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Advanced Simulation Solutions Applied to Quality Control of Laser Deposited Metals

Periodic Reporting for period 2 - ASSALA (Advanced Simulation Solutions Applied to Quality Control of Laser Deposited Metals)

Reporting period: 2020-07-01 to 2021-10-31

Productive industries of transport sector, such as aerospace, have realized that some geometrical deficiencies and high manufacturing costs could be overcome if critical components were manufactured by Additive Manufacturing (AM) methods. Aerospace sector pursues the cost-effective manufacturing of mission critical components, which are machined from previously wrought or forged preforms, scrapping high amounts of expensive materials such as superalloys, which are not still allowed to be re-used/recycled for the same structural applications. The buy-to-fly ratio for a part machined from forged billet is typically 10-20 and can potentially drop nearly to 1 with AM methods for the most favorable cases.

Laser based direct energy deposition processes offer the possibility of sorting out the geometrical, cost and process related issues. Depositing near-net-shape geometries, heat treating and machining them yield more efficient productive results than traditional processes in specific materials and markets. The main challenge to attain with AM technologies is to ensure structural integrity of fatigue loads through robust processes where simulation has a vital role.
Structural components of specific sectors have been inherently linked to the concept of catastrophic failure because of the dynamic loads (fatigue) acting on them. Failure has enormous repercussions on aspects such as personal safety, environment, or economic cost. ASSALA project will develop, test and integrate the necessary simulation technologies to limit and control defect generation in laser metal deposited components.

Since the material internal structure is being generated in the melting process, pores, crack, residual stresses, strains, and component distortions are also inherent to additive manufacturing processes. The lack of predictive tools is overcome with acquired process experience and time-consuming trial-error setup processes. However, the use of thermo-mechanical simulation tools fed with statistical failure probability models can lead to notorious time and cost reductions in laser-based AM process set-up and subsequent optimization and certification processes.

Summarizing, ASSALA project is focused on the development and introduction of a new manufacturing process on a highly standardized sector such as aerospace because clear advantages over traditional manufacturing processes have been envisaged. To this end, ASSALA has developed a set of digital simulation tools, both for the process and for the productive means, thus, enabling the achievement of more robust and reliable laser wire deposition (LWD) process because there is a real and growing demand from the aerospace sector.

This project belongs to the Clean Sky 2 Programme
To achieve the established goals, the following activities were completed:

• Definition of specifications and requirements of the additive manufacturing process and demonstrator geometry. Besides this, a thorough document compiling the state of the art of all the technologies to be developed in ASSALA was completed. This document also s specifies the planned equipment to carry out the activities.

• Development of a robot dynamic model. The model allows the simulation of both joint and cartesian coordinate movements and provides setpoints about joint (position, velocity, acceleration, motor torque) and TCP performance (position, velocity, acceleration).

• Real – time thermomechanical models. This activity relies on an approach which considers several time and space scales, in an increasing order of complexity: track/bead layer component scale, which provides component distortions as a function of process parameters and deposition trajectories. Due to the reduced order modelling (ROM) strategy, results are provided in almost real time, so the end user can evaluate a complex parameter space in a reasonable time. As an outcome, several user-friendly apps were developed for the different geometries tackled during the project.

• Sensitivity analysis and uncertainty analysis were carried out for both the robot kinematic model and the process distortion model. In this way, the most influential variables were identified for each modelling approach.
• Data – based porosity models. A neural network-based solution was built using the data extracted from a DoE campaign, using x-ray tomography results. It predicts the probability of porosity depending on process parameters and trajectory details.

Regarding the supporting digital tools, the following can be highlighted:

• Development of AM specific CAM tool. A tool was developed to automatically calculate the deposition sequence. This tool is supplied with a GUI and interfaced to the robot dynamic model, so they can be run sequentially.
• Monitoring and control strategies, based on three different technologies:
o Structured light 3D scanner for geometry measurement and part growth control.
o Side camera with laser illumination for the wire movement monitoring and its interaction with the melt pool.
o Coaxial camera for melt pool monitoring.

Finally, all these technologies were used to support the manufacture of a large demonstrator component using wire-based laser metal deposition technique (w-LMD).

As part of dissemination and communication activities, four peer-reviewed papers were published in specialized journals and two conference contributions were presented. To reach wider audiences, several pieces of news were contributed to specialized digital newspapers, as well as social media posts and a mention in a webinar.

Main exploitable results identified by the partners of ASSALA project are mainly related to:

• Fast & precise thermo-physical AM process simulation
• Deposition trajectory generation software (already copyright protected)
• Dynamic robot modelling and compensation metrology service. (already included in the service catalogue)
• Geometrical in-process control system
• Thermal in-process control system
ASSALA project develops a novel technology, wire LWD, that will allow to manufacture more efficient aero engines. ASSALA contributes to high-level objectives at demonstrator level:

• Contribution to CO2 emission reduction, as enabling technology for future light weight complex structures
• Reduce noise levels making a significant step towards to ACARE 2035 targets
• Contribute to achieve NOX emission ACARE 2020 target
• Retain European competitiveness to maintain European employment levels

In particular, the following topics have been advanced beyond SoA:
• Automatic path generation methodology (CAM) for w-LMD components
• Development of a robot model, assuming all error sources both for static and dynamic demands
• Real – time thermomechanical simulation, based on a reduced order model approach (ROM).
• Data – based approach for porosity prediction.
• Robot path corrections based on structured light scanning technologies.
Robot performance verification
App for the revaluation of distortion based on process parameters and deposition trajectories
Final demonstrator geometry built by w-LMD