Statistical analysis of manufacturing system complexity
Given the dynamism of the markets and the economic growth, nowadays companies must look for mechanisms that allow them to develop new strategies and compete successfully. The objective of this work is to develop a statistical analysis of the complexity of a manufacturing system. The methodological a...
- Autores:
-
Herrera Vidal, Germán
Coronado-Hernandez, Jairo R.
Minnaard, Claudia
Gustavo, Gatica
Schwarzenberg, Pablo
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9174
- Acceso en línea:
- https://hdl.handle.net/11323/9174
https://doi.org/10.1007/s00170-022-08981-z
https://repositorio.cuc.edu.co/
- Palabra clave:
- Complexity
Manufacturing
Statistical
Characteristics
- Rights
- embargoedAccess
- License
- © 2022 Springer Nature Switzerland AG. Part of Springer Nature.
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Statistical analysis of manufacturing system complexity |
| title |
Statistical analysis of manufacturing system complexity |
| spellingShingle |
Statistical analysis of manufacturing system complexity Complexity Manufacturing Statistical Characteristics |
| title_short |
Statistical analysis of manufacturing system complexity |
| title_full |
Statistical analysis of manufacturing system complexity |
| title_fullStr |
Statistical analysis of manufacturing system complexity |
| title_full_unstemmed |
Statistical analysis of manufacturing system complexity |
| title_sort |
Statistical analysis of manufacturing system complexity |
| dc.creator.fl_str_mv |
Herrera Vidal, Germán Coronado-Hernandez, Jairo R. Minnaard, Claudia Gustavo, Gatica Schwarzenberg, Pablo |
| dc.contributor.author.spa.fl_str_mv |
Herrera Vidal, Germán Coronado-Hernandez, Jairo R. Minnaard, Claudia Gustavo, Gatica Schwarzenberg, Pablo |
| dc.subject.proposal.eng.fl_str_mv |
Complexity Manufacturing Statistical Characteristics |
| topic |
Complexity Manufacturing Statistical Characteristics |
| description |
Given the dynamism of the markets and the economic growth, nowadays companies must look for mechanisms that allow them to develop new strategies and compete successfully. The objective of this work is to develop a statistical analysis of the complexity of a manufacturing system. The methodological approach starts with the analysis of the data obtained through the Likert technique, identifying characteristics associated with high complexity, consequently, an inquiry is made on the factors that influence significantly from an experimental analysis, then a factor analysis is made to determine the correlations between the variables raised, and finally the association between the complexity of the manufacturing characteristics and the complexity of the elements of a system is evaluated. The study is based on a sample of 71 small- and medium-sized companies in the city of Cartagena, Colombia. The results obtained show a dominance of complexity in manufacturing systems, confirming the level of significance between subsectors, type of operation, and type of process; determining that there are high correlations between the variables; and corroborating the relationship between the variables and the characteristics of the manufacturing system. |
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2022 |
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Vidal, G.H., Hernández, J.R.C., Minnaard, C. et al. Statistical analysis of manufacturing system complexity. Int J Adv Manuf Technol 120, 3427–3436 (2022). https://doi.org/10.1007/s00170-022-08981-z |
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0268-3768 |
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1433-3015 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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Vidal, G.H., Hernández, J.R.C., Minnaard, C. et al. Statistical analysis of manufacturing system complexity. Int J Adv Manuf Technol 120, 3427–3436 (2022). https://doi.org/10.1007/s00170-022-08981-z 0268-3768 10.1007/s00170-022-08981-z 1433-3015 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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eng |
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International Journal of Advanced Manufacturing Technology |
