Multi-Model In-Plant Logistics Using Milkruns for Flexible Assembly Systems under Disturbances: An Industry Study Case
Financiación H2020 / H2020 Funds
Resumen: Mass customisation demand requires increasingly flexible assembly operations. For the in-plant logistics of such systems, milkrun trains could present advantages under high variability conditions. This article uses an industrial study case from a global white-goods manufacturing company. A discrete events simulation model was developed to explore the performance of multi-model assembly lines using a set of operational and logistics Key Performance Indicators. Four simulation scenarios analyse the separate effects of an increased number of product models and three different sources of variability. The results show that milkruns can protect the assembly lines from upstream process disturbances.
Idioma: Inglés
DOI: 10.3390/machines11010066
Año: 2023
Publicado en: Machines 11, 1 (2023), 66 [21 pp.]
ISSN: 2075-1702

Factor impacto JCR: 2.1 (2023)
Categ. JCR: ENGINEERING, MECHANICAL rank: 82 / 180 = 0.456 (2023) - Q2 - T2
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 192 / 352 = 0.545 (2023) - Q3 - T2

Factor impacto CITESCORE: 3.0 - Industrial and Manufacturing Engineering (Q2) - Mechanical Engineering (Q2) - Control and Optimization (Q2) - Computer Science (miscellaneous) (Q3) - Control and Systems Engineering (Q2) - Electrical and Electronic Engineering (Q3)

Factor impacto SCIMAGO: 0.474 - Computer Science (miscellaneous) (Q2) - Control and Optimization (Q2) - Mechanical Engineering (Q2) - Electrical and Electronic Engineering (Q2) - Industrial and Manufacturing Engineering (Q2) - Control and Systems Engineering (Q2)

Financiación: info:eu-repo/grantAgreement/EC/H2020/814225/EU/DIGItal MANufacturing Technologies for Zero-defect Industry 4.0 Production/DIGIMAN4.0
Tipo y forma: Artículo (Versión definitiva)
Área (Departamento): Área Ing. Procesos Fabricación (Dpto. Ingeniería Diseño Fabri.)

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