Modeling quality control data using mixture of parametrical distributions
In this paper, we present a Bayesian analysis of a data set selected from a Brazilian food company. This data set represents the times taken for different quality control analysts to test manufactured products arriving at the company’s quality control department. The samples selected from each batch...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2013-06-01
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| Series: | International Journal of Industrial Engineering Computations |
| Subjects: | |
| Online Access: | http://www.growingscience.com/ijiec/Vol4/IJIEC_2013_11.pdf |
| _version_ | 1818956643044425728 |
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| author | Roberto Molina de Souza Claudio Luis Piratelli Jorge Alberto Achcar |
| author_facet | Roberto Molina de Souza Claudio Luis Piratelli Jorge Alberto Achcar |
| author_sort | Roberto Molina de Souza |
| collection | DOAJ |
| description | In this paper, we present a Bayesian analysis of a data set selected from a Brazilian food company. This data set represents the times taken for different quality control analysts to test manufactured products arriving at the company’s quality control department. The samples selected from each batch contain mixtures of different products, which may be submitted to quality testing taking different times. From preliminary analysis of the data, it was observed that the histograms presented two clusters, indicating a mixture of distributions. A mixture of parametrical distributions was thus assumed in the presence of a covariate in order to analyze the data set and to establish standards to be used by the company for the times taken by the analysts. Inferences and predictions are obtained using a Bayesian approach with standard existing Markov Chain Monte Carlo (MCMC) methods. |
| first_indexed | 2024-12-20T10:57:13Z |
| format | Article |
| id | doaj.art-7e95dae0a2cc49d1997c7f463d11933e |
| institution | Directory Open Access Journal |
| issn | 1923-2926 1923-2934 |
| language | English |
| last_indexed | 2024-12-20T10:57:13Z |
| publishDate | 2013-06-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Industrial Engineering Computations |
| spelling | doaj.art-7e95dae0a2cc49d1997c7f463d11933e2022-12-21T19:43:07ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342013-06-014341742610.5267/j.ijiec.2013.03.003Modeling quality control data using mixture of parametrical distributionsRoberto Molina de SouzaClaudio Luis PiratelliJorge Alberto AchcarIn this paper, we present a Bayesian analysis of a data set selected from a Brazilian food company. This data set represents the times taken for different quality control analysts to test manufactured products arriving at the company’s quality control department. The samples selected from each batch contain mixtures of different products, which may be submitted to quality testing taking different times. From preliminary analysis of the data, it was observed that the histograms presented two clusters, indicating a mixture of distributions. A mixture of parametrical distributions was thus assumed in the presence of a covariate in order to analyze the data set and to establish standards to be used by the company for the times taken by the analysts. Inferences and predictions are obtained using a Bayesian approach with standard existing Markov Chain Monte Carlo (MCMC) methods.http://www.growingscience.com/ijiec/Vol4/IJIEC_2013_11.pdfRegressionQuality control timesMixture modelsBayesian methodsMCMC methods |
| spellingShingle | Roberto Molina de Souza Claudio Luis Piratelli Jorge Alberto Achcar Modeling quality control data using mixture of parametrical distributions International Journal of Industrial Engineering Computations Regression Quality control times Mixture models Bayesian methods MCMC methods |
| title | Modeling quality control data using mixture of parametrical distributions |
| title_full | Modeling quality control data using mixture of parametrical distributions |
| title_fullStr | Modeling quality control data using mixture of parametrical distributions |
| title_full_unstemmed | Modeling quality control data using mixture of parametrical distributions |
| title_short | Modeling quality control data using mixture of parametrical distributions |
| title_sort | modeling quality control data using mixture of parametrical distributions |
| topic | Regression Quality control times Mixture models Bayesian methods MCMC methods |
| url | http://www.growingscience.com/ijiec/Vol4/IJIEC_2013_11.pdf |
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