Establishment of auto-sampling frequency using a two-state Markov chain model
Autor: | Mark Bebbington, R. Kissling, Kondaswamy Govindaraju |
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Rok vydání: | 2017 |
Předmět: |
Markov chain
Computer science Process Chemistry and Technology Foreign matter 010401 analytical chemistry Product type 01 natural sciences 0104 chemical sciences Computer Science Applications Analytical Chemistry 010104 statistics & probability Quality (physics) Volume (thermodynamics) Sampling (signal processing) Statistics Production (economics) 0101 mathematics State markov chain Spectroscopy Software |
Zdroj: | Chemometrics and Intelligent Laboratory Systems. 164:26-31 |
ISSN: | 0169-7439 |
Popis: | Modern bulk material production processes are high volume and high quality processes. The manual grab sampling of bulk material is known to be biased and unrepresentative. Auto-samplers, which are robotic samplers of bulk material in small increments, provide for better representative samples of the production process. The amount and sampling frequency for an auto-sampler can be varied depending on the product type and quality characteristic of interest. This article presents a statistical methodology for determining the sampling frequency for auto-samplers using a two-state Markov chain model for detecting the foreign matter contamination in the production. |
Databáze: | OpenAIRE |
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