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Purchasing and supply executives expect manufacturing to continue expanding in 2019, according to a survey by the Institute for Supply Management.

The bane of modern engineering is complexity. One promise of artificial intelligence and machine learning is helping engineers to use complex tools and harness vast data sets effectively.

As additive manufacturing (AM) moves from prototypes to mass production, manufacturers are setting their sights on the holy grails—the products and processes that will be game-changers. Many game-changers are already in play.

Cyber criminals are increasingly setting their sights on today’s digitized manufacturing industry as an entry point into government and commercial supply chains.

There is no shortage of competition in a global market. As a manufacturer trying to get ahead of the pack, automation can help with problems like a limited skilled labor force, quality control issues and suboptimal throughput. But the high initial cost and extended implementation time can be deterrents.

As with any digital transformation process, the devil is in the details, and there are many potential pitfalls that can derail projects.

Manufacturers are facing shrinking product lifecycles with frequently changing customer demands. As a result, they need agile production and flexible factory layouts that can easily be modified whenever needed.

Most companies do not have a clear strategy for how they are applying IoT, Mark Weatherford, former Deputy Under Secretary for Cybersecurity at the Department of Homeland Security, said at an exclusive roundtable Smart Manufacturing convened recently in Chicago.

Two main approaches exist with respect to product configuration: sales/marketing and engineering-focused strategies. The former has advantages, but could lead to gaps in what a customer is promised to what can be delivered.

Recycling increases efficiency, enhances brand image and saves money.