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The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil

Received: 20 December 2014     Accepted: 6 January 2015     Published: 19 January 2015
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Abstract

Brazil is one of the world´s leaders in the production and processing of cashew chestnut and 100% of these cashew chestnut processing industries are located in the northeastern region of the country. For the maintenance and enlargement of the cashew chestnut market it is necessary to have a guarantee of the product quality by means of controlling the productive process. In this case, the application of DOE (Design of Experiments) is suggested in the beneficiation process of the cashew chestnut, notably in the stage of decortication, where the chestnuts are being cut in bands, by a mechanical means. For this process, a fractionated factorial experiment planning was used and evaluated response variable in the experiment was the quality of the almond in the final stage of production, measured by the percentage of whole almonds after the separation from the barks. The chosen process factors were the almonds size, the humidification of the environment, the temperature of the environment before the decorticator and the velocity of the decorticator. At the end of the experiment, it was observed that DOE showed to be an applicable tool that indicates which factors showed to be more influential, as well as, their levels of adjustment. It was observed that the variables related to the size of the almonds, the velocity in decortication are the influential factors of production in this process, apart from a strong noise being identified in this process, observed by the strong variance in the experiment data, especially that of the response variable.

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 1)
DOI 10.11648/j.ajtas.20150401.12
Page(s) 6-14
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Design of Experiments, Fractionated Factorial Planning, Beneficiation of the Cashew Chestnut

