The below article was published on LinkedIn in 2019.

The following situation may be familiar to quite a number of technical or sales-people in the thermoplastics industry: at some point in a discussion a data sheet comes on the table and your (prospective) customer points at certain values on the sheet. This could happen in a discussion on a new project, a situation where a competitor has come in targeting your project or you are the one trying to come in. Or the discussion starts simply when there is a dispute on a material’s performance.

An interesting discussion might develop that centres around the question of what exactly a data sheet is and what do the values on it represent. In some cases, you realize that there is a misconception on the other side of the table of what a data sheet actually is which requires some clarification.

 The first thing when discussing a data sheet is realizing what it is not. A data sheet is not a specification. It was never intended as such. Therefore, most data sheets will therefore carry a disclaimer that values mentioned are “typical” or “generic” or words of that effect. In a lot of cases the sheet will specifically say that this document is not intended for specification purposes; often though it is in small print and easily overlooked.

Different from a data sheet, a specification will usually mention minimum or maximum values or a range depending on the property mentioned. When comparing the values on a data sheet and the material specification there can be significant differences between the two. And what is on the specification is what the producer of the material commits himself to, not the data sheet.

What is a “typical” value? One could assume this average or the mode of a large number of measurements but in fact often it isn’t. What is entered as a “typical” value is influenced by various factors, some of these will be mentioned below.

Data sheets show in general for most properties a single data point. For instance, the Melt Flow/Volume Index will be mentioned as a single value, sometimes even accurate to one decimal. Anyone however familiar with the test will know that due to natural variations in the material, manufacturing process and test method there is a variation in the values measured. Hence a specification will mention a range instead of a single value to account for these variations. The “typical” value for the MFI/MVI will commonly be the centre point of the specification.

 In addition to the above is the fact that data sheets usually are not colour specific and the effects off pigment loading are not accounted for. Color can have an effect for instance on several properties of a material. A certain base material may display a consistent difference in melt flow when comparing different colours. In effect, a specific grade-colour combination may have a different “typical” (average) value compared to the same grade but in a different colour. A non-specific MFI/MVI specification will be broader than a single-color specification might be, just to cover all the colour variations. The typical value may also differ significantly in these cases.

 Other properties can also be very much affected by colour. Just consider the effect of pigment loading may have on the ductility of a material both in the impact test as well as the actual application. You will rarely find a reference to this on a general data sheet.

 Staying with MFI/MVI testing as an example there is another issue with single point data. This is an example which can be found in many a textbook and isn’t just theoretical. The example often given is in injection moulding a Material A that doesn’t have sufficient flow for a certain application. The customer selects Material B based on the data sheet with a higher MFI (lower viscosity) only to find out that Material B is worse in filling the tool. The reason for this, as you might realize, is that the MVI/MFI test is a single data point and does not account for an effect like shear thinning. Additional multi-point data, in this case melt viscosity curves at different temperatures and shear rates will give a better insight in a material’s behaviour.

 And finally, apart from the technical reasons why data sheet values may differ from actual values there is also a non-technical reason. It’s important to realize that data sheets as such are part of the commercial documentation.

Values mentioned on a data sheet in some cases represent the high (or low) end of the specification rather than the average to match the data sheet of a competitive product. This is done for the reason that started off this article in the first place; people tend to compare materials initially on the basis of data sheets. You don’t want your material to fall out of the boat prematurely while in reality it matches the competitive material.

 Is this necessarily as bad as it looks? It may look at first but consider this: the data sheet is intended to position the material in comparison to other materials. These materials may be the competitor’s material but as a producer you also consider its position in your own portfolio. Most suppliers in a lot of cases also know the “true” performance of their competitor’s material. Nevertheless, you can expect that producers restrain themselves in creating unrealistic expectations for their materials as this is not a sustainable market strategy.

 In the end, it is important for your customer (and yourself!) whether a material performs in the application, not whether the data sheet values are “correct” to the first decimal. The suitability of a material for a specific application should inevitably be verified by additional testing of that application. Material properties of critical importance for the application should be translated to measurable values contained in the specification, especially when it concerns a critical application. But that’s another science altogether…

 The consequence of the above? The technical data sheet for a thermoplastic material should be a starting point of a technical discussion, not the end point. The art is in seeing the whole picture by looking at the details.