The growing importance of smart data in 3D printing

Getty Images

As with other types of modern production, data is crucial to the success of current additive manufacturing processes and to the improvement of future ones.

Recently, executives participating in a roundtable at Belgium-based software and 3D printing firm Materialise NV discussed the importance of data in additive, as well as control of AM data and the roles of data and human expertise in successful 3D printing operations.

“We believe in a world where the next part we print will be a better version of the previous printed part.” — Materialise customer

While data collection is key in efforts to make manufacturing “smart,” it is not enough, said Bart Van der Schueren, Materialise’s CTO and executive vice president. Collected data must also be analyzed to produce actionable insights that will allow manufacturers to improve their processes and make better products, Van der Schueren said.

As manufacturers scale up 3D printing production, a rich data history will allow them to reduce scrap rates, predict failures before printing processes begin, and meet stringent part-quality requirements, said Tim Van den Bogaert, senior market director at Materialise Software. He added that data also make it possible to continuously learn how to make products better, even on the fly, possibly allowing AM users to eventually reach goals like this one articulated by a Materialise customer: “We believe in a world where the next part we print will be a better version of the previous printed part.”

To create systems with capabilities like this, Van den Bogaert pointed out, software platforms must be able to connect to all the systems and datasets in the production environment—and even beyond.

AM also offers the possibility of a digital supply chain where users can print whatever they need, whenever they need it, Van den Bogaert said. Making this vision a reality, however, will require distributed manufacturing and subcontracting. “How you handle data in that whole network is an important [problem] that we must solve so people are confident that their data is owned and controlled by the right person,” he noted.

Peter Leys, the company’s executive chairman, believes there’s a distinction between owning and controlling data. “From an operational perspective,” Leys said, “what matters is that the customer or user of the machine should control the data they generate so, on the basis thereof, they can build a more intelligent way of manufacturing that distinguishes them from the competition.”

Participants in the Materialise roundtable (clockwise from left): Kristel Van den Bergh, Director of Innovation-Mindware; Pieter Slagmolen, Innovation Manager; Bart Van der Schueren, CTO and Executive Vice President; Kristof Sehmke, Communication Manager; Peter Leys, Executive Chairman; and Tim Van den Bogaert, Senior Market Director-3D Printing.

“From an operational perspective, what matters is that the customer or user of the machine should control the data they generate so, on the basis thereof, they can build a more intelligent way of manufacturing that distinguishes them from the competition.” — Peter Leys

For medical AM applications, process data clearly belong to the hospitals and medical-device manufacturers that create AM workflows, and they need access to and control of the data for quality-assurance purposes, according to Materialise Innovation Medical Manager Pieter Slagmolen.

Ownership of patient data, however, remains a hotly debated topic. But regardless of who owns the data, Slagmolen stressed that additive manufacturers in the medical field need access to that data in order to produce products that most effectively meet patient needs.

As important as data is to AM success, the Materialise executives agreed that it doesn’t eliminate the need for human intervention and expertise. Even in data-rich manufacturing environments, the domain-specific knowledge of human experts is required to optimize processes before they are automated, Van der Schueren said. Otherwise, a lot of good data can go to waste in a bad production process.

Even in the later stages of AM, data alone will not suffice, according to Kristel Van den Bergh, director of innovation for Materialise Mindware. For example, she pointed out that human expertise is needed to optimize and automate the postprocessing that follows the printing of metal products.

And getting an AM project started is far more complicated. With all the considerations and complications involved in the early stages of AM, she said, “I think having a multidisciplinary team of experts looking at all those facets is instrumental for success.”

WATCH the Materialise roundtable on YouTube.