Abstract

Measurements often provide an objective basis for making decisions, perhaps when assessing whether a product conforms to requirements or whether one set of measurements differs significantly from another. There is increasing appreciation of the need to account for the role of measurement uncertainty when making decisions, so that a ‘fit-for-purpose’ level of measurement effort can be set prior to performing a given task. Better mutual understanding between the metrologist and those ordering such tasks about the significance and limitations of the measurements when making decisions of conformance will be especially useful. Decisions of conformity are, however, currently made in many important application areas, such as when addressing the grand challenges (energy, health, etc), without a clear and harmonized basis for sharing the risks that arise from measurement uncertainty between the consumer, supplier and third parties.In reviewing, in this paper, the state of the art of the use of uncertainty evaluation in conformity assessment and decision-making, two aspects in particular—the handling of qualitative observations and of impact—are considered key to bringing more order to the present diverse rules of thumb of more or less arbitrary limits on measurement uncertainty and percentage risk in the field. (i) Decisions of conformity can be made on a more or less quantitative basis—referred in statistical acceptance sampling as by ‘variable’ or by ‘attribute’ (i.e. go/no-go decisions)—depending on the resources available or indeed whether a full quantitative judgment is needed or not. There is, therefore, an intimate relation between decision-making, relating objects to each other in terms of comparative or merely qualitative concepts, and nominal and ordinal properties. (ii) Adding measures of impact, such as the costs of incorrect decisions, can give more objective and more readily appreciated bases for decisions for all parties concerned. Such costs are associated with a variety of consequences, such as unnecessary re-manufacturing by the supplier as well as various consequences for the customer, arising from incorrect measures of quantity, poor product performance and so on.

Highlights

  • Decisions of conformity are currently made in many important application areas, such as environmental monitoring, the health sector and product safety testing, but without a clear and harmonized basis for sharing the risks that arise from measurement uncertainty between the consumer and the supplier

  • Separating production and measurement errors—numerically. Accounting for risks such as those arising from measurement uncertainty and associated decision rules in conformity assessment are the main subject of this work

  • It was emphasized that the study of the role of measurement uncertainty in conformity assessment addresses an area where two disciplines—conformity assessment and metrology— meet

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Summary

Introduction

Measurement is in most cases not an end in itself, but rather provides the means to make objective decisions, such as ‘do the new set of measurements differ from previous measurements?’ or ‘do measurements show that a product. The role of measurement uncertainty in high-value manufacturing is reviewed in another paper in this special issue (Loftus and Giudice 2014). Decisions of conformity are currently made in many important application areas, such as environmental monitoring, the health sector and product safety testing, but without a clear and harmonized basis for sharing the risks that arise from measurement uncertainty between the consumer and the supplier. The state of the art of uncertainty evaluation in decisionmaking and conformity assessment will be reviewed in this paper. Starting with published guides such as the recent JCGM 106:2012 guide, and current work in the EURAMET EMRP project NEW04 ‘Uncertainty’, new perspectives are being gained about the use of measurement uncertainty by extending analyses to multivariate, qualitative data, and the inclusion of measures of impact

Essential steps in conformity assessment
Measurement specifications
Separating production and measurement errors—numerically
Separating production and measurement errors—conceptually
Measurement conformity assessment: limits on measurement capability factors
Maximum permissible uncertainty and minimum measurement capability
Deciding if entity is within specified requirements
Risks of incorrect decisions of conformity—in percentage terms
Percentage risk
Sharing risks
Costs and economic risks in conformity assessment
Introducing cost into conformity assessment risks
10. Optimized uncertainty
10.1. Balancing test costs against consequence costs
10.2. Global conformity assessment by variable and by attribute
11. Conclusion and future work
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