Time truncated attribute control chart for generalized half-normal distribution and its application

Tripathi, Harsh; Saha, Mahendra; Tushaveera, Jitendra

doi:10.1007/s41872-022-00195-2

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…We explored the literature and did not find any study based on time truncated control chart for generalized Rayleigh distribution. In recent years, many researchers have developed control chart for Weibull distribution (Aslam and Jun, 2015;Alghamdi et al, 2017), Pareto distribution of second kind (Aslam et al, 2016a), Exponentiated half-logistic distribution (Rao, 2018), Dagum distribution (Gadde et al, 2019), Generalized half-normal distribution (Tripathi et al, 2022), log-logistic distribution (Rao and Paul, 2020), Rayleigh distribution (Adeoti and Rao, 2022), Exponentiated Fr echet distribution (Rosaiah et al, 2018), multivariate Poisson distribution (Chiu and Kuo, 2007), Birnbaum-Saunders distribution (Aslam et al, 2016b) and many more. Some other authors have done notable work such as: Aslam et al (2014), Lee Ho and Quinino (2013), Aslam (2019a) Baklizi and Ghannam (2022) developed several control charts.…”

Section: Related Work With Research Gapsmentioning

confidence: 99%

Time truncated attribute control chart for the generalized Rayleigh distributed quality characteristics and beyond

Saha,

Pareek,

Tripathi

et al. 2024

IJQRM

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Purpose First is to develop the time truncated median control chart for the Rayleigh distribution (RD) and generalized RD (GRD), respectively. Second is to evaluate the performance of the proposed attribute control chart which depends on the average run length (ARL) and third is to include real life examples for application purpose of the proposed attribute control chart.Design/methodology/approach (1) Select a random sample of size n from each subgroup from the production process and put them on a test for specified time t, where t = ? × µe. Then, count the numbers of failed items in each subgroup up to time t. (2) Step 2: Using np chart, define D = np, the number of failures, which also a random variable follows the Binomial distribution. It is better to use D = np chart rather than p chart because the authors are using number of failure rather than proportion of failure p. When the process is in control, then the parameters of the binomial distribution are n and p0, respectively. (3) Step 3: The process is said to be in control if LCL = D = UCL; otherwise, the process is said to be out of control. Hence, LCL and UCL for the proposed control chart.Findings From the findings, it is concluded that the GRD has smaller ARL values than the RD for specified values of parameters, which indicate that GRD performing well for out of control signal as compared to the RD.Research limitations/implications This developed control chart is applicable when real life situation coincide with RD and GRD.Social implications Researcher can directly use presented study and save consumers from accepting bad lot and also encourage producers to make good quality products so that society can take benefit from their products.Originality/value This article dealt with time truncated attribute median control chart for non-normal distributions, namely, the RD and GRD, respectively. The structure of the proposed control chart is developed based on median lifetime of the RD and GRD, respectively.

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Section: Related Work With Research Gapsmentioning

confidence: 99%

Time truncated attribute control chart for the generalized Rayleigh distributed quality characteristics and beyond

Saha,

Pareek,

Tripathi

et al. 2024

IJQRM

Self Cite

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A study of attribute control charts for censored lifetime data

Haq,

Woodall,

Steiner

2024

Quality Engineering

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Time Truncated Attribute Median Control Charts for Logistic-Exponential Process Distribution

Saha,

Pareek,

Maheshwari

et al. 2024

Stochastics and Quality Control

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In this article, time truncated attribute control chart is proposed for logistic-exponential distribution based on four acceptance sampling plans. The performance of the proposed control chart is evaluated in terms of average run length. Furthermore, the efficiency of the proposed attribute control chart is compared for all given acceptance sampling plans, viz., single sampling plan, repetitive sampling plan, multiple dependent state sampling plan and multiple dependent state repetitive sampling plan. Also, the application of the proposed control chart is illustrated by using real life example.

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Time truncated attribute control chart for generalized half-normal distribution and its application

Cited by 3 publications

References 14 publications

Time truncated attribute control chart for the generalized Rayleigh distributed quality characteristics and beyond

Time truncated attribute control chart for the generalized Rayleigh distributed quality characteristics and beyond

A study of attribute control charts for censored lifetime data

Time Truncated Attribute Median Control Charts for Logistic-Exponential Process Distribution

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