Predictive Maintenance – Effective Residue Management through Integrated Filter Monitoring

Optimum soldering results depend not only on the actual melting process of the solder paste. Cooling the assembly to be soldered plays an important role in soldering highly complex electronic components. The filter monitoring – including volume flow control integrated in the convection soldering systems of the Vision series from Rehm Thermal Systems – ensures effective residue management and constant cooling capacity, thereby supporting stable and safe performance of the soldering process.

When the solder paste melts inside the process chamber, process gases are produced which cause contamination of the cooling modules and the fine filter. The volume flow of the cooling process, which should be as constant as possible, is reduced by these contaminants. Less volume flow means less cooling capacity at the same time, which can lead to an increase in the outlet temperature or to a changed cooling gradient at the assemblies. However, for a safe and stable process, the correct run-out temperature and a constant cooling gradient of the soldered assembly are of great importance. 

The filter monitoring with active readjustment automatically detects via the integrated control system when the volume flow falls below the level individually set by the customer to meet his production requirements. This is an indication that the filter is about to be changed. Until this change is made, the system automatically readjusts the volume flow by means of active readjustment in order to continue cooling the assemblies within the specified process window by increasing the cooling capacity. For this purpose, the set gas flow rate in the cooling zones is continuously compared with the value actually determined. 

The filter monitoring with active readjustment thus guarantees a high level of process reliability and ensures an optimum reflow soldering process with constant flow conditions. In addition, the data from the filter monitoring with active readjustment can be collected and used to predict the next filter replacement with external data analysis programmes.