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Reducing the risk of automotive defects is one of the most critical issues facing manufacturers today – to protect the well-being of consumers, as well as their own reputations and financial health.

Several years ago, a global commercial vehicle maker asked my firm to develop a remote fleet management, health and performance portal that would open a new revenue stream.

I’m among the first to dive into the latest manufacturing innovations and see how they can improve our customers’ operations. Yet, I’m also among the first to advise them to pause and ensure that the fundamentals of their manufacturing processes are in place before adding something new into the complex mix of functionality and desired outcomes.

It’s a familiar scenario at the factory. Quality issues have reared their ugly heads, requiring rework, causing backorders, delaying shipments, and driving tense daily customer calls. Meanwhile, the team works to address production issues using a mix of day-old post-mortem reports, shop-floor observations captured on notepads, and other operational data summarized on spreadsheets and sticky notes.

Defense systems are, by design, built to defend against threats. Today, however, manufacturers of these systems are focusing on an entirely new kind of threat: security breaches targeting their automation systems.

The first kilowatt-class fiber laser for material processing was introduced by IPG Photonics in early 2002. Since that time, the adoption of fiber lasers for production applications has grown at a rapid rate. Today, fiber lasers are becoming the choice for most major production laser applications as well as converting traditional welding and cutting processes to fiber laser technologies.

Northrop Grumman's SCRAM system revolutionizes additive manufacturing with integrated continuous carbon fiber for aerospace and defense. It offers cost-effective build-on-demand capabilities, streamlines certification processes, and enhances agility in responding to evolving customer needs.

Going Big on 3D Fiber Laser: Glenn Metalcraft Boosts Efficiency and Capacity with Prima Power's Laser Next 2141

An engine manufacturer discovers there is a way to reduce 50 billion data points to 2 billion—a reasonable number from which the foundation for machine learning can be built.

It’s time to redefine AM and DfAM by what is possible from advanced LPBF systems—and to look ahead with the same determination the semiconductor industry used to better our lives.