Home / Author Archives: Beth Stackpole

Author Archives: Beth Stackpole

Beth Stackpole is a contributing editor to Digital Engineering. Send e-mail about this article to DE-Editors@digitaleng.news.

Shatter Multimaterial Barriers

A meshed model showcases how a unit cell can deliver different material properties for metal 3D printing. Image courtesy of TNO via COMSOL.

New multimaterial 3D printing capabilities usher in more realism to prototypes while advancing the freedom to design and manufacture innovative products.

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Vendors Push Parts Reuse to the Next Level

Aras Innovator can directly import/export SysML models and replicate their structure inside the PLM platform, promoting reuse at a systems level. Image courtesy of Aras.

CAD and product lifecycle management platforms are being modernized with parts classification, Google-like search, and systems modeling capabilities to promote model and parts reuse.

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A Dead End for PLM?

Although PLM has broken out of engineering, it has yet to gain traction for product recovery and recyclability processes crucial to sustainability efforts.

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Give it Up for PTC’s Next-Gen PLM Concept Built on IoT

PTC CEO Jim Hepplemann wove together the company’s forays into IoT, machine learning and analytics, augmented reality, 3D printing, application lifecycle management (ALM), and industrial connectivity.

PTC CEO Jim Hepplemann wove together the company’s forays into IoT, machine learning and analytics, augmented reality, 3D printing, application lifecycle management (ALM), and industrial connectivity.

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Engineers: The New Data Economy Wants You!

The Classification Learner app makes it easy to train models using supervised machine learning, and to export classification models to the MATLAB workspace. Image courtesy of MathWorks.

Big Data analytics is bound for mainstream engineering, promising to have a dramatic impact on how products are designed, manufactured and serviced.

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Self-Driving Cars Test Traditional Procedures

Ford’s autonomous vehicles employ high-resolution 3D mapping and LIDAR to facilitate driving in bad conditions when road markings aren’t visible. Image courtesy of Ford.

Current physical and virtual test and simulation methods can’t cover all of the possible scenarios for autonomous vehicles, opening the door to safety gaps.

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