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Risk Analysis by a Probabilistic Model of the Measurement Process
Wojciech Toczek1, Janusz Smulko1
1Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, Poland.
Sensors (Basel, Switzerland)
|April 3, 2021
Summary
This study presents a probabilistic model for measurement processes, identifying an issue with probability distribution distortion. Guidelines are provided for accurate risk assessment in product compliance testing.
Area of Science:
- Metrology
- Probability Theory
- Statistical Analysis
Background:
- Accurate product compliance assessment relies on robust measurement processes.
- Understanding and quantifying the risk of incorrect decisions in measurements is crucial.
- Probabilistic models offer a framework for analyzing measurement uncertainties and risks.
Purpose of the Study:
- To present the testing methodology and results for a probabilistic model of the measurement process.
- To determine the risk of incorrect decisions in product compliance assessment using measurements.
- To address the distortion of probability distribution at the edges of the measuring range within the model.
Main Methods:
- Utilized a probabilistic model for the measurement process.
- Characterized the measurand using a generalized Rayleigh distribution.
- Tested the model in parallel using six distinct risk metrics.
- Employed the Monte Carlo method for comparison and validation.
Main Results:
- Detected an undesirable effect: distortion of probability distribution at the edges of the measuring range.
- Identified specific risk metrics and their performance in parallel testing.
- Developed guidelines for analytical risk assessment aligned with Monte Carlo simulations.
Conclusions:
- The probabilistic model, despite an identified limitation, provides a framework for risk assessment in measurement.
- The study offers practical guidance for improving product quality control and test design.
- Addressing the detected distortion is key to enhancing the model's reliability across the entire measuring range.
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