Sampling may be mandatory for safety or environmental reasons. It may be because the value of a sale needs to be determined or to provide important data for investments. Whatever the reason, an incorrect sample will come at a risk. Only the person that relies on sampling data can imagine what the potential cost of such risk is.Sampling itself has a cost too; the direct cost of a quality control department and indirect cost for interrupting a process, such as stopping a conveyor belt during loading. If all material is the same then only one small sample is enough. But if all the material is different, then a very large sample must be tested; in the conveyor belt scenario it must be stopped very frequently and the associated cost will be high.A good sampling plan finds the proper balance between risk and cost. A good sample must be small enough to handle yet large enough to be representative for what information is required. All good samples have three things in common: there was proper access to the material the sampling tool allowed equal probability of particles being selected nothing was disregarded, everything was included._x000D_
This too is the core of Gy's ideal sampling scenario, where all particles have the same probability of being selected and included in the sample. There is risk of bias when part of a lot is excluded from the sample. Extra care is needed when sampling particularly heterogeneous, segregated or layered materials. The sampling tool should never systematically leave out a portion; it shall not push aside large or hard particles. Wet samples shall not stick to the sampling tool. This extends to sample preparation too when reducing particle size and dividing the sample in the process.CITATION:Vogel, D A, 2017. Access, select, include - a review of the commercial sampling of traded bulk commodities in the context of Gy's Theory of Sampling, in Proceedings Eighth World Conference on Sampling and Blending, pp 367-378 (The Australasian Institute of Mining and Metallurgy: Melbourne).