Increased focus on reduction of impact on the environment has put the aspect of remanufacturing in the spotlight, and remanufacturing of high-value engineering components is gradually becoming a mainstream practice. Out of different alternatives, laser-based deposition has been the central choice for remanufacturing, thanks to its accuracy, and precision. However, considering the complex process physics involved in laser-based remanufacturing processes, it is essential to establish the reliability of the process so that certifiable remanufactured parts can be produced. This work provides a comprehensive analysis of the issues encountered during laser-based remanufacturing, and the different approaches to address them. Apart from covering the state-of-the-art of remanufacturing by laser-based deposition, this article also discusses tools like deep learning, and digital twin which are still in their early phases in terms of applications in the remanufacturing domain.

Addressing the challenges in remanufacturing by laser-based material deposition techniques

Recently, the commercialization of hybrid machine tools that combine directed energy deposition (DED) additive manufacturing (AM) technology and subtractive manufacturing (SM) has rapidly progressed. This technology trend has been developed to meet the market demand for processing quality (precision) and productivity, and to produce products such as lightweight parts, and complex and special functional parts, as well as to facilitate mold production and part repair. Compared to SM technology, metal AM technology has limitations in terms of surface quality and shape accuracy. Therefore, post-processing is necessary for the AM output. Laser-assisted machining (LAM) is an innovative hybrid technique in which surface quality and productivity can be improved by enhancing the machinability of difficult-to-cut materials. LAM studies have mainly been performed on titanium alloys, nickel based alloys and ceramic materials. However, except for ceramics, no high-strength material studies have been conducted to analyze the LAM process machining characteristics of workpieces fabricated by AM process. Therefore, in this study, LAM is applied to post-processing of output fabricated by AM of Ti-6Al-4V. DED device was developed using metal powder feeder and a laser. The Ti-6Al-4V workpieces were successfully fabricated through many tests. The cutting depth for LAM was selected through thermal analysis for LAM of the fabricated workpiece. Compared to the case of traditional machining without preheating, machining characteristics in LAM experiments were analyzed and property testing was performed.

Laser-Assisted Machining of Ti-6Al-4V Fabricated by DED Additive Manufacturing

Directed energy deposition (DED) provides a promising additive manufacturing method to fabricate and repair large metallic parts. However, it may suffer from excessive heat accumulation due to a high build rate, particularly during a wire feeding-type DED process. The implementation of interpass time in between two depositions of beads plays an important process role to passively control the interpass temperature. In this study, a method to estimate the proper interpass time using regression analysis from heat transfer finite element analysis is proposed for maintaining the interpass temperature during a wire feeding-type DED deposition of a planar layer. The overlapping beads of a planar layer are estimated using a polygonal-shaped bead profile in the finite element model. From the estimated proper interpass time, a selected proper interpass time scheme (PITS) is suggested for practical implementation. The selected PITS is applied in a thermo-mechanical finite element model to evaluate the temperature distribution and its effects on the depth of the melt pool, the depth of the heat-affected zone (HAZ), displacement, and residual stresses. By comparing the predicted results with those using a constant interpass time scheme (CITS), the selected PITS shows better control in reducing the depths of the melt pool and HAZ without severely inducing large displacement and residual stresses.

https://www.mdpi.com/1996-1944/13/21/4935/pdf

Estimation Method of Interpass Time for the Control of Temperature during a Directed Energy Deposition Process of a Ti-6Al-4V Planar Layer.

Laser-based directed energy deposition (L-DED) is a rising field in the arena of metal additive manufacturing and has extensive applications in aerospace, medical, and rapid prototyping. The process parameters, such as laser power, scanning speed, and layer thickness, play an important role in controlling and affecting the properties of DED fabricated parts. Nevertheless, both experimental and simulation methods have shown constraints and limited ability to generate accurate and efficient computational predictions on the correlations between the process parameters and the final part quality. In this paper, two data-driven machine learning algorithms, Extreme Gradient Boosting (XGBoost) and Random Forest (RF), were applied to predict the tensile behaviors including yield strength, ultimate tensile strength, and elongation (%) of the stainless steel 316L parts by DED. The results suggest that both models successfully predicted the tensile properties of the fabricated parts. The performance of the proposed methods was evaluated and compared with the Ridge Regression by the root mean squared error (RMSE), relative error (RE), and coefficient of determination (R2). XGBoost outperformed both Ridge Regression and Random Forest in terms of prediction accuracy. 

/pdf/prediction-of-mechanical-behaviors-of-l-ded-fabricated-ss-1k9l0avm.pdf

Prediction of mechanical behaviors of L-DED fabricated SS 316L parts via machine learning

In this work, the manufacture of thin walls with sharp corners has been optimized by adjusting the limits of a 3-axis cartesian kinematics through data recorded and analyzed off-line, such as axis speed, acceleration and the positioning of the X and Y axes. The study was carried out with two powder materials (SS316L and IN718) using the directed energy deposition process with laser. Thin walls were obtained with 1 mm thickness and only one bead per layer and straight/sharp corners at 90°. After adjusting the in-position parameter G502 for positioning precision on the FAGOR 8070 CNC system, it has been possible to obtain walls with minimal accumulation of material in the corner, and with practically constant layer thickness and height, with a radii of internal curvature between 0.11 and 0.24 mm for two different precision configuration. The best results have been obtained by identifying the correct balance between the decrease in programmed speed and the precision in the positioning to reach the point defined as wall corner, with speed reductions of 29% for a programmed speed of 20 mm/s and 61% for a speed of 40 mm/s. The walls show minimal defects such as residual porosities, and the microstructure is adequate.

Optimization of Thin Walls with Sharp Corners in SS316L and IN718 Alloys Manufactured with Laser Metal Deposition

In the directed energy deposition (DED) process, the scanning speed around sharp corners decreases from the command speed to a capable-curve speed. At a constant powder feed rate, the reduction in the scanning speed causes oversized beads owing to the increased deposition amount per unit time. In this study, the excessive deposition at the corners is controlled by the tailored setting of the corner scanning speed. The proposed control method enables fabrication of an equal-height rectangular corner geometry using the DED process. The bead height along the rectangular corner is controlled to be equal to those of the linear segments. For the sensitivity analysis of the process parameters, the effect of the scanning speed, laser power, and powder feed rate on the bead deposition was investigated experimentally. To generate smooth and equal-height deposition, a corner scanning-speed control algorithm was applied. Results showed that over deposition occurred near the corner section due to the scanning speed drop but after applying the controlled scanning speed, over deposition was decreased. In addition, a three-dimensional thermo-mechanical finite element simulation was performed to investigate the temperature field and induced residual stresses.

Control of Directed Energy Deposition Process to Obtain Equal-Height Rectangular Corner

Analysis of Induction Heater System Considering Electromagnetic Field and Thermal Characteristics of Motor Rotor Bearing

Measuring Mechanism of Automatic Electric Motor Joint Inspection Equipment for Automobiles

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Won Ha

Author Tools

Chat about Author

Papers

Control of Directed Energy Deposition Process to Obtain Equal-Height Rectangular Corner

Analysis of Induction Heater System Considering Electromagnetic Field and Thermal Characteristics of Motor Rotor Bearing

Measuring Mechanism of Automatic Electric Motor Joint Inspection Equipment for Automobiles