News – HybridR https://www.hybridr-project.eu Mon, 29 May 2023 15:18:25 +0000 en-GB hourly 1 https://wordpress.org/?v=6.2.7 Process window development for the DED-LB/W process ../../../process-window-development-for-the-ded-lb-w-process/ ../../../process-window-development-for-the-ded-lb-w-process/#respond Mon, 29 May 2023 15:16:11 +0000 ../../../?p=1113

Process window development for the DED-LB/W process

Process window development for the DED-LB/W process

HybridR consortium is defining strategies for efficient process window development in DED-LB/W.

DED-LB/W is inherently a process with complex characteristics, such as repeated heating-cooling thermal cycles, rapid solidification, and laser beam-wire-melt pool interactions, that have a direct effect on the properties of the deposited material.

The definition of process parameters that provide consistent geometrical accuracy and material properties is very challenging and is highly dependent on the part geometry (thin-walled or fully dense). Additionally, when the working material changes, the cycle of determining the process window starts again.

HybridR consortium acknowledges that for the industrial adoption of Additive Manufacturing, process knowledge needs to be generated that helps end users determine fast suitable process parameters for their application. To this end, a standardized procedure for process window development, with the aim of minimizing the required number of experimental trials (and as a result cost and time of the whole procedure) is defined by the HybridR consortium partners.

 

 

Single Tracks

Process development starts with single tracks, which are simple lines of deposited material. Different process parameter combinations (laser power, robot speed, material feed speed) are examined. To minimize the required number of experiments Design of Experiment techniques are used. Advanced statistical analysis of the deposited tracks provides information regarding the effect of the process parameters in track dimensions (bead width and height), penetration in the substrate (using microscope measurements on the bead cross section) and overall process stability (using data from monitoring systems). The result is a first set of process parameters that provide the expected results in terms of process stability and bead quality.

 

 

 

 

Thin-walled geometries

Using the parameters determined from single tracks, these are transferred to manufacturing of thin-walled (1-4 walls) geometries. Thin-walled geometries are especially challenging as it regards heat accumulation, but are one of the main target applications of DED-LB/W. So, it is highly important to optimize the process window in these types of parts. At this step, the process parameters from the single tracks are evaluated together with the layer height, overlap between each wall (in multi-walled parts) and interlayer cooling time. Stable part growth (without cracks, keyholes, over- or under-deposition), cross-sectional stability and residual stresses are examined at this stage. Again, to minimize the required number of experiments appropriate Design of Experiment methodologies and statistical analysis are used. In the end, a set of stable process parameters for thin-walled parts is achieved, leading to a reduced process window, compared to single tracks. Apart from that, at this stage the ability to deposit material on top of existing parts is examined, to validate the ability of the equipment to be used for repair.

 

Fully dense parts

Last stage of the process development phase is the definition of process parameters for fully dense parts. In these parts the deposition of the outer walls and the infill (internal structure of the part) need to be optimized simultaneously. The process parameters from the single tracks are evaluated together with the layer height and overlap. Stable part growth (no under- or over-deposition, crack and pore free parts) is a key priority. Additionally, effect of overlap on material properties (e.g. tensile) strength can be examined at this stage for critical applications, where weight optimization is key, in order to reduce the infill mass.

All the above constitute a set of best practices that have been derived during HybridR and can be followed by end-users of DED-LB/W equipment to optimize fast their manufacturing process and be able to deposit high quality parts consistently.

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Getting close to the AM process – monitoring for DED/LB-W ../../../getting-close-to-the-am-process-monitoring-for-ded-lb-w/ ../../../getting-close-to-the-am-process-monitoring-for-ded-lb-w/#respond Mon, 29 May 2023 14:18:15 +0000 ../../../?p=1090

Getting close to the AM process – monitoring for DED/LB-W

Getting close to the AM process – monitoring for DED/LB-W

HybridR develops a multi-modal monitoring system for DED/LB-W.

