Optimal measurement schedule to support quality management

J. Gren, K. Konkarikoski, R. Ritala

Abstract

In industrial processes, such as in papermaking, the product quality is measured from end product samples in laboratory. It is a common practice to measure all quality parameters at regular time intervals. However, this is costly and may limit possibilities to measure those quality parameters that would be most important for overall uncertainty management and thus for decision support. This paper show general theory for measurement information dynamics and discusses how we can find the lowest cost measurement schedule satisfying the constraints on uncertainty in quality information. This paper gives theoretical approach with real data application and results show how optimal measurement schedule can be obtained to support quality management.

Keywords

Decision support; quality; uncertainty; Bayesian; information

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IMEKO-TC14-2007-58.pdf

DOI

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IMEKO TC

TC14 - Measurement of Geometrical Quantities

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