Representative Sampling in Science, Technology and Industry Theory, Practice, Case Histories, Exercises

A comprehensive and easy-to-read introduction to sampling, both for scientists in academia and industry, helps to efficiently choose reliable and representative samples. A series of case studies show how the theories are applied in the laboratory.
Following an introduction and a look at the theory of sampling, the book goes on to deal with representative mass reduction and a survey of existing techniques, equipment and procedures. Further sections discuss process sampling and the planning and optimization of sampling. Finally, a number of illustrative case studies from industry and the laboratory are included. The whole is rounded off by an extensive set of practical exercises. An invaluable aid for all those working in analytics, production control/process establishment, and quality control.

Kim H. Esbensen is Research Rrofessor at GEUS (National Geologic Survey of Denmark and Greenland), Professor at Aalborg University: Head of ACABS research group (Applied Chemometrics, Analytical Chemistry, Applied Biotechnology, Bioenergy & Sampling) and external professor at Telemark University College, Norway. 2005-2010 he was Professor Extraordinary at the Institute of Wine Biotechnology, Stellenbosch University, South Africa. He has worked within chemometrics for 25 years with a main focus on representative sampling and validation since 1996. In 2003 he organized the 1st World Conference on Sampling and Blending (WCSB1). He has authored more than 150 scientific publications including one textbook on chemometrics, currently in its 6.th edition. His research interests cover the theory of sampling (TOS), Process Analytical Technology (PAT), chemometrics and representative sampling in all major industrial sectors. Prof. Esbensen is on the editorial board and serves as reviewer at several international journals.

Pentti O. Minkkinen is Emeritus Professor of Inorganic and Analytical Chemistry at Lappeenranta University of Technology, Finland. His research interests include chemometrics, especially estimation of the uncertainty of analytical measurements including sampling. He has served as Editor in Chemometrics and Intelligent Laboratory Systems years 2001-2007. He has been Associate Member of Analytical Chemistry Division in IUPAC 2006-2009, Member of EURACHEM Working Group preparing the guide "Estimation of Uncertainty Arising from Sampling". He has been teaching sampling for more than 25 years at university level. He has received The Kowalski Prize in Chemometrics 2002, Herman Wold Gold Medal in Chemometrics, 2007and Pierre Gy Sampling Gold Medal, 2007.

Both authors are founding members of the International Sampling and Blending Forum (ISBF) and serve as standing members of the scientific committees of the World Conferences on Sampling and Blending (WCSB: 2003, 2005, 2007, 2009).

Preface/Acknowledgements
INTRODUCTION
A scope-setting example: sampling variance
Sampling Objectives;
Sampling Contexts
Origin of Sampling Errors
Systematic of Sampling Errors (Introduction)
Definitions;
Terminology;
Vocabulary
Theory of Sampling (TOS) (Introduction)
THEORY OF SAMPLING (TOS)
Lot Dimensionality
Heterogeneity
Sampling Correctness;
Sampling Incorrectness
Fundaments Sampling Principle (FSP)
TOS¿ preventive paradigm
REPRESENTATIVE MASS REDUCTION
Fundamentals of Representative Mass Reduction
SAMPLING TECHNIQUES, EQUIPMENT AND PROCEDURES
0-DIM SAMPLING
0-D Sampling Errors (Overview)
0-D Sampling Unit Operations (SUO)
Relative Sampling Variability (RSV): a measure of effective sampling variance
Seven Sampling Unit Operations (SUO)
1-DIM SAMPLING (process sampling)
1-D Sampling Errors (Introducing Process Sampling Errors)
1-D Heterogeneity
Variographic characterisation
TOS vs. Geostatistics
Alternatives to Variography
Bed Blending
PLANNING AND OPTIMISATION OF PRACTICAL SAMPLING
Sampling optimization;
Sampling plans;
Sampling logistics
Auditing Sampling Systems
Regulatory Issues;
Sampling Standards;
Sampling responsibility
SAMPLING: HALL OF FAME (successful case studies)
Industry
Laboratory
Field Sampling
SAMPLING: HALL OF SHAME (catalogue of Non-representative Sampling)
HISTORY OF TOS
History of TOS: TRIBUTE TO PIERRE GY
EXERCISES
Practical Exercises
APPENDIX:
TOS: Relationships to Statistics, Geostatistics, Measurement Uncertainty (MU)
Proportional Sampling (Eliminating Weighting Error)