Micro material processing creates structures and properties which mostly cannot be inspected without additional optical instruments. In many cases, this prevents quality control during manufacture as microscopes are needed to analyse the process result. Such high resolution microscopes cannot be embedded into manufacturing systems for technological and mainly economic reasons. What can be done is the determination of the machine status to adjust setting parameters as an adoption to changed boundary conditions. INSPECT aims to develop an integrated sensor grid for micro machining of filters which is able to monitor laser characteristics, machine conditions and deduce a statement about the process result.
The filtration market as a multibillion dollar market needs new technologies to produce finder filters at affordable prices. Since there exists an increasing demand from emerging countries industry needs to respond with increasing level of automation in the near future. Machines that can adapt their setting parameters based on the determination of boundary conditions may perform at a much more constant level. This enables the production of new filters with enhanced technological features to remove unwanted content and for example make water clean water. The integration of a multitude of sensors to a grid that extracts information about the machine conditions and an ICT based proposition on how to adapt accordingly to meet the required product quality may be seen as a template to other machines and industries. Unlike electroforming, which is the most commonly used method for the production of metal sieves, laser drilling completely avoids the production of chemical waste.
The INSPECT sensor grid showed that with the use of the collected data the manufacturer is able to detect deviations from the stable process and relate those to changes in the state of the machine itself, the laser source or even external factors. With the sensor grid users will not only gain a better understanding of the laser process they are using but also of the laser processing machines own life.
Analyzing the collected data furthermore helps to identify critical process parameters and environmental influesces, improve process parameters and reduces the time needed to setup a new process. In combination with the data from the process monitoring module product quality can validated directly in the production machine.