Wire-arc Additive Manufacturing Open Repository

WAAM dataset

This dataset collects data from various test coupons (walls) subjected to the wire-arc additive manufacturing (WAAM) process. This dataset has been generated involving two materials ER70S6 and ER110SG (denoted as M1 and M2 respectively), and considering a range of dwell times (30, 60, 90, 120, 240 seconds), to investigate the effect of heat accumulation during fabrication. Data collected includes the initial characterisation of the experiment (including material, CAD and manufacturing procedure data), thermal and distortion predictions from FEM simulation models, machine-independent process configuration data, multimodal monitoring from the WAAM process, metrology and distortion data, quality assurance data and testing (comprising micrography, macrography and hardness measurements).

Motivation

The industrialization of manufacturing processes requires comprehensive data management and process automation enabling a seamless dataflow by combining product development and virtual engineering workflows with production systems monitoring and quality assurance data to obtain a continuous representation of the component being manufactured. PIONEER implements simulation-based digital twins adopting a design-by-simulation optimisation framework in which knowledge extracted from manufacturing processes and production assets together with quality assurance data provides data-driven models for product and process optimisation.

To address this, we present an open dataset on WAAM, covering all stages of the additive manufacturing process, from concept ideation and planning to production and quality control. This resource aims to serve as a foundation for developing new data-driven methodologies, contributing to the continuous optimization and improvement of WAAM processes while accelerating their digital transformation.

Authors

Félix Vidal (Contact person: [e-mail]);

Aurora López (Data collector);

Paul Rosero (Data collector);

Martín Martínez (Data collector);

Andre Oeckerath (Data collector);

Abdallah Fawzy (Data collector)

Structure

The dataset follows this structure

1. INITIAL REQUIREMENTS

a.       MATERIAL DATA: Material datasheet and certificates. Format: PDF

b.       MANUFACTURING PROCEDURE: Process window parameterisation definition. Format: XLSX

c.       CAD: 3D design file of the wall. Format: STEP

2. CAPP: Machine-independent process parameters definition. Format: AutomationML

3. CAE: Accurate thermal and Distortion predictions from Finite Elements Simulation Models. Format: VMAP

4. PRODUCTION MONITORING:

a.       Compressed H265 data from an infrared thermal camera. Format: MKV

b.       Compressed H265 data from a high-resolution and active-illumination camera. Format: MKV

c.       Compiled process parameter data including Voltage, current, wire speed, robot speed, robot position and thermocouples measurement. Format: VTK

5.       METROLOGY:

a.       Point cloud data captured after the additive manufacturing process with clamping in place. Format: STL

b.       Point cloud data captured after clamp removal. Format: STL

6.       QUALITY ASSURANCE: Radiographic testing report. Format: PDF

7.       DESTRUCTIVE TESTING: Harness, micrographs and macrographs results. Format: JPG

SOFTWARE

To open the different files that conform the dataset, we recommend the following Open softwares:

STEP -> FREECAD 1.0.2: https://www.freecad.org/index.php

AutomationML -> AutomationML Editor V.6.4. -> https://www.automationml.org/wp-content/uploads/2025/09/AMLEditor_6.4.2.17.zip

VMAP -> Paraview 5.12.1 – Python 3.10 -> https://www.paraview.org/download/ and VMAP plugin for Paraview: https://vmap-standard.org/Specifications/Downloads/

MKV -> VLC media player: https://images.videolan.org/vlc/#download

VTK -> Paraview 5.12.1 – Python 3.10 -> https://www.paraview.org/download/

STL -> FREECAD 1.0.2: https://www.freecad.org/index.php