This Website is not fully compatible with Internet Explorer.
For a more complete and secure browsing experience please consider using Microsoft Edge, Firefox, or Chrome

MSC Software Extended Abstract

Engineering of the Additive Process for Metallic Materials: From Topological Optimization to Metrological Verification

Bruzzo, A. Faraboschi, M, Linari, F.Scannavino
(MSC Software, Italy)


Use and adoption of additive manufacturing has increased greatly in the recent years thanks to improvements in production, cost reduction, greater know-how and predictive tools. Despite the important achieved progresses, there are still several difficulties related to the distortion of the piece during the molding process, the residual stresses, the higher costs of specific materials as well as the dimensional limitations of the production machines.

This presentation describes the engineering of the additive process for metallic materials through the use of simulation tools, considering and deepening the knowledge on many aspects and topics such as: material engineering, topological optimization, DMLS process simulation and verification of distortions and residual stress; demonstrating how it is possible to improve the quality of the process itself by combining the digital world of research with the real world of production.

In particular, the multiscale modeling techniques of materials, applied to the additive production of metals, will be described in details, including homogenization theories capable of simulating the accurate behavior of latex structures. Reverse engineering techniques and topological optimization, focalized and applied on the additive process, will be addressed. The process will be completed and linked to the real world of production through metrological inspection tools and hardware, such as laser scanning arms and optical probes, which allow the measurement of the printed product, from which it will be possible to create a cloud of points that can be used for numerical and experimental comparisonsas well as a starting point for obtaining the mathematics of the final component.

1. Additive Manufacturing Simulation Solution

For many years, Additive Manufacturing technologies have been used to realize prototyping applications while AM is now becoming increasingly widespread across many fields and used in the serial production of high-tech parts, particularly in aeronautics, space, automotive and medical industries. The current presentation features on the state of the additive manufacturing focusing on the fundamental role of the numerical simulation in order to address the challenges of the new disruptive technology, and the need to apply an entire digital design solution, from structural optimization to metrological inspection, considering material characterization and process simulation, that is how simulation drives design.

Figure 1: Hexagon Additive Manufacturing Solution.

AM technology offers advantages, such as geometry design freedom - that allows the creation of optimized shapes according to the targeted function - and the ability to reduce the weight, cost, and complexity of parts production without sacrificing the reliability and durability of materials. Besides AM could afford the advantage of small production runs with less material waste, significant energy cost savings, and the possibility to produce functional, high performance parts that can’t be manufactured through traditional subtractive process. A key factor is the concept of Generative Design that helps engineer to think out-of-the box, to concept unimaginable shapes, to enhance the potential of additive manufacturing: connecting design solutions to virtual manufacturing simulation, the design can account for the engineering and production phase challenges earlier in the product development phase. The virtual manufacturing simulation is used to identify the best printing process and to optimize the orientation of the part and the build process. Furthermore, the outcome of the additive manufacturing process chain can be used for the validation of the “real” geometry, while accounting for the residual stress distribution and the local deformation under real load conditions using FEM design validation solutions. The end-to-end process enables engineers to make sure their optimized designs are validated for manufacturability and performance.

2. Generative Design concept: bridge the gap between Design and Manufacturing

Generative Design is not simply a Topological optimization process of automatically generating several design concepts that satisfy a set of user defi­ned objectives, criteria, and constraints (structural loads, boundary conditions, stress limit, mass minimization). Principally, Generative Design assists design engineers to create organic and revised topologies that can be manufactured effectively and with success, right at the very first time using 3D printing. Despite its unique ability to manufacture virtually any topology, Additive Manufacturing could be not very forgiving if an unrevised Topology Optimization result, often far from feasibility. AM still has many limitations today: issues such as shrink lines, cracking, overheated zones, etc. have to considered, because they are prevalent when using AM for production structural parts for Aerospace or Automotive industry. Today, cost of manufacturing and time of printing are seen as two major constraints in wide adoption of AM for mass production. Therefore, there is a need to account and optimize for the total manufacturing costs and print time while designing parts for AM: costs for amount of material required for the part, volume of support structure required for support and heat dissipation in the AM machine, cost of removal of support structures and machining for desired surface roughness, costs related to maximizing the number of parts printed at one time on a build plate, etc. Generative Design technology is focused not only on optimizing the parts, but on optimizing the full AM process, it is the bridge between design and manufacturing, helping AM becoming a sustainable manufacturing method.

Figure 2: Generative Design process.

3. Complete the process: optimization, examination, validation

The optimization process has been automatized reducing user intervention and allowing the interoperability of other tools like multibody and FEM in order to get loads from realistic simulation, to apply optimization on complex systems in which components must operates, satisfying realistic boundary conditions, validating the design in terms of form, fit, functionality, manufacturability, weight, costs, stress, behaviour. And all candidates will be checked using Additive technology for metal and polymer parts, and for buckling, fatigue, performance using FEM and multibody tools. Only a complete examination of the design space with a variety of results, and in a short time, leads to the best results.

Figure 3: AM simulation and optimization.

Finally, after printing the part with your 3D printer of choice, Hexagon metrology’s state-of-the-art scanners can verify the accuracy of the simulations and compare the “as-built” part to the “as-designed” part. This allows for genuine “First Time Right” 3D printing.

Figure 4: Metrology for AM verification.

4. Case Study: Formula Student wheel carrier

Weight savings is essential in car racing. The competitive advantage can be gained with the best, light weight design. Every gram that can be saved on the racing car can make it faster and more agile.

The case study focused on the wheel carrier of a Formula Student car: the target has been to build a 3D printed stiffness/weight optimized component, starting from scratch, using simulation for: topology optimization (and integrated structural verification), 3D printing process simulation, cost estimation. After the production of the optimized component, metrology verification has been made to get the real tolerances.

The dynamic of the vehicle has been studied and verified through a multibody simulation. Wheel carrier has complex load cases due to the different actions during racing (curves, brake, acceleration): 5 loadcases has been used for the optimization.

Figure 5: Adams/Car Loadcases and simulation

The topology optimization has been used to get multiple wheel carrier candidates: starting from the design space and the boundary conditions coming from multibody calculations, the topology optimizer shapes the solid material in order to get the lighter and stiffest solution. The result of the optimization has been three different shaped design components, stress verified, and possible final candidate for the production. After optimization, 3D printing process simulation has been carried out. Throught this kind of simulation have been optimized the orientation of the component inside the machine and the support structures. In order to decrease the amount of final distorsions and stresses on the printed part, an automated compensation algorithm has been used.

Figure 6: AM virtual process.

During the process simulation has been also done an economical estimation of the production. As a consequence of the entire process of simulation, at the end only one of the three multiple candidates has been built: the right compromise between structural efficiency and production costs has been chosen.

Figure 7: Final product.

After the production, the component has been measured through scanner laser, in order to get the real tolerances and confirm what has been calculated through simulation.