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compared to the range of applied current densities, metal ion mass transfer limitations can be neglected, simplifying the analysis. e digital twin is constructed by integrating the following components (Figure 2): • Plating line infrastructure: e model can account for both horizontal and verti- cal plating lines, adapting to various manu- facturing setups • Plating tank configuration: Key aspects include tank dimensions, plating package layout, types of anodes, anode-to-anode spacing, anode-to-cathode spacing, and the presence and positioning of screens, current thieves, and auxiliary anodes • Plating bath details: e model considers ohmic drop effects in the electrolyte, influ- enced by electrolyte conductivity, as well as the relationship between polarization and current density at the electrodes. Acid copper bath characteristics are measured using a Rotating Disc Electrode (RDE) for accurate input data. • Process parameters: ese include depo- sition time and the type of current pro- gram (e.g., direct current (DC) or pulsed current) used during electroplating • PCB job-specific data: e design details of the specific PCB board and panel layout undergoing processing are factored into the model in a Gerber format. e simulation outputs the current density distribution, j, across the electrodes. Using Faraday's law, the layer thickness distribu- tion, Δd, on the cathodes is calculated as: zation of plating processes to achieve precise layer thicknesses and high-quality outcomes. Results and Discussion e simulations provide detailed visualiza- tions of current density distribution and cop- per layer thickness across all active PCB sur- face areas, effectively pinpointing potential risk zones for over-plating and under-plating. As illustrated in Figure 2, the FEA results, based on input data representing the actual setup of the copper electroplating process, enable the iden- tification of these critical areas on the plated PCB panels. Regions with copper layer thick- nesses below the minimum required threshold are highlighted in blue, indicating zones at risk of underplating. Conversely, areas where cop- per thickness significantly exceeds the maxi- mum required limits are marked in red, signal- ing potential overplating concerns. is pro- active approach of upfront as-is plating pro- cess performance analysis allows for the early identification of inefficiencies and irregularities within the process. To view the full paper, click here . PCB007 References 1. "Methods for achieving high speed acid copper electroplating in the PCB industry," by A.J. Cobley, D.R. Gabe, Circuit World 27, p. 19-25, 2021. 2. "Ultra-uniform copper deposition in high aspect ratio plated through-holes via pulse-reverse plating," by W. Ge, W. Li, R. Li, Y. Dong, Z. Zeng, H. Cao, L. Yu, Z. Wen, J. He, Coatings 12, p. 995-1010, 2022. 3. Digital Twin Concept in Cu Electroplating Pro- cesses, by A. Franczak, PLUS 8, p. 1033-1041, 2023. 4. "Beyond Design: Copper Pours in High-speed Design," by Barry Olney, Design007 Magazine, 2022. 5. "Effects of etching process: Inaccuracy in the malfunctioning level of PCB circuits—a simulation- based analysis," by H. Aregawi, M. Abdo, Journal of EEA 28, p. 53-63, 2020. 6. "A performance simulation tool for bipolar pulsed PCB plating," by G. Nelissen, B. Van den Bossche, L. Wanten, ECWC 10 Conference at IPC Printed Circuits Expo, 2005. 7. "Validation of new generation tooling concept for electroplating of copper on printed circuit boards," G. Nelissen, A. Rose, P. Vieira, B. Van den Bossche, Plat- ing & Surface Finishing, p. 36-41, 2010. ∆d = (M ∆t j) (ρ z F) where M is the atomic weight of the metal, Δt is the deposition time, ρ is the metal's den- sity, z is the number of electrons exchanged in the metal deposition reaction, and F is Far- aday's constant. This detailed simulation pro- vides critical insights into the uniformity of copper deposition and supports the optimi- 82 PCB007 MAGAZINE I JUNE 2025