Engenharia da qualidade na perspectiva da estatística inferencial e do método AHP-TOPSIS-2N: uma proposta de melhoria numa indústria de bebidas

Considerando que a competitividade dos negócios é um elemento decisivo na busca de posicionamento do mercado, bem como de sobrevivência do negócio, a estratégia de se posicionar com custos sob controle, não impondo uma prática de preços extras para garantir a margem de contribuição e equilibrar o custo de fabricação. Este estudo objetivou, mediante o mapeamento do processo, identificar as variáveis críticas e entender a relação de causa-efeito entre elas. Assim, percebeu-se a importância da fundamentação da estatística descritiva, gráfica e inferencial na aplicação de um processo de envase de bebidas, onde têm-se dois aspectos: o volume envasado acima da especificação, incorrerá no alto custo de fabricação. Ao mesmo tempo em que se a respectiva embalagem apresentar volume abaixo do especificado, de acordo a legislação vigente, implicará em multas aplicadas por instituições de defesa do consumidor. Logo, percebeu-se a necessidade de estipular um método robusto a fim de garantir a precisão do processo de envase e que os fornecedores, dos itens críticos, fossem avaliados e ordenados sob critérios técnicos. Com isso, constatou-se a eficácia de uma abordagem estatística na identificação do problema, bem como a abordagem do método multicritério na avaliação dos fornecedores das peças de reposição.

David de Oliveira Costa Production Engineer, Master in Environmental Management from the Federal Institute of Pernambuco (IFPE – Brazil), postgraduate in Environmental Management, and MBA in Six Sigma and Quality Management. He works as a student researcher for the Master’s Program in Production Engineering at Universidade Federal Fluminense (UFF – Brazil) and develops his research with Multicriteria Analysis in line with corporate strategy. He is also a reviewer and referee for national and international journals: GEPROS, Online Production and Brazilian Journal of Operations & Production Management.

Carlos Francisco Simões Gomes Associate project manager, and researcher at the Center for Analysis of Naval Systems (CASNAV) from 1997 to 2007, he was Head of the Department of CASNAV, and later Deputy Director of this Center until 2008, when he left the active service of the Navy. Has experience in Administration, Production Engineering, Information Technology (IT), and Information Architecture, with emphasis on Risk Management, working mainly on the following topics: Multicriteria, Operations Research, Logistics, Project Management, Information Systems focusing on Accessibility and Usability, Decision Analysis, Analytical Methods applied to the solution of Brazilian business problems and Strategic Planning using IT. Speaker at UFRJ, UFPE, Candido Mendes, UFF – Volta Redonda, UVA and FGV, Escola de Guerra Naval and Escola Superior de Guerra. Vice President of SOBRAPO. Participated in 63 undergraduate, Master’s, Doctoral, and Doctoral Qualifying Exams; of 68 congresses and/or symposia, and national and/or international events. He has 34 articles published in national and international journals, and another 85 articles published in congresses, symposia, and national and international events. He has supervised 19 undergraduate monographs. Author of the books Management of the Supply Chain Integrated to Information Technology, Publisher CENGAGE LEARNING; and Managerial Decision Making – Multicriteria Approach (3rd Edition); Atlas Publisher. He participated as a member of the Brazilian delegation to the International Maritime Organization (UN body for the Oceans based in London) in the negotiations of the Ballast Water and Double Hull agreement, being both of them the author of the work that marked the Brazilian position. technical reviewer of journals: European Journal of Operational Research (EJOR); Operational Research; Management and Production; Production Magazine; Brazilian Journal of Operations and Production Management and Annals of Operations Research and Engevista.

