How can you structure your data from Additive Manufacturing processes to increase productivity?

By 26 February 2020No Comments

Additive Manufacturing at the heart of industrial processes is a challenge for tomorrow’s businesses. The global market continued the 20% growth trend announced in 2019, reaching $13 billion. A large share of the investments made has been devoted to the acquisition of machinery and the supply of materials, but the majority is dedicated to the development of new methods and processes. The technology remains relatively new on a global scale, and the rapid development of additive manufacturing faces a challenge that was already crucial at the end of 2010’s: how to structure the data acquired through additive manufacturing with a view to optimal profitability ?

Transition from discrete to mass production manufacturing

Additive manufacturing has opened up a new dimension for the industry. Based on a cross-reasoning between design, processes and material properties, this technology allows the production of unique parts and products.
In 2016, plastic and metal were the main materials used by companies for 3D printing. But the emergence of increasingly specific production needs has led to the exponential development of biomaterials and specialized materials (wax, laywood, polymers, etc.). In doing so, the appearance of new materials has completed the operational transition of companies: production can now take place in series, and no longer only in discrete production.
Thanks to this, new sectors have been able to appropriate applications and transpose them to their core business. For example, with pharmaceuticals and biomedical leading the way, these sectors could generate up to 20% of the growth rate for the additive manufacturing market. Notably due to the explosion in demand for healthcare applications to economically alleviate the procedures associated with complex surgeries.
But then, more than just the industrialization of the manufacturing process to be defined, it is really the ability of companies to adapt to the technology that is challenged. This is in order to take into account the enormous amount of data that revolves around additive manufacturing. Because, logically, a test that would have failed is a piece that collapses, it’s a waste of time and material, and therefore of money. Faced with this, it is necessary to structure one’s manufacturing processes so as not to make the same mistakes twice.

Two additive workflow issues: community and security

Due to its disruptive nature, it is easy to see that additive manufacturing is a cross-functional activity within companies. From laboratory test data, through simulations by calculation and metrology engineers, to the processing of feedback from materials experts. The interweaving of numerous departments, often compartmentalized in their respective missions, is leading to the development of new operating modes.
Initially, given the very diverse nature of the players involved in the additive manufacturing process, it is important to keep an overview of this process. Indeed, nowadays, the performer of a task must know how to balance autonomy and interconnection. Therefore, he needs to know “What to do? “and “How to do it? “but also “Why? So the notion of product logic introduces a view of the designers on their missions within the process. In this sense, they can identify the different services and sites involved, and if necessary, decompartmentalize the information to any person with a right to know about it.
By setting up a community around the information to be (re)used, the designer will be able to invest time to appropriate the prescriptive knowledge transmitted by an expert, in order to apply it. Thus, in a problem of efficiency and profitability, the decompartmentalized structuring of information allows:

  • Optimization of the production thanks to the understanding of the articulation of the functions.
  • The capitalization of feedback from experts, particularly on potential failures.
  • Avoid duplication in a highly strategic context.
  • To update the material databases on an ongoing basis.

However, with the integration of all these players in the process, some may be concerned about the safety of the data, and then the knowledge gained, from additive manufacturing. As mentioned above, competition in this market is only increasing. The very principle of adaptability of additive manufacturing reinforces the safety issue, especially in the development of specialized materials. Often based on “in-house recipes”, it is sometimes the medium-term R&D plan that is exposed.
In this case, opening up information to all stakeholders has its corollary. Specifically, the sharing of global functionalities, test and analysis results and expert knowledge must not compromise the confidentiality of high value-added data. Therefore, a single repository, with fine rights management, is a necessity in order to combine security and collaboration.
In a context of industrial revolution, thanks to Industry 4.0 and the connected whole, applications are limited only by imagination. Of course, today the parameterization of machines is complex, and manufacturing cycles are relatively long. But beyond the economic aspect, this technology pushes innovation to progress relentlessly. The latest news is that MIT is working on 4D printing, with the aim of making objects capable of changing shape or properties over time.

Questions about additive manufacturing?

Learn more about the TEEXMA® Additive Manufacturing Project Management Methodology. To learn more, visit our Additive Manufacturing page:

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