Simulation-Driven Process Maps for Metal Additive Manufacturing for Advanced Alloys

Developing reliable process parameters in metal additive manufacturing is one of the most critical and resource-intensive tasks in production and qualification workflows. Engineers must understand how combinations of laser power, scan speed, hatch spacing, and layer thickness influence key outcomes such as melt pool stability, part density, residual stress, and defect formation. For every new material or geometry, this process can be both time-consuming and expensive.

Simulation-driven process maps offer a smarter way forward. At AdditiveLab, we provide engineers with tools to generate predictive process maps using high-fidelity thermal simulations. These maps visualize how specific process parameters affect thermal behavior and mechanical responses in the material. The result is a more informed, faster, and cost-effective approach to developing robust AM processes.

AdditiveLabRESEARCH simulates a matrix of laser power and scan speed combinations.

What Is a Simulation-Driven Process Map?

A process map is a visual tool that links combinations of input parameters with predicted outcomes. The most common example is a laser power versus scan speed map. For a given set of conditions, such as spot diameter, hatch spacing, and layer thickness, the map helps engineers understand how variations in power and speed affect the process.

Engineers can simulate and plot a matrix of laser power and scan speed values. For each combination, AdditiveLabRESEARCH software predicts key outputs such as:

• Melt pool depth, width, and length

• Peak temperatures and cooling rates

• Temperature gradients that affect microstructure

• Accumulated thermal exposure across layers

• Risk of keyholing or lack of fusion

Simulation-driven contour plots showing how melt pool volume, shape, and peak temperature vary with laser power and scan speed in LPBF for processing Al6061. These results support process map development for parameter optimization.

This results in a process map where safe, unstable, and high-risk zones are clearly identified. The map can guide parameter selection before any physical build takes place.

This map shows how laser power and scan speed affect melt pool quality during LPBF of AL6061. Green areas indicate optimal process settings, while red zones highlight high-risk regions. The overlaid contours mark thresholds for acceptable and poor melt pool behavior, helping guide parameter selection and process stability.

Why This Matters for Advanced Alloys

Simulation-driven process maps are particularly valuable when working with complex materials that are sensitive to thermal and mechanical conditions. For example:

• Haynes 230 is a high-temperature alloy used in aerospace and nuclear applications. It is prone to liquation cracking, which can be predicted by identifying heat-affected zones exceeding critical temperature thresholds.

• GRCop-42 is a copper-based alloy used in rocket engine components. Its high thermal conductivity demands precise energy control to achieve full fusion. Simulations help determine the optimal balance between power and speed.

• Scalmalloy is a high-strength aluminum alloy developed for aerospace structures. It is sensitive to porosity and requires fine-tuning of energy input to maintain consistent melt pools.

• Al6061 is widely used but difficult to print due to its tendency for hot cracking. Simulations highlight parameter combinations that minimize stress and promote uniform solidification.

Each of these materials benefits from a predictive approach that helps engineers understand how thermal behavior and process parameters interact.

Supporting Smarter Experimentation

Physical testing is essential for final validation, but simulation provides direction. It allows teams to:

• Eliminate unpromising parameter sets early

• Focus experiments on a narrow, high-potential region

• Reduce the number of physical builds required

• Generate layer-by-layer thermal and mechanical histories

• Link simulation data to microstructure models or defect predictions

This results in faster iteration, lower cost, and more efficient use of machine time and material.

A Tool for Qualification and Production Readiness

In regulated industries such as aerospace, defense, and nuclear energy, the ability to document and justify process development decisions is vital. Simulation-driven process maps support traceable and reproducible parameter development workflows. They also provide a strong foundation for scaling up production or transferring parameters between machines.

With AdditiveLabRESEARCH, engineers can simulate complex scan strategies, use calibrated material models, and generate detailed reports that support qualification requirements.

Conclusion

Simulation-driven process maps are transforming how engineers approach parameter development in metal additive manufacturing. They provide the clarity and confidence needed to move quickly, reduce risk, and achieve high-quality builds using even the most challenging materials.

At AdditiveLab, we believe every AM process should begin with understanding. Process maps are not just visual tools. They are engineering strategies that guide smarter decisions from the start.

If you are developing new parameters, qualifying a critical part, or exploring a novel alloy, simulation can give you the insight you need to move forward with confidence. For more information on making process maps, contact us.