Bottleneck prediction and data-driven discrete-event simulation for a balanced manufacturing line

Bottleneck identification is a relevant tool for continuous optimization of production lines. In this work, we implement a data-driven discrete-event simulator (DDS) based on experimental distributions, obtained from real historical data. The DDS allows to analyse the behavior of a balanced manufact...

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Bibliographic Details
Main Author: Rocha, Eugénio M. (author)
Other Authors: Lopes, Maria J. (author)
Format: article
Language:eng
Published: 2022
Subjects:
Data-driven discrete-event simulation
Bottleneck prediction
Machine learning
Manufacturing lines
Online Access:http://hdl.handle.net/10773/35452
Country:Portugal
Oai:oai:ria.ua.pt:10773/35452

Internet

http://hdl.handle.net/10773/35452

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