References
[1] SILVA, S. F. C et al. Implantação do controle estatístico de processos em uma indústria de beneficiamento de castanhas de caju. XXXII Encontro Nacional de Engenharia de Producão. Bento Gonçalves, RS, Brasil, 2012.
[2] SEBRAE, available em: , acessado em 02 de janeiro de 2014.
[3] CAVAZZUTI, M. Optimization Methods: from theory to Design, Springer, Verlag Berlin Heidelberg, 2013.
[4] TOSELLO, G. et al. Study of process parameters effect on the filling phase of micro-injection moulding using weld lines as flow markers. Int J Adv Manuf Technol. 47:81–97. 2010.
[5] ABELLAN-NEBOT, Jose Vicente e SUBIRÓN, Fernando Romero. A review of machining monitoring systems based on artificial intelligence process models. Int J Adv Manuf Technol. 47: 237–257. 2010.
[6] MONTGOMERY, D. C. Design and analysis of experiments. 6th edition. Arizona: John Wiley & Sons, Inc., 2005.
[7] PALANISAMY et al. Prediction of tool wear using regression and ANN models in end-milling operation. Int J Adv Manuf Technol 37:29–41. 2007.
[8] BESSERIS, George J. Profiling effects in industrial data mining by non-parametric DOE methods: An application on screening check weighing systems in packaging operations. European Journal of Operational Research. 147–161. 2012.
[9] ATKINSON, A. C., et al. Optimum Experimental Designs, with SAS. Oxford: Oxford University Press. 2007.
[10] BELL, G. H. ET AL. A. Plackett-Burman Experiment to Increase Supermarket Sales of a National Magazine. Interfaces. V. 39, n. 2, p. 145–158. 2009.
[11] LIMA, V. B. S.; BALESTRASSI, P. P.; PAIVA, A. P. Otimização do desempenho de amplificadores de radio frequência banda larga: uma abordagem experimental, Produção, v. 21, n. 1, p. 118-131, jan/mar, 2011.
[12] GRANATO, D.; BRANCO, G. F.; CALADO, V. M. A. Experimental design and application of response surface methodology for process modelling and optimization: A review, Food Research International, v.1, p. 0-14, 2011.
[13] GENTILINI, M. M. Otimização das características da qualidade brix e carbonação no processo de fabricação de refrigerantes através da utilização de projeto de experimentos. XXXI Encontro Nacional de Engenharia de Producão. Belo Horizonte, MG, Brasil, 2011.
[14] ANTONY, J. et al. Design of experiments for non-manufacturing processes: benefits, challenges and some examples. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, pp. 2078-2087, 2011.
[15] TONG, Lee-Ing et al. Determining the optimal re-sampling strategy for a classification model with imbalanced data using design of experiments and response surface methodologies. Expert Systems with Applications. 4222–4227. 2011.
[16] GOUJOT, Daniel.; MEYER, Xuân.; COURTOIS, Francis. Identification of a rice drying model with an improved sequential optimal design of experiments. Journal of Process Control. 22 (2012) 95– 107.
[17] NANDAKUMAR, Vivek. BISHOP, Daniel. ALONAS, Eric. LABELLE, Jeffrey. JOSHI, Lokesh. ALFORD, Terry L. A Low-Cost Electrochemical Biosensor for Rapid Bacterial Detection. IEEE Sensors Journal, v. 11, n. 1, pp. 210 - 216, 2011.
[18] FEKETE, Veronika. DECONINCK, Eric. BOLLE, Fabien. Van LOCO, Joris. Modelling aluminium leaching into food from different foodware materials with multi-level factorial design of experiments. Food Additives and Contaminants. Vol. 29, No. 8, pp. 1322–1333, August, 2012.
[19] MERZ, J. Zorn, BURGHOFF. H. and, SCHEMBECKER, G. Purification of a fungal cutinase by adsorptive bubble separation: A statistical approach. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 382, 2011.
[20] GURUNATHAN, Baskar. SAHADEVAN, Renganathan. Design of Experiments and Artificial Neural Network Linked Genetic Algorithm for Modeling and Optimization of L-asparaginase Production by Aspergillus terreus MTCC 1782. Biotechnology and Bioprocess Engineering. 16: 50-58 2011.
[21] SOUZA, H. J. C. de; MOYSES, C. B. ; PONTES, Fabrício J. ; DUARTE, Roberto N.; SANCHES DA SILVA, Carlos Eduardo ; ALBERTO, Fernando Lopes ; FERREIRA, Ubirajara R. ; SILVA, M. B. . Molecular Assay optimized by Taguchi Experimental Design Method for Venous Thromboembolism Investigation. Molecular and Cellular Probes. v. 25, p. 1-8, 2011.
[22] LIAO, Hsin-Te. SHIE, Jie-Ren. YANG, Yung-Kuang. Applications of Taguchi and design of experiments methods in optimization of chemical mechanical polishing process parameters. International Journal Advanced Manufacture Technology 38:674–682, 2008.
[23] KARNIK, S. R.; GAITONDE, V. N.; DAVIM, J. P. A comparative study of the ANN and RSM modeling approaches for predicting burr size in drilling. International Journal of Advanced Manufacture Technology 38:868–883. 2008.
[24] KIM, Hong Seok. A combined FEA and design of experiments approach for the design and analysis of warm forming of aluminum sheet alloys. International Journal of Advanced Manufacture Technology 51:1–14, 2010.
[25] PALANISAMY, P. RAJENDRAN, I. SHANMUGASUNDARAM, S. Prediction of tool wear using regression and ANN models in end-milling operation. International Journal on Advanced Manufacture Technology 37:29–41.2008.
[26] HARIDY, S. GOUDA, S. A. WU, Z. An integrated framework of statistical process control and design of experiments for optimizing wire electrochemical turning process. International Journal Advanced Manufacture Technology, 53:191–207, 2011.
[27] PAWADE, Raju Shrihari. JOSHI, Suhas S. Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA). International Journal Advanced Manufacture Technology 56:47–62. 2011.
[28] PIMENTA, Cristie Diego. SILVA, Messias Borges. RIBEIRO, Rosinei Batista. CLARO, Fernando Antonio Elias. Planejamento de experimentos em blocos aplicado às propriedades mecânicas de arames de aço para molas. Revista Produção. 2014.
[29] SILVA, S. F. C et al. Implantação do controle estatístico de processos em uma indústria de beneficiamento de castanhas de caju. XXXII Encontro Nacional de Engenharia de Producão. Bento Gonçalves, RS, Brasil, 2012.
[30] GUIMARÃES, Oswaldo Luiz Cobra ; VILELA FILHO, Darcy Nunes; Siqueira, A.F.; IZÁRIO FILHO, Hélcio José; SILVA, M. B.. Optimization of the azo dyes decoloration process through neural networks: Determination of the H2O2 addition critical point. Chemical Engineering Journal, v. 141, p. 35-41, 2008.
[31] GUIMARÃES, Oswaldo Luiz Cobra ; SILVA, M. B. . Hybrid Neural Model for decoloration by UV/H2O2 involving process variables and structural parameters characteristics to azo dyes. Chemical Engineering and Processing. Holanda, n 46, pp. 45-51, 2007.
[32] PONTES F. J.; FERREIRA, João Roberto; SILVA, M. B.; PAIVA, A. P.; BALESTRASSI, Pedro Paulo. Artificial neural networks for machining processes surface roughness modeling. International Journal of Advanced Manufacturing Technology, vol 49, p. 879-902, 2010.
[33] MOUTTA, R. O. ; CHANDEL, Anuj K. ; RODRIGUES, R. C. L. B. ; SILVA, M. B. ; ROCHA, G. J. M. ; SILVA, S. S. . Statistical Optimization of Sugarcane Leaves Hydrolysis into Simple Sugars by Dilute Sulfuric Acid Catalyzed Process. Sugar Tech, v. 14, p. 1-8, 2012.
[34] RIBEIRO JÚNIOR, Hugo J.; MOTA, Rodrigo Luiz Mendes.; LEME, Rafael Coradi.; SANTOS, Paulo Eduardo Steele. Ensaios Plackett-Burman para identificação de elementos de custo tarifário de energia elétrica. Anais do XXXIII Encontro Nacional de Engenharia de Produção, 2013.
[35] LAVOIE, P. GHARBI, A. KENNE, J.P. A comparative study of pull control mechanisms for unreliable homogenous transfer lines. International Journal of Production Economics. n 124, pp. 241–251. 2010.
[36] BARROS NETO, B.; SCARMINIO, I. S.; BRUNS, R. E. Como fazer experimentos: Pesquisa e Desenvolvimento na Ciência e na Indústria, 3ª edição, editora Unicamp, 480 p. 2007.
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    Miriam Karla Rocha, Liane Márcia Freitas Silva, Alexandre José de Oliveira, André Lucena Duarte, Adrícia Fonseca Mendes, et al. (2015). The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil. American Journal of Theoretical and Applied Statistics, 4(1), 6-14. https://doi.org/10.11648/j.ajtas.20150401.12