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1. Salom G, Shulterbrandt S (2012) Microenterprises, SMEs and Latin America. In Inter Forum Magazine. Retrieved on (pp. 10–12) 2. Wolff J, Pett T (2006) Small-firm performance: modeling the role of product and process improvements. J Small Bus Manag 44(2):268–284. https://doi.org/10.1111/j.1540-627X.2006.00167.x 3. Escobar A, Velandia G, Hernández P (2017) Gestión del conocimiento e innovación en las PYME exportadoras del sector industrial en Colombia 4. Pine Ii B, Hull R (1995) Mass customization: the new frontier in business competition. R and D Manag 25(2):254 5. Michalos G, Makris S, Papakostas N, Mourtzis D, Chryssolouris G (2010) Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach. CIRP J Manuf Sci Technol 2(2):81–91. https://doi.org/10.1016/j.cirpj.2009.12.001 6. Vidal GH, Hernández JRC (2021) Study of the effects of complexity on the manufacturing sector. Prod Eng Res Devel. https://doi.org/10.1007/s11740-020-01014-2 7. Papakostas N, Papachatzakis P, Xanthakis V, Mourtzis D, Chryssolouris G (2010) An approach to operational aircraft maintenance planning. Decis Support Syst 48(4):604–612. https://doi.org/10.1016/j.dss.2009.11.010 8. Herbert S (1962) The architecture of complexity. Proc Am Philos Soc 106(6):467–482. https://doi.org/10.2307/985254 9. Flynn B, Flynn E (1999) Information-processing alternatives for coping with manufacturing environment complexity. Decis Sci 30(4):1021–1052. https://doi.org/10.1111/j.1540-5915.1999.tb00917.x 10. Calinescu A, Efstathiou J, Bermejo J, Schirn J (1997) Assessing decision-making and process complexity in a manufacturer through simulation. IFAC Proceedings Volumes 30(24):149–152 11. Isik F (2010) An entropy-based approach for measuring complexity in supply chains. Int J Prod Res 48(12):3681–3696. https://doi.org/10.1080/00207540902810593 12. Gaio L, Gino F, Zaninotto E (2002) I sistemi di produzione: manuale per la gestione operativa dell’impresa. Carocci 13. Bick W, Drexl-Wittbecker S (2008) Komplexität reduzieren: Konzept. Methoden. Praxis. LOG_X, Stuttgart 14. Salum L (2000) The cellular manufacturing layout problem. Int J Prod Res 38(5):1053–1069. https://doi.org/10.1080/002075400189013 15. Heragu S, Kusiak A (1988) Machine layout problem in flexible manufacturing systems. Oper Res 36(2):258–268 16. Meller R, Gau K (1996) The facility layout problem: recent and emerging trends and perspectives. J Manuf Syst 15(5):351–366. https://doi.org/10.1287/opre.36.2.258 17. Li S, Rao S, Ragu-Nathan T, Ragu-Nathan B (2005) Development and validation of a measurement instrument for studying supply chain management practices. J Oper Manag 23(6):618–641. https://doi.org/10.1016/j.jom.2005.01.002 18. Wu Y, Frizelle G, Ayral L, Marsein J, Van de Merwe E, Zhou D (2002) A simulation study on supply chain complexity in manufacturing industry. En Proceedings of the conference of the manufacturing complexity network. University of Cambridge. https://doi.org/10.1016/j.cirpj.2019.02.001 19. Jacobs M (2007) Product complexity: a definition and impacts on operations. Decision Line 38(5):6–12. https://doi.org/10.1016/j.cirpj.2019.02.001 20. Efthymiou K, Mourtzis D, Pagoropoulos A, Papakostas N, Chryssolouris G (2016) Manufacturing systems complexity analysis methods review. Int J Comput Integr Manuf 29(9):1025–1044. https://doi.org/10.1080/0951192X.2015.1130245 21. Hernández S, Fernández C, Baptista L (2014) Metodología de la investigación. Investigación cuantitativa (p 5) 22. Tamayo M (2004) El proceso de la investigación científica. Editorial Limusa 23. Guimaraes T, Martensson N, Stahre J, Igbaria M (1999) Empirically testing the impact of manufacturing system complexity on performance. Int J Oper Prod Manag. https://doi.org/10.1108/01443579910294228 24. Bozarth C, Warsing D, Flynn B, Flynn E (2009) The impact of supply chain complexity on manufacturing plant performance. J Oper Manag 27(1):78–93. https://doi.org/10.1016/j.jom.2008.07 25. Garbie I, Shikdar A (2010) Complexity level in industrial firms: case studies and implementation. En Proceedings of the 2010 international conference on industrial engineering and operations