Abstract
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.
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