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  • Writer's pictureMariam Mir

Additive Manufacturing Simulation - Process Map Generation

In metal Additive Manufacturing, a Process Map is a graphical representation of the relationship between power and speed settings during the manufacturing process. It involves plotting different combinations of power and speed on a diagram to understand their impact on the quality of the manufactured part and it is used to analyze and optimize laser-based additive manufacturing processes.


Sample Process Map


In a Process Map, the power level of the laser is plotted on the vertical axis, while the scanning speed of the laser beam is plotted on the horizontal axis. By varying these parameters, one can observe how they affect the quality and characteristics of the printed part.


The Process Map can identify zones where non-optimal combinations of power and speed may lead to specific issues, such as keyholing, balling, or lack of fusion. For example, keyholing occurs when excessive power or slow speed causes the laser to penetrate the material, leaving a keyhole-shaped void. Balling refers to the excessive melting or pooling of material, resulting in an uneven surface. Lack of fusion indicates inadequate bonding between the layers, leading to weakened structural integrity.


The simulation software AdditiveLabRESEARCH can create such Process Maps automatically; utilizes simulation and modeling techniques by incorporating material properties, laser parameters, and other relevant factors. This is an efficient tool in addition to experimental methods for several reasons. Firstly, it saves time and cost by reducing the need for extensive trial and error experiments. Instead of physically testing different combinations of power and speed, the software can quickly simulate and evaluate various scenarios, providing insights into the optimal process parameters. Additionally, using the FEM-based software allows for a deeper understanding of the underlying physics and mechanisms involved in additive manufacturing. It enables the identification of critical process variables and their effects on the final part quality. This knowledge can then be used to refine the manufacturing process, improve efficiency, and minimize defects.


To learn more on how AdditiveLab process simulation can help you predict melt-pool formations and guide you during the optimization of your process parameters, reach out to the AdditiveLab team via our Contact page.

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