Direct energy deposition by laser (DED-LB) of Ti-6Al-4V alloy wire Open Repository

Direct energy deposition by laser (DED-LB) of Ti-6Al-4V alloy wire Dataset This dataset collects data from various test coupons, where linear tracks were produced by direct energy deposition by laser (DED-LB), using Ti-6Al-4V titanium alloy wire as feedstock material. Each DED-LB corresponds to a different set of process parameters: laser power, process speed, and wire speed. The aim is to provide significant data on the DED-LB process applied to the additive manufacturing (AM) and repairing of aeronautical components. These collected data includes the process parameters for every DED-LB track, the real time instant value of these process parameters during processing, the melt pool monitoring by an infrared camera, the energy consumption by the equipment (laser, robot, chillers, wire feeder, and inert chamber equipment and sensors), and macrographs of the track metallographic cross sections. Motivation The adoption of Circular Economy (CE) strategies along both manufacturing value chains and products lifecycle will substantially improve the sustainability, efficiency, and use of imported and critical raw materials in industry. , pushing towards a new paradigm of digital-enabled EU industrial sustainability and resilience. DaCapo project aims at establishing a systematic approach enabling the creation of human-centric digital tools and services, focused on the creation of new digital assets, AI-based systems and the application of process and product Digital Twins, pushing towards a new paradigm of digital-enabled EU industrial sustainability and resilience. In particular, these digital tools were applied to the implementation of DED-LB technology for the repair and additive manufacturing of metallic jet engine parts. This open dataset on DED-LB of Ti-6Al-4V alloy wire aims to serve as a contribution to the continuous optimization and improvement of DED-LB as a technology for the additive manufacturing and repairing of aeronautic components WAAM processes, with a positive impact on Sustainability and Circular Economy. Structure The dataset follows this structure: 1. DED-LB Ti-alloy wire parametrization: Process window parametrization definition, with the set of parameters for each DED-LB track. Format: CSV 2. Monitoring of DED-LB Ti-alloy wire process: Compiled data of the process monitoring for each DED-LB track including: a. Images of the melt pool monitored by an infrared camera, at a 100 fps acquisition rate. Format: TIFF b. Combined filed with: Real time values of the process parameters for each DED-LB track during processing, extracted from the equipment. Energy consumption by the equipment: laser, robot, chillers, wire feeder, and inert chamber equipment and sensors. Format: VTK 3. Macrographs of metallographic cross sections of the DED-LB Ti alloy wire tracks. Format: JPEG Software To open the different files that conform the dataset, we recommend the following Open software: VTK -> Paraview 6.1.0 – Python 3.12 -> https://www.paraview.org/download/Ti-6Al-4V合金线材激光直接能量沉积（Direct Energy Deposition by Laser, DED-LB）数据集 本数据集采集自多组试验试板，试验以Ti-6Al-4V钛合金线材为送料原料，通过激光直接能量沉积（DED-LB）工艺制备线性熔道。每一条DED-LB熔道对应一组差异化工艺参数：激光功率、加工速度及线材送进速度。本数据集旨在为应用于航空部件增材制造（Additive Manufacturing, AM）与修复的激光直接能量沉积工艺提供详实数据支撑。所采集的数据涵盖：每条DED-LB熔道的工艺参数、加工过程中各工艺参数的实时瞬时值、红外相机监测的熔池信息、设备（激光器、机器人、冷水机组、线材送进机、惰性气体腔设备及传感器）的能耗数据，以及熔道金相横截面的宏观形貌图。 研究背景 在制造价值链与产品全生命周期中推行循环经济（Circular Economy, CE）策略，可显著提升工业领域可持续性、生产效率，并优化关键进口原材料的使用，助力构建以数字化赋能的欧盟工业可持续发展与韧性新范式。 DaCapo项目旨在建立系统化方法，开发以人为中心的数字化工具与服务，重点聚焦新型数字资产、基于人工智能（AI）的系统，以及工艺与产品数字孪生的应用，推动构建数字化赋能的欧盟工业可持续发展与韧性新范式。其中，此类数字化工具被应用于激光直接能量沉积技术在金属喷气发动机部件修复与增材制造中的落地实施。 本Ti-6Al-4V合金线材激光直接能量沉积开放数据集，旨在为激光直接能量沉积技术（用于航空部件增材制造与修复的线材电弧增材制造（Wire Arc Additive Manufacturing, WAAM）工艺）的持续优化提供助力，对可持续发展与循环经济产生积极影响。 数据集结构 本数据集遵循如下结构： 1. DED-LB钛合金线材工艺参数化：工艺窗口参数定义，包含每条DED-LB熔道的参数集合。格式：CSV 2. DED-LB钛合金线材工艺监测：各熔道的工艺监测汇总数据，包括： a. 红外相机以100fps帧率采集的熔池监测图像。格式：TIFF b. 综合文件，包含： - 加工过程中从设备采集的每条DED-LB熔道的工艺参数实时值 - 设备能耗数据：激光器、机器人、冷水机组、线材送进机、惰性气体腔设备及传感器 格式：VTK 3. DED-LB钛合金线材熔道金相横截面宏观形貌图。格式：JPEG 配套软件建议 建议使用以下开源软件打开本数据集的各类文件： VTK → ParaView 6.1.0 – Python 3.12 → 下载地址：https://www.paraview.org/download/