Selective laser melting and post-processing for lightweight metallic optical components
Bibliographic record
Abstract
Industry 4.0 will pave the way to a new age of advanced manufacturing. Additive manufacturing (AM) is one of the leading sectors of the upcoming industrial revolution. The key advantage of AM is its ability to generate lightweight, robust, and complex shapes. AM can also customize the microstructure and mechanical properties of the components according to the selected technique and process parameters. AM of metals using selective laser melting (SLM) could significantly impact a variety of critical applications. SLM is the most common technique of processing high strength Aluminum alloys. SLM of these alloys promises to enhance the performance of lightweight critical components used in various aerospace and automotive applications such as metallic optics and optomechanical components. However, the surface and inside defects of the as-built parts present an obstacle to product quality requirements. Consequently, the post-processing of SLM produced Al alloy parts is an essential step for homogenizing their microstructure and reducing as-built defects. In the current research, various studies assess the optimal process mapping for high-quality SLM parts and the post-processing treatment of Al alloy parts. Ultra-precision machining with single point diamond turning or diamond micro fly-milling is also investigated for the as-built and post-processed Al parts to satisfy the optical mirror’s surface finish requirements. The influence of the SLM process parameters on the quality of the AlSi10Mg and Al6061 alloy parts is investigated. A design of experiment (DOE) is used to analyze relative density, porosity, surface roughness, dimensional accuracy, and mechanical properties according to the interaction effect between SLM process parameters. The microstructure of both materials was also characterized. A developed process map shows the range of energy densities and SLM process parameters for each material needed to achieve optimum quality of the as-built parts. This comprehensive study also strives to reduce the amount of post-processing needed. Thermal post-processing of AlSi10Mg parts is evaluated, using recycled powder, with the aim of improving the microstructure homogeneity of the as-built parts. This work is essential for the cost-effective additive manufacturing (AM) of metal optics and optomechanical systems. To achieve this goal, a full characterization of fresh and recycled powder was performed, in addition to a microstructure assessment of the as-built fabricated samples. Annealing, solution heat treatment (SHT) and T6 heat treatment (T6 HT) were applied under different processing conditions. The results demonstrated an improvement in microstructure homogeneity after thermal post-processing under specific conditions of SHT and T6 HT. A micro-hardness map was developed to help in the selection of optimal post-processing parameters for the part’s design requirements. A study is also presented, which aims to improve the surface characteristics of the as-built AlSi10Mg parts using shot peening (SP). Different SP intensities were applied to various surface textures of the as-built samples. The SP results showed a significant improvement in the as-built surface topography and a higher value of effective depth using 22.9A intensity and Gp165 glass beads. The area near the shot-peened surface showed a significant microstructure refinement up to a specific depth, due to the dynamic precipitation of nanoscale Si particles. Surface hardening and high compressive residual stresses were generated due to severe plastic deformation. Friction stir processing (FSP) was studied as a localized treatment on a large surface area of the as-built and hot isostatic pressed (HIPed) AlSi10Mg parts using multiple FSP tool passes. The influence of FSP on the microstructure, hardness, and residual stresses of parts was investigated. FSP transforms the microstructure of parts into an equiaxed grain structure. A consistent microstructure homogenization was achieved over the processed surface after applying a high ratio of tool pass overlap of ≥60%. A map of microstructure and hardness was prepared to assist in the selection of the optimal FSP parameters for attaining the required quality of the final processed parts. Micromachining to the mirror surface was performed using diamond micro fly-milling and single point diamond turning techniques, and the effect of the material properties on surface roughness after machining was investigated. The machining parameters were also tuned to meet IR mirror optical requirements. A novel mirror structure is developed using the design for additive manufacturing concept additive (DFAM). This design achieved weight reduction of 50% as compared to the typical mirror structure. Moreover, the developed design offers an improvement of the mirror cooling performance due to the embedded cooling channels directed to the mirror surface. A novel mirror structure is developed using the design for additive manufacturing concept additive (DFAM). This design achieved weight reduction of 50% as compared to the typical mirror structure. Moreover, the developed design offers an improvement of the mirror cooling performance due to the embedded cooling channels directed to the mirror surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".