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Evaluating the Statistical Process Control Data Acquisition System in a Heat Exchanger Factory

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Advances in Manufacturing III (MANUFACTURING 2022)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

Manufacturers of Heating Ventilation and Air Conditioning systems in Brazil are experiencing several challenges to increase competitiveness of their operations, considering the world class companies which are continuously improving their products and processes to deliver better quality products with lower costs. To achieve this target, new opportunities for improvements in management and operation system are welcome. This paper evaluates the statistical process control data acquisition system in a company in Manaus Industrial Zone for heat exchanger manufacturing, by using BPMN for Process Mapping at current state. Following the mission of Industry 4.0, options for improvements were proposed for a new future state, considering quality improvements and resources reduction. The analysis brought process improvements, for instance increased speed of data analysis time, regarding the corrective and preventive actions taken in the production system, and its influences in reducing the failure rate of products due to leakage rate, besides the analysis of the failure rate of product performance, and the reduction of resources used to collect process data.

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References

  1. Sarti, F., Hiratuka, C.: Desempenho recente da indústria brasileira no contexto de mudanças estruturais domésticas e globais, Para além da política econômica, pp. 127–170 (2018)

    Google Scholar 

  2. Bogoviz, A.V., Osipov, V.S., Chistyakova, M.K., Borisov, M.Y.: Comparative analysis of formation of industry 4.0 in developed and developing countries. In: Popkova, E.G., Ragulina, Y.V., Bogoviz, A.V. (eds.) Industry 4.0: Industrial Revolution of the 21st Century. SSDC, vol. 169, pp. 155–164. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94310-7_15

    Chapter  Google Scholar 

  3. Sakurai, R., Zuchi, J.D.: As revoluções industriais até a Industria 4.0. Rev. Interface Tecnológica 15(2), 480–491 (2018)

    Google Scholar 

  4. Fernandes, N.: Economic effects of coronavirus outbreak (COVID-19) on the world economy. Nuno Fernandes Full Professor of Finance IESE Business School Spain, SSRN Electron. Journal, ISSN 1556-5068, Elsevier BV, pp. 0–29 (2020)

    Google Scholar 

  5. Lizarelli, F.L., Bessi, N.C., Oprime, P.C., Amaral, R.M., Chakraborti, S.: A bibliometric analysis of 50 years of worldwide research on statistical process control. Gestão Produção 23(4), 853–870 (2016)

    Article  Google Scholar 

  6. Petrovic, S., Milosavljevic, Sajic, L.: Rapid evaluation of maintenance process using statistical process control and simulation Int. J. Simul. Model. 17, 119–132 (2018)

    Google Scholar 

  7. Gibbs, L., Shea, T.: The Power of Two The Power of Two: Combining Lean Six Sigma and BPM (2007)

    Google Scholar 

  8. Antosz, K., Chandima Ratnayake, R.M.: Machinery classification and prioritization: empirical models and AHP based approach for effective preventive maintenance. In: IEEE International Conference on Industrial Engineering and Engineering Management, art. no. 7798104, pp. 1380–1386 (2016). https://doi.org/10.1109/IEEM.2016.7798104

  9. Jasiulewicz–Kaczmarek, M., Antosz, K., Żywica, P., Mazurkiewicz, D., Sun, B., Ren, Y.: Framework of machine criticality assessment with criteria interactions. Eksploatacja i Niezawodnosc 23(2), 207–220 (2016). https://doi.org/10.17531/ein.2021.2.1

  10. Coughlan, P., Coghlan, D.: Action research for operations management. Int. J. Oper. Prod. Manag. 22(2), 220–240 (2002). https://doi.org/10.1108/01443570210417515

    Article  Google Scholar 

  11. ASHRAE Thermal Environmental Conditions for Human Occupancy, ASHRAE Stand., no. 55 (2003)

    Google Scholar 

  12. Abrava, Recomendação Normativa ABRAVA RN 03 - 2003 - Sistemas de Condicionamento de ar para conforto Parâmetros de Conforto Termico (2003)