management (IEOM 2010). Dhaka, Bangladesh: International University of Bangladesh, p 9–10 26. Eckstein D, Goellner M, Blome C, Henke M (2015) The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity. Int J Prod Res 53(10):3028–3046. https://doi.org/10.1080/00207543.2014.970707 27. Kohr D, Budde L, Friedli T (2017) Identifying complexity drivers in discrete manufacturing and process industry. Procedia CIRP 63:52–57 28. Alshammari F, Yahya K, Haron Z (2020) A conceptual approach in developing a project manager’s skills framework (PMSF) for improving the performance of complex projects in Kuwait construction industry. En IOP Conference Series: Materials Science and Engineering. IOP Publishing, p 012007 29. Saraph J, Benson PG, Schroeder RG (1989) An instrument for measuring the critical factors of quality management. Decis Sci 20(4):810–829. https://doi.org/10.1111/j.1540-5915.1989.tb01421.x 30. Sekaran U, Bougie R (2016) Research methods for business: a skill building approach. John Wiley & Sons |
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Herrera Vidal, GermánCoronado-Hernandez, Jairo R.Minnaard, Claudia Gustavo, GaticaSchwarzenberg, Pablo2022-05-17T19:44:13Z20232022-05-17T19:44:13Z2022Vidal, G.H., Hernández, J.R.C., Minnaard, C. et al. Statistical analysis of manufacturing system complexity. Int J Adv Manuf Technol 120, 3427–3436 (2022). https://doi.org/10.1007/s00170-022-08981-z0268-3768https://hdl.handle.net/11323/9174https://doi.org/10.1007/s00170-022-08981-z10.1007/s00170-022-08981-z1433-3015Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Given the dynamism of the markets and the economic growth, nowadays companies must look for mechanisms that allow them to develop new strategies and compete successfully. The objective of this work is to develop a statistical analysis of the complexity of a manufacturing system. The methodological approach starts with the analysis of the data obtained through the Likert technique, identifying characteristics associated with high complexity, consequently, an inquiry is made on the factors that influence significantly from an experimental analysis, then a factor analysis is made to determine the correlations between the variables raised, and finally the association between the complexity of the manufacturing characteristics and the complexity of the elements of a system is evaluated. The study is based on a sample of 71 small- and medium-sized companies in the city of Cartagena, Colombia. The results obtained show a dominance of complexity in manufacturing systems, confirming the level of significance between subsectors, type of operation, and type of process; determining that there are high correlations between the variables; and corroborating the relationship between the variables and the characteristics of the manufacturing system.1 páginaapplication/pdfengSpringer LondonUnited Kingdom© 2022 Springer Nature Switzerland AG. Part of Springer Nature.Atribución 4.0 Internacional (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfStatistical analysis of manufacturing system complexityArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_b1a7d7d4d402bccehttps://link.springer.com/article/10.1007/s00170-022-08981-zInternational Journal of Advanced Manufacturing Technology1. Salom G, Shulterbrandt S (2012) Microenterprises, SMEs and Latin America. In Inter Forum Magazine. Retrieved on (pp. 10–12)2. Wolff J, Pett T (2006) Small-firm performance: modeling the role of product and process improvements. J Small Bus Manag 44(2):268–284. https://doi.org/10.1111/j.1540-627X.2006.00167.x3. Escobar A, Velandia G, Hernández P (2017) Gestión del conocimiento e innovación en las PYME exportadoras del sector industrial en Colombia4. Pine Ii B, Hull R (1995) Mass customization: the new frontier in business competition. R and D Manag 25(2):2545. Michalos G, Makris S, Papakostas N, Mourtzis D, Chryssolouris G (2010) Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach. CIRP J Manuf Sci Technol 2(2):81–91. https://doi.org/10.1016/j.cirpj.2009.12.0016. Vidal GH, Hernández JRC (2021) Study of the effects of complexity on the manufacturing sector. Prod Eng Res Devel. https://doi.org/10.1007/s11740-020-01014-27. Papakostas