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Put the paper and pencil away. Hybrid data management and analysis systems-where users combine paper tracking with computer processing-are no longer meeting the needs of manufacturers for speed, accuracy, traceability and compliance with regulations.

Industrial robots are becoming easier to program, more versatile, more cost-effective, more accurate and more mobile. These changes are lowering barriers to entry, shortening return on investment and making robots a more practical investment.

As I walked the floor this spring at North America’s largest trade show for automation technologies, Industry 4.0 was on everybody’s lips. One of the more complex of our industrial revolutions, Industry 4.0 has been about the Internet of Things: digitizing and connecting things.

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.

Cloud technology presents manufacturers with opportunities to improve the flexibility, scalability and efficiency of their operations. Realizing these benefits will require more than simply doing a one-to-one transfer of current technology to cloud-based servers.

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.

Hybrid manufacturing—using one machine to perform both additive and conventional subtractive manufacturing processes—is gaining traction across manufacturing sectors, allowing companies to leverage the benefits of both.

The German metrology developer Jenoptik is shifting “from focusing on metrology and laser processing standalone equipment to integrated automation solutions for the automotive industry.

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.

Convergence-enabled cyberattacks—where criminals exploit traditionally isolated operational technology (OT) devices through their new connections to the IT network—may be motivated by the desire to hijack and demand ransom for services, steal trade secrets through industrial or national cyberespionage, or commit cyberterrorism or engage in cyberwarfare.