Comunicación presentada a MESIC 2019 8th Manufacturing Engineering Society International Conference (Madrid, 19-21 de Junio de 2019)Variation propagation has been successfully modeled by the Stream of Variation (SoV) approach in multistage machining processes. However, the SoV model basically supports 3-2-1 fixtures based on punctual locators and other workholding systems such as conventional vises are not considered yet. In this paper, the SoV model is expanded to include the fixture- and datum-induced variations on workholding devices such as bench vises. The model derivation is validated through assembly and machining simulations on Computer Aided Design software. The case study analyzed shows an average error of part quality prediction ...
Multistage manufacturing processes (MMP) are complicated processes involving more than one workstati...
ABSTRACT Linear state space Stream of Variation (SoV) models of error flow in multistation assembly ...
Multi-stage production systems concede for low error and failure margins within every single machini...
Modelling the dimensional variation propagation in multi-station machining processes (MMPs) has been...
Recent research efforts have been aimed toward deriving mathematical models to relate manufacturing ...
Nowadays, advanced manufacturing models, such as the stream-of-variation (SoV) model, have been succ...
Variation propagation modeling of multistage machining processes enables variation reduction by maki...
A stream-of-variation analysis (SOVA) model for three-dimensional (3D) rigid-body assemblies in a si...
In multi-operational machining processes, part dimensional variation can be attributed to a variety ...
In product design and quality improvement fields, the development of reliable 3D machining variation...
Purpose - Dimensional variation management is a major challenge in multi-station sheet metal assembl...
Variation propagation models play an important role in part quality prediction, variation source ide...
Current works on process-oriented tolerancing for multi-station manufacturing processes (MMPs) have ...
The research presented in this dissertation offers a new linear state space model of dimensional mac...
Manufacturing process variability is a major issue of concern in high value industries. Manufacturin...
Multistage manufacturing processes (MMP) are complicated processes involving more than one workstati...
ABSTRACT Linear state space Stream of Variation (SoV) models of error flow in multistation assembly ...
Multi-stage production systems concede for low error and failure margins within every single machini...
Modelling the dimensional variation propagation in multi-station machining processes (MMPs) has been...
Recent research efforts have been aimed toward deriving mathematical models to relate manufacturing ...
Nowadays, advanced manufacturing models, such as the stream-of-variation (SoV) model, have been succ...
Variation propagation modeling of multistage machining processes enables variation reduction by maki...
A stream-of-variation analysis (SOVA) model for three-dimensional (3D) rigid-body assemblies in a si...
In multi-operational machining processes, part dimensional variation can be attributed to a variety ...
In product design and quality improvement fields, the development of reliable 3D machining variation...
Purpose - Dimensional variation management is a major challenge in multi-station sheet metal assembl...
Variation propagation models play an important role in part quality prediction, variation source ide...
Current works on process-oriented tolerancing for multi-station manufacturing processes (MMPs) have ...
The research presented in this dissertation offers a new linear state space model of dimensional mac...
Manufacturing process variability is a major issue of concern in high value industries. Manufacturin...
Multistage manufacturing processes (MMP) are complicated processes involving more than one workstati...
ABSTRACT Linear state space Stream of Variation (SoV) models of error flow in multistation assembly ...
Multi-stage production systems concede for low error and failure margins within every single machini...