Download statistics - Document (COUNTER):
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
Selected time period:
Sum total of downloads: 188
| Abstract: | |
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. | |
| License of this version: | CC BY 3.0 DE |
| Document Type: | BookPart |
| Publishing status: | publishedVersion |
| Issue Date: | 2023 |
| Appears in Collections: | Proceedings CPSL 2023 - 2 Proceedings CPSL 2023 - 2 |
distribution of downloads over the selected time period:
downloads by country:
| pos. | country | downloads | ||
|---|---|---|---|---|
| total | perc. | |||
| 1 |  |
Peru | 66 | 35.11% |
| 2 |  |
United States | 24 | 12.77% |
| 3 |  |
No geo information available | 16 | 8.51% |
| 4 |  |
Germany | 15 | 7.98% |
| 5 |  |
Indonesia | 6 | 3.19% |
| 6 |  |
Paraguay | 5 | 2.66% |
| 7 |  |
India | 5 | 2.66% |
| 8 |  |
Israel | 5 | 2.66% |
| 9 |  |
Brazil | 5 | 2.66% |
| 10 |  |
Pakistan | 4 | 2.13% |
| other countries | 37 | 19.68% | ||
Further download figures and rankings:
Hinweis
Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.