In modern manufacturing, data-driven optimization is one of the key priorities. Monitoring systems that are able to sense the process status and provide data for real-time control and optimization are integral parts of new machine tools. Especially considering Additive Manufacturing, which is a highly complex process that incorporates different physical phenomena simultaneously, having the ability to monitor the process is crucial for its optimization.

The HybridR cell does not fall short in this essence. A multi-modal monitoring system has been developed, utilizing a combination of data sources:

  1. Vision-based monitoring: A Basler ace high-speed vision camera has been integrated on the AM head. Using a set of suitable optics (lens, optical filters) this camera enables an accurate depiction of the melt pool at a small field of view (10x10mm), at a very high frame rate (more than 200 fps). The camera enables accurate detection of defects, such as stand-off distance error, keyholes, balling, etc. As a next step, the development of algorithms for automated characterization of the images and detection of defects, utilizing Artificial Intelligence, is being pursued by the consortium of HybridR.

  1. Wire feeding stability monitoring: The second data source for the HybridR monitoring system for the DED/LB-W process comes from the internal sensors of the Meltio AM head. A load cell that is integrated in the AM head measures the load exerted on the head by the wire that is touching the workpiece surface. This peculiarity of the DED/LB-W process, compared to the powder alternative, provides an innovative monitoring alternative. Instabilities in the process, due to poor process parameter selection, such as over- or under-deposition of wire are demonstrated as excessive variations on the load cell signal.

The fusion of these two data sources by synchronous, timestamped acquisition of the data that are also registered in the coordinate system of the part, by logging the robot position simultaneously, provides a complete picture of what is happening in the process and enables its optimization

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Digital Twins for robotic machining ../../../digital-twins-for-robotic-machining/ ../../../digital-twins-for-robotic-machining/#respond Mon, 29 May 2023 13:53:52 +0000 ../../../?p=1071

Digital Twins for robotic machining

Digital Twins for robotic machining

HybridR consortium provides a solution for accurate process planning of the robot machining process using Digital Twins.

The use of robots for milling operations seems to be a logical step since they offer high flexibility to a manufacturing system and present several major advantages over conventional CNC machines. In specific, milling with robots offers larger working envelopes without increasing the cost, while due to their flexible kinematics they can reach and move in tight areas, to produce parts with complex shape. However, robots have an inherent problem with structural stiffness, as most of them are designed as open, serial kinematic chains supported by rotational joints. Consequently, the cutting forces applied to the tool tip during milling operations can lead to serious trajectory deviations, when high cutting loads are applied, resulting in an accuracy that cannot meet the requirements of several industrial sectors.

HybridR provides a solution to tackle this issue through advanced simulation and Digital Twins of the robot machining process. A dynamic model of the machining robot of HybridR has been developed, using the Multi-Body Simulation (MBS) and Component Mode Synthesis (CMS) methods, which is able to calculate the robot deflections throughout the toolpath. The simulation is linked with SprutCAM (the CAM s/w used for programming the HybridR cell), in order to adapt the process plan automatically, based on the user requirements in terms of machining tolerances and the simulation results

Through the simulation results, the machining error can be calculated along the whole toolpath length. Additionally, the feed rate of the robot can be automatically adjusted locally, to optimize the process and ensure that tolerances are met throughout the whole part.

More information can be found in the corresponding scientific article that has emerged from this development.

  1. Stavropoulos, C. Gerontas, H. Bikas, T. Souflas, “Multi-Body dynamic simulation of a machining robot driven by CAM”, 55th CIRP Conference on Manufacturing SystemsVolume 107, pg. 764-769 , 29 June – 1 July, Lugano, Switzerland (2022)

      https://doi.org/10.1016/j.procir.2022.05.059

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Meltio Engine integration with Robot ../../../meltio-engine-integration-with-robot/ ../../../meltio-engine-integration-with-robot/#respond Mon, 29 May 2023 13:14:33 +0000 ../../../?p=1028

Meltio Engine integration with Robot

Meltio Engine integration with Robot

The Meltio Engine has been successfully integrated with the YASKAWA robot and the first experiments regarding the Additive process have been conducted.

