Particle size distribution is dependent on principle and method of measurement. Also, even with analyzers that use the same principle of measurement, perfect transferability of data cannot, in reality, be expected.

Though "absolute" or "true" particle size distribution does not objectively exist, it sometimes exists subjectively or as an "impression or preconceived notion" in people's minds.

For example, the following three major cases can be considered:

1) Specific principles/methods or manufacturers/models are considered to be absolute.
2) Correct particle size distribution is determined by majority decision.
3) Particle size distribution as a "conviction" not based on measurement

The first case can have inevitability if not objectivity.

When a model made by a specific manufacturer gain ground in a specific field or region, that, as it were, becomes the standard, and creates a situation where it becomes extremely difficult for subsequent manufacturers and models to make inroads.

There may be a strong tendency for manufacturers, who buy powder raw materials to be turned into products, to buy the same analyzer as the one used by the manufacturer of those raw materials when they buy a particle size analyzer.

Inversely, when the manufacturer who makes products already has a particle size analyzer and is influential on the market, the manufacturer who makes raw materials for those products sometimes has no other option but to follow suit and buy the same model.

By repetition of this process, specific manufacturers to all intents and purposes become the standard in specific fields (i.e. sectors of industry) or regions where these fields (sectors) concentrate.

However, note, that quite a long time is required until effective standards take root, and that, if the problem of transferability of particle size distribution data is taken into consideration by upgrading or replacement of models (i.e. by the introduction of new models) from even the same manufacturer, there is no objectivity as a standard and the only thing that remains is the manufacturer's name.

Ironically, subjective "impression or preconceived notion" apparently becomes stronger the less objectivity there is and the "effective standard" sometimes transforms into an "absolute" particle size distribution.

The second case is "majority decision." In this case, measurement targets (samples) believed to be identical are measured on several analyzers and the correct particle size distribution is determined by majority decision.

For example, if measurement is performed using five models of analyzers and relatively close measurement results (i.e. particle size distribution) are output by three of these models, then these results are considered to be the correct particle size distribution, and the measurement results from the remaining two models and those analyzers themselves are regarded as being inaccurate. If the sample and measuring conditions used are different, combinations of majority camp and minority camp models also might differ. The fact that an analyzer is in the minority camp is no basis for it being regarded as inaccurate. If a model is intentionally targeted, it would be possible to show off a specific model as being in such a minority camp.

The third case is the most awkward, "conviction."

People say that "Measurement results such as this for this product (powders) ought to be obtainable since it was made to produce this kind of particle size distribution." They also say that "Products (powders) that we made ourselves ought to have much smoother distribution." And, some will also assert, for two or more measurement targets (samples), that "Products ought be in the expected size relationship since they were made by altering conditions like this."

If "conviction" or "belief" is too strong in situations like this, the user might seek out an analyzer that is capable of providing measurement results (particle size distribution) faithful to or more inclined towards these feelings. Naturally, since logical basis sometimes also exists, I cannot generalize that this is not an appropriate method, yet there is also no guarantee that the analyzer (model) sought after by the user is correct.