Application of the Non-Parametric Signals Test to a Company

Sampaio, Nilo Antônio S.; Mazza, Felipe Cury; De Siqueira, Sílvio Sérgio Silveira; Miranda Junior, João Ercio; De Abreu, Laura Dutra; De Lima, Rafael Martins

doi:10.24857/rgsa.v18n2-071

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…During the last century, statistics revolutionized science by presenting useful models that modernized the research process in the direction of better research parameters, making it possible toguide decision making in a wide variety of areas. Statistical methods were developed as a mixture of science and logic for the solution and investigation of problems in various areas of human knowledge (Abraão et al, 2024;da Motta Reis et al, 2023;Sampaio, Mazza, Sérgio, et al, 2024;A. C. P. da Silva et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Using Analysis of Variance and Tukey's Test to Compare Four Brands of Industrial Paint

Deus,

Carvalho,

Mazza

et al. 2024

RGSA

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Objective: The aim of this paper is to show the application of Analysis of Variance and Tukey's Test to compare four brands of paint used in a company's production. Theoretical framework: Analysis of Variance, or ANOVA, is a statistical method used to determine whether there are significant differences between the means of three or more independent groups. This technique was developed by the British statistician and geneticist Ronald Fisher at the beginning of the 20th century (Bosco v & Bispo, 2010). Method: Data was taken from a company in the South of Rio de Janeiro and a case study was carried out using Analysis of Variance and Tukey's test. Final Considerations: This result indicates that the hardness of the paint mixtures differs significantly. Some of the group averages are known to be different. Tukey's comparison results were used to formally test whether the difference between a pair of groups is statistically significant. It was found that Paint 4 has a higher hardness than the others. Implications of the research: The use cases of Analysis of Variance and Tukey's Test are multiplying in the scientific literature and are proving to be highly effective for processing data in a wide variety of areas. Originality/value: Despite being well-known statistical tools, Analysis of Variance and Tukey's Tests are only valid in cases where there are more than two types of samples in which the statistical assumptions have been confirmed.

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Section: Introductionmentioning

confidence: 99%

Using Analysis of Variance and Tukey's Test to Compare Four Brands of Industrial Paint

Deus,

Carvalho,

Mazza

et al. 2024

RGSA

View full text Add to dashboard Cite

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Using the Non-Homogeneous Poisson Process (Duane's Model) to Analyze the Number of Failures in Industrial Equipment

Borges,

Abreu,

Prates

et al. 2024

RGSA

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Objective: The aim of this paper is to show the application of Duane's Chart to analyze the time between failures in a company in the South of Rio de Janeiro. Theoretical framework: A Duane chart is a scatter plot of the cumulative failure rate versus time. Use a Duane chart to do the following: •Assess whether the data follows a power-law process or a homogeneous Poisson process. •Determine whether a repairable system is improving, getting worse or remaining stable. The fitted line on the Duane chart plots the best fitted line when the power-law process assumption is valid and the shape and scale are estimated using the least squares method. The Duane plot should be approximately linear if the power-law process or homogeneous Poisson process is appropriate. A negative slope shows an improvement in reliability, a positive slope shows a deterioration in reliability and no slope (a horizontal line) shows a stable system (Zanin et al., 2010). Method: Data was taken from a company in the South of Rio de Janeiro and a case study was carried out using Duane's Chart. Final Considerations: This result indicates that Duane's Model is a very viable option when the aim is to monitor the failure rate as a function of time to check whether a system is improving or not. In this specific Case Study, it is clear that there is a significant improvement in the system over time and that the work carried out in this company is being very effective in reducing and even eliminating failures in the long term. Implications of the research: The use cases of Duane's Chart are multiplying in scientific literature and are proving to be highly effective for interpreting data in the area of reliability. Originality/value: Despite being a well-known Statistical Tool, Duane's Chart has a specific application in monitoring the number of failures over time in a system.

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How to Perform a Statistical Analysis of Non-Destructive Degradation Data to Study Crack Growth in Wind Blades as a Function of the Number of Cycles

Vasconcelos,

Savi,

Prates

et al. 2024

RGSA

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Objective: The aim of this paper is to show the application of the Exponential Regression Model to study the failure time of a system over time. The data was taken from the paper (Wang et al., 2021). Theoretical framework: The linear regression model, where the response is associated with the explanatory variables by means of a linear model, is the best known. To formulate the model, it is necessary to specify a deterministic component and a random (stochastic) component. The exponential model should be used when it is assumed that risk is constant over time. Once the model has been specified, its parameters are estimated. In the absence of normal errors and especially in the presence of censoring, a more appropriate option is the maximum likelihood method. As the equations are non-linear in their parameters and do not have an analytical solution, it is necessary to use the Newton-Raphson numerical method. Due to the simplicity of the exponential regression model, few situations in practice are adequately adjusted by this model. The Weibull regression model is widely used in survival analysis (Bastos Lyra et al., 2008) Method: Data taken from the article (Wang et al., 2021) e foi utilizado a Regressão Exponencial para modelar os dados. Final Considerations: This result indicates that Exponential Regression is a very viable option when the aim is to monitor the number of cracks as a function of time to check whether a system will fail. In this specific Case Study, it is clear that one of the blades is better than the others and that there are some Probability Distribution models that are suitable for the model. Implications of the research: The use cases of Exponential Regression are more restricted in the scientific literature and because of this, this case study is interesting to show that this model is effective for treating data in the area of reliability. Originality/value: Despite being a well-known statistical tool, Exponential Regression has a specific application in monitoring the number of cracks over time in a system.

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Application of the Non-Parametric Signals Test to a Company

Cited by 3 publications

References 33 publications

Using Analysis of Variance and Tukey's Test to Compare Four Brands of Industrial Paint

Using Analysis of Variance and Tukey's Test to Compare Four Brands of Industrial Paint

Using the Non-Homogeneous Poisson Process (Duane's Model) to Analyze the Number of Failures in Industrial Equipment

How to Perform a Statistical Analysis of Non-Destructive Degradation Data to Study Crack Growth in Wind Blades as a Function of the Number of Cycles

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