Taking electroplating processes to the next level via Computer Aided Engineering approach

Electrochemical deposition of metal coatings has many advantages, e.g. low-cost, thickness of the coating can be controlled by adjusting the electrochemical parameters, higher deposition rates in comparison to physical deposition methods can be achieved. Nevertheless, a common obstacle in an efficient electroplating process is a complex geometry of the parts to-be-plated. For instance, in case of Zn-Ni coatings deposited onto parts with important 3D topology of the surfaces subjected to plating, severe problems with the non-uniformity of current density, layer thickness distribution and deposit composition can be expected. This cannot be simply solved by changing the electrodeposition parameters: the over- and underplated areas, even if in different dimensions, will still exist within the part. Therefore, a dedicated conformal tooling structure must be designed in order to rule out the encountered non-uniformities.

Standard practice applies empirical and “by experience” methods to rule out the non-uniformity issues, taking months for tooling design&manufacturing and wet test runs, and even then, process performance might be still surprising. This can be changed when relying on a Computer Aided Engineering (CAE) approach which allows to assess process risk issues and eliminate them before any actual process will take place:

CAE approach uses a virtual mock-up of the real-life plating line infrastructure in order to provide information on the current density and metal layer thickness distributions over a 3D computer model of the part to-be-plated. Thus, detail overview on the low and high current density areas is obtained upfront and can be quickly addressed by developing a proper mitigation strategy composed of adequate active tooling components and process parameters. The entire guess-work in this case, is replaced with the exact know-how on the process and right-first-time production achieved within days rather than extensive weeks.