Integration of the Meltio Engine with the YASKAWA GP225 robot within the HybridR project has been accomplished on Gizelis Robotics premises, from the HybridR project consortium with ANiMA assistance.

       Figure 1: YASKAWA robot and Meltio Engine after the integration

Meltio Engine uses Laser Metal Deposition (LMD), which is a Directed Energy Deposition (DED) process that supports both powder and wire form material printing. Multi Material printing is also feasible, supporting materials such as Stainless Steel, Titanium and Nickel. Robotics based AM enables in-line AM as a sub-process in an existing production flow, allowing us to accomplish multiple manufacturing processes (machining, cladding etc.) and quality inspection systems such as 3D scanners in a single manufacturing cell.

Figure 2: Additive process snapshot

 

Process development

After the integration was completed, a series of experiments have been conducted from the consortium towards process development for 316 Stainless Steel. Several test coupons have been printed, ranging from single tracks and layers up to simple shapes such as cubes. Different process parameters have been used to understand the system behavior and extract the best process window for this specific material.

                                                                                                                                         Figure 3: Printed test coupons

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Design of a Portable Robotic Machining Cell ../../../design-of-a-portable-robotic-machining-cell/ ../../../design-of-a-portable-robotic-machining-cell/#respond Mon, 29 May 2023 13:03:06 +0000 ../../../?p=1018

Design of a Portable Robotic Machining Cell

Design of a Portable Robotic Machining Cell

HybridR consortium is using Digital Twins to support the design and development of the portable hybrid manufacturing cell.

Hybrid manufacturing opens the pathway for in-situ repair of high-value industrial components for industries, such as aerospace, oil and gas, etc. A portable robotic cell for repair enables the solution to move to the problem, allowing supply management practices such as just-in-time manufacturing, shortening the supply chain and dramatically increasing the sustainability of the repair operation for large-scale industrial components, by significantly reducing the required transports. To this end, HybridR is developing such a cell with a specific focus on repair of high-value components, apart from green field manufacturing.

In cases of portable manufacturing cells for hybrid manufacturing development, the design of the load bearing structure of the cell becomes significantly complicated, since it needs to provide the required stiffness to support the machining loads, while minimizing the weight to enhance portability. The final accuracy of the machining system depends on the behavior of the frame structure which is loaded under static, dynamic, and thermal loads.

To support this design optimization effort within the HybridR project, the Digital Twin of the robotic machining process has been exploited, taking into account both the process and the robotic arm to set the boundary conditions for the design of the load bearing structure. The use of the digital twin to build the boundary conditions for the simulation of the robotic cell can effectively lead to a virtual prototype of the whole system that can reduce the need for physical prototyping and trial and error approaches.

 

                                                                                                                                                                             Figure 1: Overview of the used design approach

 

Three different simulations have been performed during the design stage of the load bearing structure, in order to create a successful design that will ensure a safe and reliable operation and transportation:

  • Simulation of the material removal process by using the Multi-Body Simulation for the robotic arm, considering both the flexibility from its joints and links.
  • A static structural simulation was performed to estimate the stresses and deformations on the load bearing structure during transportation scenarios.
  • A harmonic response analysis using as input the forces that was calculated from the machining process simulation.

                                                                                                                    Figure 2: Static and harmonic response analysis simulation results (ANSYS)

 

Through the knowledge of the dynamic behavior of the portable hybrid manufacturing cell, gained by these simulations, it was possible to design a lightweight, yet highly stiff, load bearing structure to support the machining loads and ensure high accuracy of the milling process.

 

                                                                                                                                                                                                               Figure 3: Complete cell render

 

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