OPTIMISING A MEASUREMENT SETUP FOR DECISION MAKING

Kimmo Latva-Käyrä, Risto Ritala

Abstract

Measurements are the key to rational decision making. Measurement information generates value, when it is applied in the decision making. An investment cost and maintenance costs are associated with each component of the measurement system. Clearly, there is – under a given set of scenarios – a measurement setup that is optimal in expected (discounted) utility. Contrary to process design, design of measurement and information systems has not been formulated as such an optimization problem, but rather been tackled intuitively. In this presentation we propose a framework for analyzing such an optimization problem. Our framework is based on that the basic mechanism of measurement is reduction of uncertainty about reality. Statistical decision theory serves as the basis for analyzing decision making. In this paper we apply the framework to a problem that is rather simple but of practical importance: how to arrange laboratory quality measurements optimally. In particular, we discuss a case in the paper making industry, in which the product quality is measured with automated quality analyzers and by laboratory measurements.

Keywords

decision support, design, optimization, uncertainty

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PWC-2006-TC7-026u.pdf

DOI

-

IMEKO TC

TC7 - Measurement Science

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