Often the manufacturing and the inspection workstations in a manufacturing process can coincide: thus, in these workstations the statistical process control (SPC) procedure of collecting sample statistics related to a critical-to-quality parameter is a task required to be done by the same worker who has to complete the working operations on a part. The aim of this study is to design a local SPC inspection procedure implementing an adaptive Shewhart control chart locally managed by the worker within the manufacturing workstation: the economic design of the inspection procedure is constrained by the expected number of false alarms issued and is restricted to those designs feasible with respect to the available shared labour resource. Furthermore, a robust approach that models the shift of the controlled parameter mean as a random variable is taken into account. The numerical analysis allows the most influencing environmental process factors to be captured and commented upon. The obtained results show that a few process operating parameters drive the choice of performing a robust optimization and the selection of the optimal SPC adaptive procedure.

Robust design of adaptive control charts for manual manufacturing / inspection workstations

CELANO, GIOVANNI
2009-01-01

Abstract

Often the manufacturing and the inspection workstations in a manufacturing process can coincide: thus, in these workstations the statistical process control (SPC) procedure of collecting sample statistics related to a critical-to-quality parameter is a task required to be done by the same worker who has to complete the working operations on a part. The aim of this study is to design a local SPC inspection procedure implementing an adaptive Shewhart control chart locally managed by the worker within the manufacturing workstation: the economic design of the inspection procedure is constrained by the expected number of false alarms issued and is restricted to those designs feasible with respect to the available shared labour resource. Furthermore, a robust approach that models the shift of the controlled parameter mean as a random variable is taken into account. The numerical analysis allows the most influencing environmental process factors to be captured and commented upon. The obtained results show that a few process operating parameters drive the choice of performing a robust optimization and the selection of the optimal SPC adaptive procedure.
2009
Statistical Process Control; Control Charts; Robust optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/8334
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