Bryan Crutchfield is Vice President and General Manager, North America for Materialise, a global leader in 3D printing.
Many families have generations-old recipes they wouldn’t dream of sharing, keeping secret the ingredients, measurements and methods written on yellowing index cards.
While not a new idea, I see a similar practice taking hold in the manufacturing space as production ecosystems become increasingly connected with data running the operation. Gone are the days when companies had to worry that the competition would copy their final product; now, they have to guard the data that controls the production process as well.
Supporting Smart Manufacturing Environments
Production environments are becoming smarter and more connected, with automation and artificial intelligence (AI) needed to keep the many aspects of manufacturing operations working smoothly. Behind these operations is data—information that outlines exactly how each aspect of the environment works and connects to the next part. Data that is interrupted—or worse, hacked—can temporarily shut down operations or even reveal operational best practices to the competition.
Therefore, manufacturers could benefit by focusing on a balance of data security and integrity. Data security keeps data proprietary so competitors can’t steal and produce other companies’ products while data integrity helps ensure the final products reflect the production parameters and quality requirements set by engineers and designers.
But why take this data-focused approach even when the consequences of a data breach can be so dire? Despite some of the concerns over data breaches, I find that it is more than made up by the fact that data enables more flexible design processes and production.
Manufacturing operations that are automated or run by AI help ensure efficiency, reliability and quality. They also alert manufacturers of hiccups in the system and can reveal ways to improve the operation. By taking care of the day-to-day tasks, manufacturers and engineers behind the automated processes can focus on continuously improving and updating data to make as efficient and effective a manufacturing process as possible.
Some aspects of manufacturing that are becoming more popular, such as 3D printing, also operate solely on data. Previously, a machine may have only been able to stamp out one part or a few varieties of a part and would require time-consuming retooling for design iterations or personalization. However, smarter digital technologies such as 3D printers can print anything the data outlines for them without any changes or retooling to the printer. (Full disclosure: I am a leader in a company that offers 3D printing services.)
Enabling Distributed Manufacturing
Data also plays a key role in enabling distributed manufacturing, in which production is split among a larger number of smaller facilities closer to the company’s customers. Distributed manufacturing gained popularity due to supply chain challenges in recent years tied to the Covid-19 pandemic, Suez Canal blockage, semi-conductor chip shortage and political tensions. These disruptions left some manufacturers waiting for months for parts from other countries and seeking solutions to localize supply chains.
Startup costs to nearshore the production of parts that were previously made entirely or mostly overseas are high; distributed manufacturing can help lower these costs by enabling manufacturers to use a variety of existing, smaller facilities run by their own company as well as third parties. It can also cut costs related to transportation and enable flexibility in the case that one or a couple of the smaller facilities are not operational; it’s easier to find another small facility to fill the gap than to adjust the operations at a massive factory.
Through distributed manufacturing, companies also see no lack of production capabilities, as manufacturers can work with facilities that offer technologies not available in their own operations, expanding their horizons. Again, using the example of 3D printing service bureaus, they can offer a cost-effective gateway to manufacturers who may be interested in the technology but unsure it would fit their needs.
Working across locations and with third-party parts producers reinforces the importance of data security and integrity. As data travels from facility to facility and is used within each location, it must remain secure so it can’t be hacked.
Manufacturers also need protections in place to ensure they maintain ownership and control over their data and designs. Digital rights management makes this possible by enabling manufacturers to set a maximum number of parts for each vendor when sharing data, preventing overproduction or misuse of designs in individual facilities.
Beyond these security considerations, any data shared for distributed manufacturing must also have measures in place to retain its integrity and ensure that third-party parts manufacturers cannot cut corners or alter designs during production. These parameters can specify everything from the design requirements themselves to the machine or materials necessary to build the part.
In an age of automation, AI and machine learning, strong data drives efficient manufacturing environments and high-quality products. But as manufacturers look to a myriad of options to modernize and streamline their production, I think it is important to think first and foremost about protecting the data that runs both their in-house and distributed operations.
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