Design of multi-station manufacturing processes by integrating the stream-of-variation model and shop-floor data
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Scholar |
Otros documentos de la autoría: Abellán-Nebot, José V.; Liu, Jian; Romero Subirón, Fernando
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7034
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http://dx.doi.org/10.1016/j.jmsy.2011.04.001 |
Metadatos
Título
Design of multi-station manufacturing processes by integrating the stream-of-variation model and shop-floor dataFecha de publicación
2011-04Editor
ElsevierISSN
0278-6125Cita bibliográfica
Journal of Manufacturing Systems Volume 30, Issue 2, April 2011Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0278612511000264Palabras clave / Materias
Resumen
Processdesign has been intensively studied to reduce dimensional variability of products produced in multi-stationmanufacturingprocesses (MMPs). Most of the existing studies focus on predicting variation propagation ... [+]
Processdesign has been intensively studied to reduce dimensional variability of products produced in multi-stationmanufacturingprocesses (MMPs). Most of the existing studies focus on predicting variation propagation and evaluating process robustness. However, these studies overlook the potential use of historical shop-floor quality data of existing MMPs in order to extract the actual manufacturing operation capabilities from each station, and then, to evaluate more accurately the expected dimensional variability of new candidate process plans. This paper proposes a methodology to improve process plan selection based on three components: (i) based on historical shopfloordata, an inference on the process capabilities of the stations in an existing MMP, which will be used to produce the new product; (ii) a sensitivity analysis of candidate process plans to identify critical fixtures and manufacturingstations/operations; and (iii) an optimal selection of candidate process plans. A case study is presented to demonstrate the effectiveness of the methodology. [-]
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Copyright © 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
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