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The main application of surface analytical methods is without doubt that of failure analysis. Types of paint failure are spots, adhesion, wetting and flow problems, craters and stains. Very often, this issue demands the detection and identification of very low quantities of paint components and contaminants in a small sample area (microanalysis). For these tasks, surface analysis provides an extensive set of instruments. But that is not the only prerequisite for a successful problem troubleshooting. Therefore, the author wants to point out which steps are also important before diving deep into the analysis of different failure types: If a production fails and one does not know why, the urgency of beginning a journey of knowledge that makes the mystery familiar is obvious.

In order to understand

 how a coating product works

 why it fails

 how it is composed

 what can be done if an unexpected coating result occurs

 how the quality of raw material can be controlled

 how my products can be tested…

facts and data are necessary. And in mind: „Furious activity is no substitute for understanding!”

Figure II.1: Powder coating booth

Especially, when it comes to paint failure analysis people tend to rely on conjectures more and more, rather than focussing on facts. But only facts are reliable.

This book presents various examples of “real world” challenges that have occurred in this or a similar way in the author's professional experience over the last twenty-five years, happening somewhere every day, and shows the ways to solve certain problems. Attention is focused on the analysis of paint defects, as well as on raw material control, process control and production monitoring. It is important to notice that the methods go beyond standard paint quality tests and can be adjusted to the actual situation which makes them flexible for any kind of upcoming problem.

If a solution for a problem is based on science it works, if it is based on assumptions it often leads into dead ends, costs a fortune and wastes resources. To achieve facts and data you need machines, analytical equipment and manpower, but it pays off. Facts and data do not solve problems. They must be combined with knowledge and expertise. But if these requirements are fulfilled, the right path is under your shoes.

The methods described here, serve as a tool to elucidate the root cause of the failure. They should enable the optimization and improvement of production processes which would otherwise afford a lot of money and time for try and error without having these techniques.

On the other hand, the facts generated by measurements and analyses are sometimes used to “share” the costs of production failures with the suppliers.

The scientific methods are an important and versatile tool to understand and solve problems, but they are not the universal remedy. If a coating failure happens, it is a good choice to think about the procedure how to solve it before starting into action.

Failure analysis includes the search for the cause of a malfunction during production of coating materials as well as the investigation into coating application failures. A paint crater observed at the end of the production line of a product, for example, can be caused by:

 coating material production failures (wrong choice of paint components, mixing errors)

 storage failures

 application failures

 insufficient cleaning and pretreatment of the raw product

Therefore, a comprehensive search must cover all aspects from raw materials to the finished product. The challenge is the total amount of substances that have to be detected and identified. For example, one droplet of a fluorocarbon lubricant of 10 μm diameter can be the cause for a paint crater. This is a total of a few nanogram of material which has to be found and identified. It is obvious that classical low-cost analytical techniques of routine laboratory processes do not have the power to achieve this. In fact, this task asks for “heavy machinery” like e.g. TOF-SIMS and highly educated manpower. But it is worth it, because a problem solution is nothing without understanding the problem.

The efficient failure analysis requires:

 the appropriate design of experiment

 the appropriate sampling

 the appropriate instrumentation

 a qualified and educated evaluation of the data and

 last but not least the translation and transfer of the achieved knowledge into the process

If one of these steps fails, the whole analytical process is worth for nothing. These issues will be described in detail in the following chapters.