N, Papachatzakis P, Xanthakis V, Mourtzis D, Chryssolouris G (2010) An approach to operational aircraft maintenance planning. Decis Support Syst 48(4):604–612. https://doi.org/10.1016/j.dss.2009.11.0108. Herbert S (1962) The architecture of complexity. Proc Am Philos Soc 106(6):467–482. https://doi.org/10.2307/9852549. Flynn B, Flynn E (1999) Information-processing alternatives for coping with manufacturing environment complexity. Decis Sci 30(4):1021–1052. https://doi.org/10.1111/j.1540-5915.1999.tb00917.x10. Calinescu A, Efstathiou J, Bermejo J, Schirn J (1997) Assessing decision-making and process complexity in a manufacturer through simulation. IFAC Proceedings Volumes 30(24):149–15211. Isik F (2010) An entropy-based approach for measuring complexity in supply chains. Int J Prod Res 48(12):3681–3696. https://doi.org/10.1080/0020754090281059312. Gaio L, Gino F, Zaninotto E (2002) I sistemi di produzione: manuale per la gestione operativa dell’impresa. Carocci13. Bick W, Drexl-Wittbecker S (2008) Komplexität reduzieren: Konzept. Methoden. Praxis. LOG_X, Stuttgart14. Salum L (2000) The cellular manufacturing layout problem. Int J Prod Res 38(5):1053–1069. https://doi.org/10.1080/00207540018901315. Heragu S, Kusiak A (1988) Machine layout problem in flexible manufacturing systems. Oper Res 36(2):258–26816. Meller R, Gau K (1996) The facility layout problem: recent and emerging trends and perspectives. J Manuf Syst 15(5):351–366. https://doi.org/10.1287/opre.36.2.25817. Li S, Rao S, Ragu-Nathan T, Ragu-Nathan B (2005) Development and validation of a measurement instrument for studying supply chain management practices. J Oper Manag 23(6):618–641. https://doi.org/10.1016/j.jom.2005.01.00218. Wu Y, Frizelle G, Ayral L, Marsein J, Van de Merwe E, Zhou D (2002) A simulation study on supply chain complexity in manufacturing industry. En Proceedings of the conference of the manufacturing complexity network. University of Cambridge. https://doi.org/10.1016/j.cirpj.2019.02.00119. Jacobs M (2007) Product complexity: a definition and impacts on operations. Decision Line 38(5):6–12. https://doi.org/10.1016/j.cirpj.2019.02.00120. Efthymiou K, Mourtzis D, Pagoropoulos A, Papakostas N, Chryssolouris G (2016) Manufacturing systems complexity analysis methods review. Int J Comput Integr Manuf 29(9):1025–1044. https://doi.org/10.1080/0951192X.2015.113024521. Hernández S, Fernández C, Baptista L (2014) Metodología de la investigación. Investigación cuantitativa (p 5)22. Tamayo M (2004) El proceso de la investigación científica. Editorial Limusa23. Guimaraes T, Martensson N, Stahre J, Igbaria M (1999) Empirically testing the impact of manufacturing system complexity on performance. Int J Oper Prod Manag. https://doi.org/10.1108/0144357991029422824. Bozarth C, Warsing D, Flynn B, Flynn E (2009) The impact of supply chain complexity on manufacturing plant performance. J Oper Manag 27(1):78–93. https://doi.org/10.1016/j.jom.2008.0725. Garbie I, Shikdar A (2010) Complexity level in industrial firms: case studies and implementation. En Proceedings of the 2010 international conference on industrial engineering and operations management (IEOM 2010). Dhaka, Bangladesh: International University of Bangladesh, p 9–1026. Eckstein D, Goellner M, Blome C, Henke M (2015) The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity. Int J Prod Res 53(10):3028–3046. https://doi.org/10.1080/00207543.2014.97070727. Kohr D, Budde L, Friedli T (2017) Identifying complexity drivers in discrete manufacturing and process industry. Procedia CIRP 63:52–5728. Alshammari F, Yahya K, Haron Z (2020) A conceptual approach in developing a project manager’s skills framework (PMSF) for improving the performance of complex projects in Kuwait construction industry. En IOP Conference Series: Materials Science and Engineering. IOP Publishing, p 01200729. Saraph J, Benson PG, Schroeder RG (1989) An instrument for measuring the critical factors of quality management. Decis Sci 20(4):810–829. https://doi.org/10.1111/j.1540-5915.1989.tb01421.x30. Sekaran U, Bougie R (2016) Research methods for business: a skill building approach. 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