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How to Structure Data from Additive Manufacturing Processes to Increase Productivity

By December 8, 2021No Comments

Additive manufacturing being at the heart of industrial processes poses as a challenge for tomorrow’s businesses. The global market has continued the 20% growth trend announced for 2019, reaching $13 billion. Much of the investment has gone towards the acquisition of machines and the supply of materials, however, the majority is dedicated to the development of new methods and processes. The technology is still relatively new on a global scale, and the rapid growth in the development of additive manufacturing faces a challenge that was already crucial in the late 2010s.

Structuring The Data Acquired Through Additive Manufacturing That Is Most Cost-Effective

The answer is to transition from discrete to mass production. Additive manufacturing has opened up a new dimension for the industry. Based on a cross-reasoning between design, process 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 now the emergence of increasingly specific production needs has led to the exponential development of biomaterials and specialized materials (e.g., wax, laywood, polymers, etc.). In doing so, the emergence of new materials has completed the operational transition of companies in which production can be carried out in series, and no longer only in discrete production. As a result, new sectors have been able to appropriate applications for their core business. For example, the pharmaceutical and biomedical sectors are leading the way and could generate up to 20% of the growth rate for the additive manufacturing market. Also bearing in mind the explosion in demand for healthcare applications to economically alleviate complex surgical procedures.

Beyond defining the issue of industrialization of the manufacturing process, it is really the capacity of companies’ ability to adapt to the technology that is challenged. The massive amount of data that revolves around additive manufacturing must be taken into account because reasonably, a failed test signifies a part that collapses, loss of time and materials, and therefore a loss of money. With having to face this, it is necessary for a company to structure its manufacturing processes to prevent making the same mistakes twice.

Two Challenges of Additive Workflow: Community and Security

Due to its disruptive nature, it is clear that additive manufacturing is a cross-functional activity within companies. From laboratory tests data, to the simulations of the calculation and metrology engineers, to the processing of feedback from the materials experts. So, the interweaving of numerous departments, which are often compartmentalized by their respective operations, leads to the development of new operating methods.

Given the very diverse nature of stakeholders 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 designers on their tasks within the process. This way they can identify the different departments and sites involved and make the information available to anyone who has 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 in appropriating the knowledge transmitted by an expert, in order to apply it. Thus, in a matter of efficiency and profitability, the decompartmentalized structure of information allows:

  1. An optimization of production due to the understanding of the articulation of functions
  2. The capitalization of feedback from experts particularly on potential failures
  3. Avoiding duplication in a highly strategic context
  4. Updating material databases

However, with the integration of all these stakeholders into the process, some may be concerned about the security of the data and subsequently the knowledge gained from additive manufacturing. As mentioned earlier, the competition in this market is only increasing. The very principle of adaptability of additive manufacturing reinforces the security issue, especially in the development of specialized materials. Often resulting from “in-house recipes,” it is sometimes the medium-term R&D plan that is exposed.

The opening of information to all stakeholders has its own concerns. More specifically, the sharing of global functionalities, test and analysis results and expert knowledge must not compromise the confidentiality of high value-added data. A single information repository with rights management is a necessity to combine security and collaboration.

In a context of industrial revolution, thanks to Industry 4.0 and the all-connected world, applications are only limited by the imagination. Of course, today’s machines are very complex and manufacturing cycles are relatively long but aside from the economic aspect, this technology pushes innovation to progress relentlessly. MIT is currently working on 4D printing, with the aim of producing objects capable of changing shape or properties over time.

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