Marcos dos Santos has over 800 articles published, it has a Scopus H-8 index. He held two post-docs, namely: one in Space Sciences and Technologies at the Instituto Tecnológico de Aeronáutica (ITA) and another in Production Engineering at the Universidade Federal Fluminense (UFF). He holds a Ph.D. in Production Engineering (from UFF) in the Research Line: Systems, Decision Support, and Logistics. Master in Production Engineering (from COPPE/UFRJ) in the Operational Research Line. He has a degree in Mathematics and is a Specialist in Mathematical Instrumentation (also from UFF). Coordinator of the 1st MBA in Operations Research and Decision Making in Brazil. Professor of the Postgraduate Program in Systems and Computing at the Instituto Militar de Engenharia (IME). Professor of Advanced Mathematics at the Computer Engineering graduation at IME. Permanent Professor of the Graduate Program in Production Engineering at UFF. MBA Professor in Data Science and Analytics at the University of São Paulo (USP). Professor of Corporate Governance and Organizational Excellence at University of Estácio de Sá (UNESA). Creator of several mathematical methods to support decision making (all published in international journals), including SAPEVO-M Method, ELECTRE-MOr Method, AHP-Gaussian Method, and PrOPPAGA Method.

Daniel Augusto de Moura Pereira Mechanical Production Engineer from the Federal University of Paraíba (2006), Specialist in Occupational Safety Engineering from the University Center of João Pessoa (2008), Master`s in Production Engineering from the Federal University of Paraíba (2009). Doctor in Quality of the Built Environment (2018) by PPGAU/UFPB. Adjunct Professor of the Production Engineering Course at CDSA – UFCG. Consultant in the areas of Production Management, Ergonomics and Occupational Health and Safety. Green Belt, Black Belt and Master Black Belt in Lean Six Sigma (2019). Judicial Expert in the sphere of Occupational Safety. Chief Executive Officer (CEO) of the Production Engineering Symposium (SIMEP)

Agrawal, N. (2019). A framework for Crosby’s quality principles using ISM and MICMAC approaches. The TQM Journal, 32(2), 305–330. https://doi.org/10.1108/TQM-03-2019-0085

Araujo, J. V. G. A., Santos, M., & Gomes, C. F. S. ([s.d.]). Método Multicritério de Apoio à Decisão AHP-TOPSIS-2N Aplicado em Licitações para Melhoria do Controle de Gastos Públicos.

Barbosa, H. M., Gomes, C. F. S., & Santos, M. dos. (2020). Aplicação do Método Híbrido AHP-TOPSIS-2N Para Ordenação da Execução de Furos de Alívio em Revestimentos de Poços de Petróleo Sob Risco De Colapso. Simpósio de Pesquisa Operacional e Logística da Marinha – Publicação Online. https://www.proceedings.blucher.com.br/article-details/aplicao-do-mtodo-hbrido-ahp-topsis-2n-para-ordenao-da-execuo-de-furos-de-alvio-em-revestimentos-de-poos-de-petrleo-sob-risco-de-colapso-34467

Bozza, G., Ruy, M., Santos, M., Moreira, M. Â., Rocha Junior, C. S., & Gomes, C. F. S. ([s.d.]). Three Decision Methods (3DM) Software Web.

British Standard – BS 6143-2: Guide to the Economics of Quality – Parte 2, 1990.

Costa, R., & Castro, FAS (2020). Métodos Estatísticos Adotados em Teses de Doutorado em Ciências do Movimento Humano: Um Estudo Descritivo. Revista Brasileira de Pós-Graduação , 16

Dharmalingam, S., Subramanian, R., & Somasundara Vinoth, K. (2010). Analysis of dry sliding friction and wear behavior of aluminum-alumina composites using Taguchi’s techniques. Journal of Composite Materials, 44(18), 2161–2177. https://doi.org/10.1177/0021998310365175

De Souza, L. P., Gomes, C. F. S., & De Barros, A. P. (2018). Implementation of new hybrid AHP–TOPSIS-2N Method In Sorting And Prioritizing Of An It CAPEX Project Portfolio. International Journal Of Information Technology & Decision Making, 17(04), 977–1005. https://doi.org/10.1142/s0219622018500207

Nascimento Maêda, S. M. (2021). Multi-criteria analysis applied to aircraft selection by Brazilian Navy. Production, 1–13.

Editora, F. (Org.). (2013). Falconi, Vicente C. Plano de Gerenciamento do Projeto.

