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Well into the 21st century, the medical industry faces a host of intriguing challenges, from aging populations to a growing range of personalized and at-home diagnostic and care devices—all set against a backdrop of increasing digital collection, transfer and storage of sensitive patient data.

If you’re feeling a bit overwhelmed by the prospect of Industry 4.0, and perhaps a bit sheepish about your lack of progress, you’ve got good company.

Amid predictions of global economic slowdowns and several recent PMI readings indicating manufacturing contraction, it becomes easy to see how slow production performance and data inefficiencies throughout the manufacturing supply chain contribute to economic uncertainty and concerns for future business.

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

The U.S. Army is working assiduously to flight-qualify engine parts it has redesigned using additive manufacturing (AM).

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.

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.

Cofounder Johannes Trabert, who lives a poetic life in the Thuringian Forest, says the future will be focused on ‘the clever share of work’ between humans and robots.

The industrial revolution of today, called Industry 4.0, is driven by the interconnectedness of advanced technology, automation, robotics, and real-time data, also called the Internet of Things (IoT). While these cyber-physical systems can autonomously exchange information to trigger actions and make decentralized decisions, it’s impossible to dismiss the importance of the human element in manufacturing.

Machine vision is proving ideal in helping humans perform tedious but crucial manufacturing tasks. That is why it is poised to grow significantly in the next few years.