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Skip to content * Articles * Downloads * Education * Home * Legal Notice * Links * Privacy Policy * TOS Framework * Home * TOS Framework * Education Menu INTRODUCTORY GUIDE TO SAMPLING THEORY AND PRACTICE OF SAMPLING, TOS STAKEHOLDER REQUEST Stakeholders need reliable data upon which to make decisions - data are requested from an appointed sampling manager. Data representing stationary or flowing heterogeneous materials are requested by different parties and with a multitude of objectives. Stakeholders can be commercial organisations, public authorities or non-governmental organisations. The stakeholder appoints a Responsible Sampling Manager and states acceptable Total Uncertainty thresholds of the requested data and is obliged to make available the necessary resources for appropriate sampling. RESOURCES Financial resources, personnel and equipment. Necessary resources for executing the sampling activity need to be supplied by the stakeholder. This includes the financial resources as well as personnel, equipment and access needed for proper sampling. Minimisation of the Total Uncertainty is directly dependent on the resources invested. DATA QUALITY Data always includes Total Uncertainty. Total Uncertainty comprises of Sampling and Analytical Uncertainty. It is not enough to optimise Analytical Uncertainty only. The Total Uncertainty threshold must include contributions from both sampling and analysis! The Total Uncertainty must be balanced with respect to all necessary costs and resources. MUTotal = MUSampling + MUAnalysis 42ppm +- 8.5ppm +- 1.5ppm IMPLEMENTATION & MANAGEMENT Design of Sampling Procedures & Sampling Error Management. The Responsible Sampling Manager is required to execute the stakeholder’s directive with regards to managing the budget/costs/ resources for obtaining the acceptable Total Uncertainty. Conflicts between these two objectives must be presented to the project owner for decision. The Total Uncertainty and costs may first become available after lot heterogeneity characterisation. The Theory of Sampling offers practical strategic advice on how manage a project in the customer’s interest. Sampling Error Management determines the priorities and tools for all sampling procedures in the following order: 1. Elimination of Incorrect Sampling Errors ISE (unbiased sampling) 2. Minimisation of the remaining Correct Sampling Errors CSE 3. Application of FSE (Gy’s formula) requires complete elimination of ISE 4. Minimisation of Process Sampling Errors The responsible sampling manager is mandated to report the Sampling Quality Objective SQO. Professional sampling mandates disclosure of an SQO as part of documenting compliance with TOS’s demands for representative sampling (Danish Standard 3077 3rd edition). The relevant QO for sampling of stationary lots is the Replication Experiment RE; the relevant QO for sampling of dynamic lots is variographic characterization VAR. ORIGINAL PARTICULATE MASS (LOT) PRE-PROCESSING PRIMARY SAMPLING STAGE SECONDARY SAMPLING STAGE ... ANALYSIS SAMPLING ERRORS 80% 15% 4% 1% Each Sampling Stage has a different impact on the Global Estimation Error. 80% 15% 4% 1% Each Sampling Stage has a different impact on the Global Estimation Error. >The primary sampling stage has by far the biggest impact on the Global Estimation Error, contributing typically 80%. Different errors may occur during the sampling stages. They can be categorized into Correct Sampling Errors, Incorrect Sampling Errors and Process Sampling Errors. 80% 15% 4% 1% Each Sampling Stage has a different impact on the Global Estimation Error. >The primary sampling stage has by far the biggest impact on the Global Estimation Error, contributing typically 80%. Different errors may occur during the sampling stages. They can be categorized into Correct Sampling Errors, Incorrect Sampling Errors and Process Sampling Errors. FSE GSE PTE PPE IDE IEE IPE IWE FSE GSE IDE IEE IPE IWE FSE GSE IDE IEE IPE IWE TSE TAE GEE SAMPLING UNIT OPERATIONS Five Sampling Unit Operations (SUO) cover all necessary practical aspects of representative sampling. Composite sampling Representative Mass Reduction Fractionation Crushing Mixing / Blending GOVERNING PRINCIPLES Six Governing Principles (GP) describe how to conduct representative sampling of heterogeneous materials. FSP SSI PSC PSS LDT LHC FURTHER READING THE TOS FRAMEWORK Theory of Sampling (TOS) is comprised by six Governing Principles (GP) (top grey panel), five Sampling Unit Operations (bottom yellow panel) and eight sampling errors (blue/maroon). Learn more about the framework WHY WE NEED THE THEORY OF SAMPLING Without representative sampling, measurement uncertainty is compromised. Read the article "Why We Need the Theory of Sampling" INTRODUCTION TO THE THEORY AND PRACTICE OF SAMPLING This book presents the Theory and Practice of Sampling (TOS) starting from level zero in a novel didactic framework without excessive mathematics and statistics. It represents 20 years of teaching experience which has developed into a unique conceptual framework. Learn more about the book powered by * Legal Notice * Privacy Policy Copyright © 2020-2024 SIX-S GmbH. All rights reserved. Webdesign & Coding: hotpixels.de