Estatística Aplicada com Minitab. (2015). Estatística Aplicada com Minitab. Rio de Janeiro.

Francisco, M. G., Canciglieri Junior, O., & Sant’Anna, Â. M. O. (2020). Design for six sigma integrated product development reference model through systematic review. International Journal of Lean Six Sigma, 11(4), 767–795. https://doi.org/10.1108/IJLSS-05-2019-0052

Gomes, L., & Gomes, C. F. S. (2019). Princípios e métodos para a tomada de decisão: Enfoque multicritério. Atlas.

Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: methods and applications. Springer-Verlag.http://dx.doi. org/10.1007/978-3-642-48318-9

Ivandro, K., Marcelo Tomio, M., & Matheus Pereira, G. (2015). Como estimar o poder do teste mínimo e valores limites para o intervalo de confiança do data snooping. Boletim de Ciências Geodésicas, 21(1), 26–42. https://doi.org/10.1590/S1982-21702015000100003

Juran, J.M.(2000). Quality Control Handbook, 5th ed., McGraw-Hill, New York,.

Keki, B. (1996). Qualidade de classe mundial. Rio de Janeiro. Qualitymark.

Kong, X., Yang, J., & Hao, S. (2021). Reliability modeling-based tolerance design and process parameter analysis considering performance degradation. Reliability Engineering & System Safety, 207, 107343. https://doi.org/10.1016/j.ress.2020.107343

Krohling, R. A., & Pacheco, A. G. C. (2015). A-TOPSIS – an approach based on TOPSIS for ranking evolutionaryalgorithms. Procedia Computer Science, 55, 308–317. https://doi.org/10.1016/j.procs.2015.07.054

Larson, H. J. (1934). Introduction to probability theory and statistical inference. 2. ed. New York: John Wiley & Sons.

Morettin, L. G. (1974). Estatística Básica: Probabilidade e Inferência. In Pearson Larson, H. J. Introduction to probability theory and statistical inference. John Wiley & Sons.

Pyzdek, T., & Keller, P. (2011). Seis Sigma: guia do profissional, um guia completo para Green Belts, Black Belts e Gerentes em todos os níveis. Alta Books.

Pan, L. K., Wang, C. C., Wei, S. L., & Sher, H. F. (2007). Optimizing multiple quality characteristics via Taguchimethod-based Grey analysis. Journal of Materials Processing Technology, 182, 107–116.

Prates, G. A. (2015). Robustness Optimization in Physics Sustainable -Mechanic- Based Design of Taguchi Methods for Experimental Development of Products and Processes. Espacios, 36(23).

Rotondaro, R. G. (2008). Seis Sigma: estratégia gerencial para a melhoria de processos, produtos e serviços. Atlas.

Sanchez-Marquez, R., & Jabaloyes Vivas, J. (2021). Building a Cpk control chart – A novel and practical method for practitioners. Computers & Industrial Engineering, 158, 107428. https://doi.org/10.1016/J.CIE.2021.107428

Santos, Marcos. (2021). Fundamentos do Método Multicritério Híbrido AHP-TOPSIS-2N.

[Vídeo aula, lecionada na UFF, IME]. https://www.youtube.com/watch?v=akXQyTXiCdI.

Taguchi, G. (1990). Introduction to Quality Engineering. Asian Productivity Organization.

Taguchi, G. (1986) Introduction to Quality Engineering: Designing Quality into Products and Processes. Asian Productivity Organization, Tokyo.

Taguchi, G., Parr, W. C. (1989). Introduction to quality engineering: Designing quality into products and processes. Technometrics: a journal of statistics for the physical, chemical, and engineering sciences, 31(2), 255. https://doi.org/10.2307/1268824

Weir, B. S., & Cockerham, C. C. (1984). Estimating F -Statistics For The Analysis Of Population Structure. Evolution, 38(6), 1358–1370. https://doi.org/10.1111/j.1558-5646.1984.tb05657.x

AHP-TOPSIS-2N, Custos industriais, Método de Taguchi