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    ACS Style

    Miriam Karla Rocha; Liane Márcia Freitas Silva; Alexandre José de Oliveira; André Lucena Duarte; Adrícia Fonseca Mendes, et al. The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil. Am. J. Theor. Appl. Stat. 2015, 4(1), 6-14. doi: 10.11648/j.ajtas.20150401.12

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    AMA Style

    Miriam Karla Rocha, Liane Márcia Freitas Silva, Alexandre José de Oliveira, André Lucena Duarte, Adrícia Fonseca Mendes, et al. The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil. Am J Theor Appl Stat. 2015;4(1):6-14. doi: 10.11648/j.ajtas.20150401.12

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  • @article{10.11648/j.ajtas.20150401.12,
      author = {Miriam Karla Rocha and Liane Márcia Freitas Silva and Alexandre José de Oliveira and André Lucena Duarte and Adrícia Fonseca Mendes and Messias Borges Silva},
      title = {The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {1},
      pages = {6-14},
      doi = {10.11648/j.ajtas.20150401.12},
      url = {https://doi.org/10.11648/j.ajtas.20150401.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150401.12},
      abstract = {Brazil is one of the world´s leaders in the production and processing of cashew chestnut and 100% of these cashew chestnut processing industries are located in the northeastern region of the country. For the maintenance and enlargement of the cashew chestnut market it is necessary to have a guarantee of the product quality by means of controlling the productive process. In this case, the application of DOE (Design of Experiments) is suggested in the beneficiation process of the cashew chestnut, notably in the stage of decortication, where the chestnuts are being cut in bands, by a mechanical means. For this process, a fractionated factorial experiment planning was used and evaluated response variable in the experiment was the quality of the almond in the final stage of production, measured by the percentage of whole almonds after the separation from the barks. The chosen process factors were the almonds size, the humidification of the environment, the temperature of the environment before the decorticator and the velocity of the decorticator. At the end of the experiment, it was observed that DOE showed to be an applicable tool that indicates which factors showed to be more influential, as well as, their levels of adjustment. It was observed that the variables related to the size of the almonds, the velocity in decortication are the influential factors of production in this process, apart from a strong noise being identified in this process, observed by the strong variance in the experiment data, especially that of the response variable.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazil
    AU  - Miriam Karla Rocha
    AU  - Liane Márcia Freitas Silva
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    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
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    AB  - Brazil is one of the world´s leaders in the production and processing of cashew chestnut and 100% of these cashew chestnut processing industries are located in the northeastern region of the country. For the maintenance and enlargement of the cashew chestnut market it is necessary to have a guarantee of the product quality by means of controlling the productive process. In this case, the application of DOE (Design of Experiments) is suggested in the beneficiation process of the cashew chestnut, notably in the stage of decortication, where the chestnuts are being cut in bands, by a mechanical means. For this process, a fractionated factorial experiment planning was used and evaluated response variable in the experiment was the quality of the almond in the final stage of production, measured by the percentage of whole almonds after the separation from the barks. The chosen process factors were the almonds size, the humidification of the environment, the temperature of the environment before the decorticator and the velocity of the decorticator. At the end of the experiment, it was observed that DOE showed to be an applicable tool that indicates which factors showed to be more influential, as well as, their levels of adjustment. It was observed that the variables related to the size of the almonds, the velocity in decortication are the influential factors of production in this process, apart from a strong noise being identified in this process, observed by the strong variance in the experiment data, especially that of the response variable.
    VL  - 4
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Author Information
  • Federal Rural University of Semi-Arid – UFERSA, Department of Environmental Sciences and Technological – DCAT, East Campus, Production Engineering, Mossoró – RN, Brazil

  • Paulista State University, Pos-graduate Program of Mechanical Engineering, Engineering Faculty of Guaratinguetá Campus - UNESP, Guaratinguetá - SP, Brazil

  • Federal Rural University of Semi-Arid – UFERSA, Department of Environmental Sciences and Technological – DCAT, East Campus, Production Engineering, Mossoró – RN, Brazil

  • Federal Rural University of Semi-Arid – UFERSA, Department of Environmental Sciences and Technological – DCAT, East Campus, Production Engineering, Mossoró – RN, Brazil

  • Federal Rural University of Semi-Arid – UFERSA, Department of Environmental Sciences and Technological – DCAT, East Campus, Production Engineering, Mossoró – RN, Brazil

  • Universidade Estadual Paulista, Guaratinguetá, Department of Chemical Engineering, School of Engineering of Lorena EEL, S?o Paulo University USP, Lorena, Brazil

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