A Production Model based in Lean 4.0 Principles And Machine Learning To Enhance The Productivity Of Small And Medium-Sized Enterprises (SMEs) In Peru's Food Manufacturing Sector

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Komori-Zevallos, A.R.;Montedoro-Garay, F.M.; Garcia-Lopez, Y.J.; Quiroz Flores, J.C.: A Production Model based in Lean 4.0 Principles And Machine Learning To Enhance The Productivity Of Small And Medium-Sized Enterprises (SMEs) In Peru's Food Manufacturing Sector. In: Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 2. Hannover : publish-Ing., 2023, S. 139-150. DOI: https://doi.org/10.15488/15256

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New technologies, increasing competition, and changing consumer preferences in the food manufacturing sector have forced companies to generate customized products in dynamic demand and thus remain competitive in the market. As a result, companies have had to rethink their processes and product designs to optimize their manufacturing operations. In addition, moving from a conventional production model to processes supported by intelligent systems to generate efficiency improvements in the demand planning and productivity in their activities is necessary. This paper aims to introduce the development of an integrated model of lean 4.0 practices, demand forecasting using SARIMAX and DSS in a manufacturing SME. In addition, a literature review allowed identifying the variables that would be affected, such as inventory, waste, obsolete products, and productivity. Finally, a case study in the food manufacturing sector is considered to validate the model. The results will be presented through a visual analytics dashboard to streamline plant team decision-making.
Lizenzbestimmungen: CC BY 3.0 DE
Publikationstyp: BookPart
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2023
Die Publikation erscheint in Sammlung(en):Proceedings CPSL 2023 - 2
Proceedings CPSL 2023 - 2

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Anzahl Proz.
1 image of flag of Peru Peru 42 31,82%
2 image of flag of United States United States 24 18,18%
3 image of flag of Germany Germany 12 9,09%
4 image of flag of No geo information available No geo information available 6 4,55%
5 image of flag of Paraguay Paraguay 5 3,79%
6 image of flag of India India 5 3,79%
7 image of flag of Indonesia Indonesia 5 3,79%
8 image of flag of Brazil Brazil 5 3,79%
9 image of flag of Pakistan Pakistan 4 3,03%
10 image of flag of Switzerland Switzerland 3 2,27%
    andere 21 15,91%

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