Abstract
The business environment is becoming increasingly fast-paced, competitive and demanding, making it vital for manufacturing processes to create agile, flexible and simplified environments. The objective of this research is to apply a new entropic and hybrid metric to measure complexity in manufacturing systems with flow shop and job shop environments. The methodological approach is based on equations that facilitate entropic analysis in different types of scenarios and provide quantitative support for decision making. The model is defined in two vectors, one of a classical subjective type based on the complexity index method (CXI), and the other of an objective type focused on Shannon's entropy metric. In both situations a new entropic metric of complexity measurement is applied. For its application, the following are used two particular case studies are used for its application and finally the results and discussions are presented. The findings allow us to solve, with the new method, the shortcomings found in the classical methods and to propose improvement bets in the areas detected in the different processes.
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Acknowledgements
Thanks are due to the 2 small and medium-sized enterprises in the manufacturing sector in the city of Cartagena, Colombia, for their access to technical visits, information gathering and support. We would also like to thank the Universidad del Sinú (USINU)-Colombia, for the support of its academic and scientific group, especially the DeArtica research group. We would also like to thank the Universidad de la Costa (CUC)-Colombia and the Universidad Nacional Lomas de Zamora (UNLZ)-Argentina.
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All authors contributed to the development of the research and approval of the final version. GHV, conceptualisation, methodology, research, writing—original draft, revision and editing. JRCH, conceptualisation, methodology. CM: research and analysis of input and output data.
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Vidal, G.H., Hernández, J.R.C. & Minnaard, C. Measuring complexity in manufacturing systems: a new metric in flow shop (Fs) and job shop (Js) environments. Prod. Eng. Res. Devel. 18, 653–665 (2024). https://doi.org/10.1007/s11740-023-01237-z
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DOI: https://doi.org/10.1007/s11740-023-01237-z