In-Service Part Quality for Additive Manufacturing

Over the past century, we have witnessed amazing milestones in manufacturing. The most impactful achievements have been those that simplified and automated the design-to-manufacturing process. Consider Henry Ford’s moving assembly line in 1914, the launch of the first CAD software in 1954 and the arrival of industrial robots in 1973. Each of these developments allowed manufacturers to bring better products to the marketplace more quickly.

Today we are witnessing the next breakthrough—the widespread adoption of additive manufacturing (AM) technology, popularly known as 3D printing, for production use. With the advent of highly controlled materials and processes made possible through advanced software, we are now seeing the proliferation of much more functional engineering applications using layer-wise manufacturing methods.

One capability of AM is the ability to manufacture parts with complex and heterogeneously variable internal substructures and properties at minimal additional production cost. But designing those complex internal structures is in no way trivial.

Simulation Guides Additive Manufacturing Design

Advances in simulation technology for multiphysics, design optimization and predictive analytics are aiding the adoption of AM for producing final parts. With design no longer constrained by subtractive manufacturing restrictions, a part designer can leverage design simulation software to answer:

• What is the functional objective of the part?
• Can we design a part with the same functional characteristics but use less material?
• Can we obtain the savings from optimized additive parts?

By using physics-based simulation and optimization, engineers are empowered to develop parts that are increasingly complex, more organic and lighter—all while meeting performance requirements and using less time and fewer resources.

Driven by representative volume elements (or RVEs) simulation helps transform the detailed internal structures into continuum representations, which enables the realistic modeling of part-level simulations. Because the underlying variable that drives a topology optimization is the relative density of the material, simulation tools are able to determine variable densities and material distribution in a fixed design space. Users can apply single or multiple loadings. Optimization software is capable of iterating the design with this load case to find the maximally stiff structure within a given mass constraint. Notably, the optimization results often reveal that the maximum density region does not always correspond with maximum load location. This kind of insight can only be achieved using simulation technology.

Expanded Manufacturing Machine Options

The AM machine provider now includes machines capable of handling metals and polymers, with new material capabilities being added regularly.

Most AM processes require detailed process analytics, such as temperature and distortion profiles. By adopting an all-purpose simulation framework, companies can simulate parts built from different processes. Such a framework allows users to specify machine-dependent information as inputs in space and time, include support structures from their builds and analyze material behavior—while it computes the solution locally and globally.

Subham Sett leads the Dassault Systèmes team responsible for the rollout of roles and applications for additive manufacturing and materials. Contact him via [email protected].