Resumen
The food sector is developing differently worldwide, growing exponentially in recent years. However, due to consumer demand, industries have opted to transform or modify raw materials. These challenges also have an economic impact on companies. In this sense, food companies aim to increase productivity in their product chain by minimizing losses. This research will analyze the losses in the production chain that generate a minimum growth percentage. Therefore, a model based on tools such as Systematic Layout Planning, Total Productive Maintenance, and Standardization is proposed to increase productivity in food manufacturing companies. Therefore, the research focuses on the family of cereals with one of the highest growth rates in the global market, such as quinoa, wheat, and corn. An analysis and diagnosis were carried out to identify the root causes of the problem so that it can be combated with the tools mentioned above. Finally, the delivery models managed to reduce production cycle times by 26.26% and increase the company's productivity by 10.82%, achieving an improvement in the optimization of the production process of food manufacturing companies.
| Idioma original | Inglés estadounidense |
|---|---|
| Título de la publicación alojada | 2022 8th International Conference on Industrial and Business Engineering, ICIBE 2022 |
| Editorial | Association for Computing Machinery |
| Páginas | 299-306 |
| - | 8 |
| ISBN (versión digital) | 9781450397582 |
| DOI | |
| Estado | Indizado - 27 set. 2022 |
| Publicado de forma externa | Sí |
| Evento | 8th International Conference on Industrial and Business Engineering, ICIBE 2022 - Virtual, Online, China Duración: 27 set. 2022 → 29 set. 2022 |
Serie de la publicación
| Nombre | ACM International Conference Proceeding Series |
|---|
Conferencia
| Conferencia | 8th International Conference on Industrial and Business Engineering, ICIBE 2022 |
|---|---|
| País/Territorio | China |
| Ciudad | Virtual, Online |
| Período | 27/09/22 → 29/09/22 |
Nota bibliográfica
Publisher Copyright:© 2022 ACM.
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