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The ever-volatile oil and natural gas industry—roiled most recently by September’s drone attacks on Saudi Arabian oil facilities that temporarily reduced the kingdom’s output by nearly half (about 5 percent of global production)—faces particularly challenging requirements for machined components to meet evolving supply targets.

Rapid prototyping is a staple of every designer and engineer’s workflow—essential for testing new concepts, verifying designs, and meeting increasingly aggressive time-to-market goals. Regardless of the industry or product, all engineers must consider the speed, accessibility, cost, and output of these additive manufacturing equipment.

For years, companies have struggled to understand how additive manufacturing (AM) can add value to their businesses. This makes sense because for a long time, additive tech didn’t meet the threshold for producing industrial-grade parts.

With an influx of investment in digital factories, the playing field is changing and the ROI for digitizing production is becoming ever more apparent. However, restraints, such as company size and a disconnect between IT and OT, means the road to a successful digital transformation is one very few will be able to do alone.

While looking for inspiration for this column,Ilene Wolff came across a rousing magazine headline. “Why the Women in 3D Printing Innovator Award Is Important,” the TCT Magazine headline read.

Kennametal Inc., Pittsburgh, has formed a 3D printing materials and production business unit, Kennametal Additive Manufacturing, as part of its Infrastructure segment.

There is an ever-increasing demand for the individualization of products from today’s consumer. When consumers are able to get exactly what they want (shape, size, color) they are more satisfied and more likely to do repeat business. But how do you scale custom part production?

The Pittsburgh region is a hotbed of activity in robotics and AI. This activity includes research and technology companies that commercialize academic research and solve real world problems.

Amid vigorous growth in their industry, product lifecycle management (PLM) software developers are exploiting the cloud and machine learning to manage data and enhance the users’ experience.

More and more manufacturers are seeing productivity as a crucial factor to their business success. In the meantime, business models are changing from the large quantities and few variants to small quantities with frequently changed variants. This change requires high flexibility during production.