariate production processes using these indicators. Other univariate PCIs were also introduced in the literature [13] [20] but only the C p and the C pk indices are widely adopted by the industry. Several multivariate PCIs have been recently introduced in the literature to describe the capability of multivariate production processes in a global way [21] Taking a look at the existing literature in the eld of process capability analysis we can see that many authors are introducing new multivariate PCIs in the literature [33], but there is a lack of research on the benets of using multivariate PCIs in the industry.…”

Section: Introductionmentioning

confidence: 99%

Monitoring high complex production processes using process capability indices

de-Felipe

Benedito

2017

Int J Adv Manuf Technol

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The increasing demand and the globalization of the market are leading to increasing levels of quality in production processes, and thus, nowadays multiple product characteristics must be tested because they are considered critical. In this context, decision makers are forced to interpret a huge amount of quality indicators, when monitoring production processes. This fact leads to a misunderstanding as a result of information overload. The aim of this paper is to help practitioners when monitoring the capability of processes with a huge amount of product characteristics. We propose a methodology that reduces the amount of data in capability analysis by structuring hierarchically the multiple quality indicators obtained in the quality tests. The proposed methodology may help practitioners and decision makers of the industry in three aspects of statistical process monitoring: To identify the part of a complex production process that presents capability problems; to detect worsening over the time in multivariate production processes; and to compare similar production processes. Some illustrative examples based on dierent kinds of production processes are discussed in order to illustrate the methodology. A case of study based on a real production process of the automotive industry is analyzed using the proposed methodology. We conclude that the proposed methodology reduces the necessary amount of data in capability analysis; and thus, that it provides an added value of great interest for managers and decision makers.

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“…In fact, the offline quality approach tries to improve quality before the production stage, i.e. in the design stage (Eslamipoor and Hosseini-nasab, 2015). Contributing to the offline quality, Taguchi proposed a two-step optimization procedure (TSOP) which minimizes two different effects, namely, dispersion and location effects.…”

Section: Introductionmentioning

confidence: 99%

Proposing a two-criterion quality loss function using critical process capability indices

Geramian

Shahin

Bandarrigian

et al. 2017

BIJ

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Purpose Average quadratic quality loss function (QQLF) measures quality of a given process using mean shift from its target value and variance. While it has a target parameter for the mean, it lacks a target for the variance revisable for counting any progress of the process across different quality levels, above/below the standard level; thus, it appears too general. Hence, in this research, it was initially supposed that all processes are located at two possible quality spaces, above/below the standard level. The purpose of this paper is to propose a two-criterion QQLF, in which each criterion is specifically proper to one of the quality spaces. Design/methodology/approach Since 1.33 is a literarily standard or satisfactory value for two most important process capability indices Cp and Cpk, its upper/lower spaces are assumed as high-/low-quality spaces. Then the indices are integrated into traditional QQLF, of type nominal the best (NTB), to develop a two-criterion QQLF, in which each criterion is more suitable for each quality space. These two criteria have also been innovatively embedded in the plan-do-check-act (PDCA) cycle to help continuous improvement. Finally, the proposed function has been examined in comparison with the traditional one in Feiz Hospital in the province of Isfahan, Iran. Findings Results indicate that the internal process of the studied case is placed on the lower quality space. So the first criterion of revised QQLF gives a more relevant evaluation for that process, compared with the traditional function. Moreover, this study has embedded both proposed criteria in the PDCA cycle as well. Research limitations/implications Formulating the two-criterion QQLF only for observations of normal and symmetric distributions, and offering it solely for NTB characteristics are limitations of this study. Practical implications Two more relevant quality loss criteria have been formulated for each process (service or manufacturing). However, in order to show the comprehensiveness of the proposed method even in service institutes, emergency function of Feiz Hospital has been examined. Originality/value The traditional loss function of type NTB merely and implicitly targets zero defect for variance. In fact, it calculates quality loss of all processes placed on different quality spaces using a same measure. This study, however, provides a practitioner with opportunity of targeting excellent or satisfactory targets.

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A Modified Process Capability Index Using Loss Function Concept

Cited by 5 publications

References 8 publications

Bayesian Test for Lifetime Performance Index of Exponential Distribution under Symmetric Entropy Loss Function

Bayesian Test for Lifetime Performance Index of Exponential Distribution under Symmetric Entropy Loss Function

Monitoring high complex production processes using process capability indices

Proposing a two-criterion quality loss function using critical process capability indices

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