A step in time for industrialising AM

| Aerospace Testing

Path optimisation simulation could take additive manufacturing out of prototyping workshops and into volume production

Path optimisation software aims to solve overheating and improve yield to take additive manufacturing out of the lab and onto the shop floor.

The Digital Industries Software division of Siemens has created “Additive Manufacturing (AM) Path Optimizer”, a beta technology integrated in the company’s NX Computer Aided Engineering (CAE) software.

The path optimiser is design to assist AM users to solve overheating challenges and help reduce scrap and increase production yield to achieve the industrialisation of AM, or the use of AM on an industrial scale.

This advanced simulation technology has been created to help maximise the production yield and quality of powder bed fusion manufactured parts. This latest extension of Siemens’ end-to-end additive manufacturing software feeds the digital thread, informing the user of each step of the industrialised additive manufacturing process.

Digital Twinning

Building on Siemens’ pre-existing Simcenter Additive Manufacturing Process Simulation software, AM Path Optimizer complements the company’s strategy for the digital twin of the manufacturing process and addresses errors originated from suboptimal scan strategies and process parameters. These can lead to systematic failures due to overheating, which can cause scrap and inconsistencies in component quality.

Siemens has had success demonstrating this beta technology with TRUMPF as a partner. “With the AM Path Optimizer, Siemens and TRUMPF can push industrialisation of additive technologies further forward,” said Jeroen Risse, AM Expert at TRUMPF. “In our demonstrations we saw an improvement of geometrical accuracy, elimination of re-coater errors caused by overheating and a more homogenous surface quality. Also, the scrap rate is expected to be reduced significantly.”

The technology uses an innovative approach combining physics-based simulation with machine learning to analyse a full job file in a few minutes before execution on the machine. This technology is expected to help achieve “right first time” prints and drastically reduce trial and error. It can also help reduce printing costs and enable the printing of components that are nearly impossible to achieve today.

“We believe that AM Path Optimizer will have a great impact on the use of additive manufacturing for powder bed fusion manufactured parts,” said Zvi Feuer, Senior Vice President, Manufacturing Engineering Software of Siemens Digital Industries Software.

The aim of Siemens is for companies to use the path optimisation tool to take additive manufacturing out of the laboratory and low volume prototyping work and into high volume manufacturing. To assist in this aim, the company has also created its AM Network.

Additive Manufacturing Network

The advanced cloud-based AM Network digitalises the order-to-delivery process by aligning engineering and commercial processes for high-quality AM functional prototypes and serial production parts. The system connects buyers with a global supplier network which streamlines the process, fosters collaboration and engagement, and orchestrates the workflow to increase throughput and reduce operational costs. As part of the Siemens’ suite of Software as a Service (SaaS) products, the AM Network meets the most stringent requirements for security, availability and regulatory compliance.

“Siemens’ additive manufacturing experts and industry veterans have developed the additive manufacturing network based on a clear understanding of the complexities and needs of the industry, fostered by a sincere passion to promote the adoption of AM in the industrial domain,” adds Feuer.

Some companies are already realising the benefits of the AM Network, including Decathlon, a sports goods retailer. It uses the AM Network to manage its Additive Manufacturing ordering process and control production progress as part of its strategy to scale its use of 3D printing globally and ramp up production.

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