Numerous articles and a few books have been written about sampling of particulate materials before this third edition. Then, why select Pierre Gy’s theory, Visman and Ingamells’s works? As a Pierre Gy’s Gold Medalist I want to bring my knowledge and experience on the Theory of Sampling (TOS) and contribute to making sure TOS grows in a rational way, in spite of its many detractors. Looking at comments made around the world, it is clear that many statisticians and empiricists promoting “Measurement of Uncertainty” (MU) strongly believe that TOS is something they can live without. Such antagonism is misplaced, unjustified and very unfair. I also strongly believe the MU promoters, who most of the time, are more comfortable with J. Visman’s work, need TOS, and vice versa. In this third edition of my book a special effort is made to integrate J. Visman and C. O. Ingamells’s works into the TOS and create a unified foundation that may help to create better sampling standards. <...>

Кратко изложены основные процессы и аппаратура опробования и контроля на обогатительных фабриках. Описаны способы, правила и системы отбора, транспортирования и обработки проб.
Подготовлено по дисциплине «Опробование и контроль процессов обогащения» и предназначено для студентов специальности 21.05.04 «Горное дело», специализации 21.05.04.06 «Обогащение полезных ископаемых».
Печатается по решению редакционно-издательского совета Кузбасского государственного технического университета имени Т. Ф. Горбачева.

What is the quality of the sample and assay data? Am I confident enough in my data to be able to make a potentially costly decision? These are the types of questions which should be asked when dealing with assay data.

Отражены теоретические основы опробования полезных ископаемых. Представлены типы, виды и способы опробования, а также способы оценки представительности и достоверности опробования. Приведены основные требования к мероприятиям контроля отбора, обработки проб и проведения последующих лабораторных исследований.

Для студентов специальности 21.00.00 «Прикладная геология», может быть использовано при подготовке студентов других специальностей геологического профиля.

Resource modelling is a complex process involving different specialists with relevant experience using a multi-disciplinary approach and the best available technology and reviews by independent auditors. The reliability of the final resource estimate is highly dependent on the quality control exercised at each stage of the process. At each step in the resource modelling process it is necessary to define the specific objectives, the methodology proposed to achieve those objectives and to establish a set of checks and validation tools to assess the effectiveness of the proposed methodology. Designation of responsibility and authority for meeting these objectives must also be clearly identified. External audits must also be incorporated to review and validate the implementation of new procedures.

Resource modelling is the basis for any economic appraisal of a mining project and includes a number of steps from data acquisition and validation to resource reporting, classification, and risk analysis

Control of analytical data quality is usually referred to in the mining industry as Quality Assurance and Quality Control (QAQC), and involves the monitoring of sample quality and quantification of analytical accuracy and precision. QAQC procedures normally involve using sample duplicates and specially prepared standards whose grade is known. Numerous case studies indicate that reliable control of sample precision is achieved by using approximately 5% to 10% of field duplicates and 3% to 5% of pulp duplicates. These duplicate samples should be prepared and analyzed in the primary laboratory.

The status of sampling practices in the Gold Mining Industry in Africa was determined as an initial step in a process to standardise sampling practices in the Mining Industry. Several mines, metallurgical plants and laboratories were visited and the status of equipment, standards and procedures were rated to determine the potential influence of the relevant sampling errors on each component of the particular sampling system.