    Google Scholar 

  13. Moran, M., Shapiro, H., Munson, B., DeWitt, D.: Introdução à Engenharia de Sistemas Termicos: termodinâmica, mecânica dos fluidos e transferencia de calor, 1st ed. Grupo Gen-LTC, Rio de Janeiro (2011)

    Google Scholar 

  14. World Economic Forum: Deep shift: technology tipping points and societal impact World Econ. Forum, no. September, pp. 1–44 (2015)

    Google Scholar 

  15. Sarfraz, M.: Intelligent Computer Vision and Image Processing: Innovation, Application, and Design. IGI Global (2013)

    Google Scholar 

  16. Gonzalez, R., Woods, R., Eddins, S.: Digital Image Processing, 3rd edn. Gatesmark Publishing, Knoxville (2009)

    Google Scholar 

  17. Ivanov, V., Pavlenko, I., Kuric, I., Kosov, M.: Mathematical modeling and numerical simulation of fixtures for fork-type parts manufacturing. In: Knapčíková, L., Balog, M. (eds.) Industry 4.0: Trends in Management of Intelligent Manufacturing Systems. EICC, pp. 133–142. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14011-3_12

    Chapter  Google Scholar 

  18. Varela, M.L., Putnik, G.D., Manupati, V.K., Rajyalakshmi, G., Trojanowska, J., Machado, J.: Collaborative manufacturing based on cloud, and on other I4. 0 oriented principles and technologies: a systematic literature review and reflections. Manag. Prod. Eng. Rev. 9 (2018). https://doi.org/10.24425/119538

  19. Ferreira, L., et al.: Framework for collaborative practices platforms for humans and machines in industry 4.0 oriented smart and sustainable manufacturing environments. In: Manupati, V.K., Goran, D.P., Rocha, M.L. (eds.) Smart and Sustainable Manufacturing Systems for Industry 4.0. CRC Press, Taylor & Francis Group, Boca Raton (2022, in Press)

    Google Scholar 

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Acknowledgement

This work has been supported by national funds through FCT – Fundação para a Ciência e Tecnologia within the project references: UIDB/00319/2020, EXPL/EME-SIS/1224/2021, and UID/CEC/00319/2019.

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Authors and Affiliations

  1. Department of Production and Systems, Universidade do Minho, Guimarães, Portugal

    Diogo Costa, Leonilde Varela & Goran Putnik

  2. Department of Information Systems, Universidade do Minho, Guimarães, Portugal

    Vaibhav Shah

  3. Department of Mechanical Engineering, Universidade do Minho, Guimarães, Portugal

    Caetano Monteiro & José Machado

  4. ALGORITMI Research Center, Universidade do Minho, Guimarães, Portugal

    Vaibhav Shah, Leonilde Varela, Caetano Monteiro & Goran Putnik

  5. MEtRICs Research Center, Universidade do Minho, Guimarães, Portugal

    José Machado

Authors
  1. Diogo Costa
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  2. Vaibhav Shah
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  3. Leonilde Varela
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  4. Caetano Monteiro
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  5. Goran Putnik
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  6. José Machado
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Corresponding author

Correspondence to Diogo Costa .

Editor information

Editors and Affiliations

  1. Department of Production Engineering, Poznan University of Technology, Poznan, Poland

    Adam Hamrol

  2. Production Engineering Department, Poznan University of Technology, Poznan, Poland

    Marta Grabowska

  3. Faculty of Organizational Sciences, University of Maribor, Kranj, Slovenia

    Damjan Maletič

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Costa, D., Shah, V., Varela, L., Monteiro, C., Putnik, G., Machado, J. (2022). Evaluating the Statistical Process Control Data Acquisition System in a Heat Exchanger Factory. In: Hamrol, A., Grabowska, M., Maletič, D. (eds) Advances in Manufacturing III. MANUFACTURING 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-00218-2_10

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  • DOI: https://doi.org/10.1007/978-3-031-00218-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-00166-6

  • Online ISBN: 978-3-031-00218-2

  • eBook Packages: EngineeringEngineering (R0)

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