Response Surface Methodology (RSM) Approach for Optimizing the Processing Parameters of 316L SS in Directed Energy...

Area of Science:

• Additive Manufacturing (AM)
• Materials Science
• Process Engineering

Background:

• Directed Energy Deposition (DED) is vital for repairing and manufacturing multi-material components.
• 316L austenitic stainless steel is extensively used across diverse industries including aerospace, biomedical, and energy.
• Optimizing DED process parameters is crucial for consistent quality and defect minimization in 316L steel parts.

Purpose of the Study:

• To investigate the effects of key process parameters on 316L steel fabricated via Laser Engineered Net Shaping (LENS) DED.
• To understand the individual and synergistic impacts of laser power, scan speed, and powder mass flow rate.
• To develop predictive models for layer thickness, density, microstructure, and microhardness.

Main Methods:

• Utilized Response Surface Methodology (RSM) with a Central Composite Design (CCD).
• Systematically varied laser power, laser scan speed, and powder mass flow rate.
• Analyzed the resulting layer thickness, density, microstructure, and microhardness of the deposited 316L steel.

Main Results:

• Developed polynomial empirical models correlating processing parameters with geometric and material responses.
• Quantified the influence of laser power, scan speed, and powder flow on 316L steel's characteristics.
• Established a framework for predicting and controlling DED process outcomes for 316L steel.

Conclusions:

• The study successfully established predictive models for LENS DED of 316L stainless steel.
• Optimized parameter sets can ensure repeatable manufacturing and minimize defects.
• Findings are essential for advancing the application of DED in critical industries.