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Additive manufacturing

Transparency and quality assurance of additive manufacturing, from powder to delivery

The rise of additive manufacturing requires digital support from the entire production chain in order to monitor and guarantee product quality. To make this possible, Sirris is working on an eID or digital passport for products in its 4.0 Made Real Pilot Factory. Sirris has also researched quality assurance and process reliability in Selective Laser Melting (SLM) machines.

Traceability and quality assessment via product eID 

In recent years, there has been a major shift in the use of additive manufacturing. This technology is now increasingly used for serial production of functional end products, the characteristics of which must meet stricter requirements. Proving this via process control, repeatability and certifications is therefore becoming more and more challenging. Digital support for the entire production chain is required to ensure the production quality can be monitored, guaranteed and tracked throughout the different stages, which often spread over at multiple locations and ath the end the information available to the end customer is often limited.


As part of Industry 4.0, Sirris launched the 4.0 Made Real project, in which it is working on an eID or digital passport that will resolve current issues with identification. The eID includes not only the product characteristics, but also those of the production processes, steps, tools, operations, etc. carried out to arrive at the end product. 


Product identification is becoming a requirement in every type of quality assessment and certification process. Certain guidelines for the certification of additive manufacturing parts have already been developed. Using the digital passport, companies can easily draw conclusions as to the quality of the process and the end product, by analysing all the data available. This knowledge is essential for serial production in various industries. 

Enhanced quality assurance via in-situ monitoring of selective laser melting

Quality assurance and process reliability are the main challenges of SLM and LBM machines. In a study conducted by Sirris, machine learning algorithms were applied to the melt pool signatures and data from the layer control system to use them for detection of internal defects, originating from production of the part. 


Despite many industrial technological advancements in selective laser melting (SLM or LBM) machines, the quality assurance and reliability of the process remains a major challenge. To overcome this challenge, commercial machines are equipped with in-situ monitoring modules that efficiently monitor the production process at various levels such as powder bed spreading and melt pool/laser power monitoring. However, the lack of data processing and the absence of a link between monitored paramaters limits  the exploitation of the full capability of these systems. The origin of a defect in the final product is not always linked to a single independent process parameter, but to several independent parameters.


To illustrate this, we assumed the powder spreading in a specific layer is not as it should be, due to for example part movement or deformation during production. This would not affect the melt pool signature. Monitoring this single independent process parameter cannot therefore predict the final quality of the printed product. Linking the monitoring data throughout the process chain is therefore a current requirement. In our study, we applied the machine learning algorithm to the melt pool signatures and the layer control system data, to improve the process reliability and quality assurance.


A bundled overview of knowledge on additive manufacturing of ceramic materials

In general, ceramic products are the best option for parts required to resist extreme conditions in the long term; they offer many advantages over metals, including resistance to high temperatures and corrosion, high hardness and high compression strength. The main use of technical ceramics relates to one or more of these advantages. However, the high hardness of ceramic materials also constitutes one of its disadvantages. 


Additive manufacturing can be the right choice to shape ceramic parts. As is the case with other types of materials, it is unrealistic to assume that AM will resolve all the issues of the ceramics industry. Ceramics also come with a few challenges, particularly because of their high hardness.

20 years of knowledge and experience

Since the beginning of the 21st century, Sirris has been involved in additive manufacturing developments in the field of ceramics, either at the request of the industry or as part of various joint research projects. Sirris has bundled together their experience and knowledge from research and practice, in a new e-book. The e-book contains information on the market, its potential and opportunities, the AM processes that give the best results for ceramic materials, industrial success stories and more.


The e-book on additive manufacturing of ceramic materials can be downloaded here, free of charge.

Previous project as a benchmark for new software

For additive manufacturing, specifically in the LBM or SLM process, the choice of suitable supports structures is a critical stage for success of following production. Until today, this was often a history of iterations, filled with trial & error, specifically in case of complex parts with large dimensions (> 150 mm) in materials with high internal stresses, such as titanium alloys. Empirical validation came with extra costs and exceedance of deadlines, which was a  major obstacle for the technology.


To reduce the risk and aim at 'first time right', Sirris invested in a software solution allowing simulation of support behaviour compared to the internal stress levels generated during production. To validate potential gains and the accuracy of the simulation achieved by this solution, Sirris decided in agreement with Thales Alenia Space, to reuse an previous case study, completed in 2014, without the use of this tool.


Previously, Thales Alenia Space, a designer and manufacturer of space systems, had called upon Sirris to validate the manufacturability of a support structure for mirrors for satellites, by means of the LBM technology. For this project an iterative process was used to converge to a satisfying solution. Based on this experience Thales Alenia Space still manufactures the part, developed in the scope of this project, on a regular basis today and has patented the component.


Thanks to the new software tool, the exercise Sirris carried out allowed to precisely identify the rupture zones in the support structure, that previously were identified by experiment during iterations for optimisation. Hence, the exercise proved substantial gains (multiple dozens of production hours) achieved with this type of tool, especially with small series of parts with a complex geometry, for which even an experienced operator's knowhow does not suffice to remove the risk of failure caused by rupture of the support structures.


As it is a collective centre, Sirris now makes the tool available to companies, to allow designers and users of LBM machines to remove the risk linked to rupture of support structures.