Productivity improvement by means of method engineering tools and automation in ice cream production at bonanza company

Sofia Raymunda Aldana-Fernandez, Edgar Walter Menendez-Elguera, Sebastian David Torres-Sanchez, Nabilt Moggiano, Ruben Dario Arzapalo-Bello

Producción científica: Libro o Capítulo del libro Contribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

The production of ice cream has become very popular in the last decade, showing a gradual increase in the preference of food consumption, generating millions of dollars in the international market, becoming a sector with great technological progress helping to improve the ice cream industry. Even so, there are companies that carry out the processes in an artisanal manner or with little technological modernization, as is the case of the Bonanza company. The purpose of this research is to improve productivity through the use of method engineering tools and industrial automation in the production of ice cream line of Bonanza company. In a guided inspection, the operations diagram, process analysis and route diagram were determined. Finding dead times, bottlenecks, congestion and misuse of resources. With the help of Autodesk Inventor, LabVIEW and TinkerCAD programs, the design and simulation of automated machines for the process of cleaning, inspection and weighing of fruit was carried out. This allowed to go from 30 min, 41 min and 65 min to 14 min and 20 minutes by merging the last two processes respectively. In addition to improving all internal processes and restructuring the path of the route. In conclusion, with the implementation of this project, the product execution time was reduced by 3 hours, optimal resources and increased productivity in the Bonanza company.

Idioma originalInglés estadounidense
Título de la publicación alojada2023 IEEE World AI IoT Congress, AIIoT 2023
EditoresSatyajit Chakrabarti, Rajashree Paul
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas724-729
-6
ISBN (versión digital)9798350337617
DOI
EstadoIndizado - 2023
Evento2023 IEEE World AI IoT Congress, AIIoT 2023 - Virtual, Online, Estados Unidos
Duración: 7 jun. 202310 jun. 2023

Serie de la publicación

Nombre2023 IEEE World AI IoT Congress, AIIoT 2023

Conferencia

Conferencia2023 IEEE World AI IoT Congress, AIIoT 2023
País/TerritorioEstados Unidos
CiudadVirtual, Online
Período7/06/2310/06/23

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Publisher Copyright:
© 2023 IEEE.

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