Joe McKendrick

Digital twins offer a way to apply advanced analytics to derive insights that, in turn, drive optimization of production and operation processes.

Study finds that the movement to the edge is fundamentally changing the way organizations collect and analyze data.

The convergence of complementary technologies is making the machine economy and manufacturing as a service possible.

Supported by the power of artificial intelligence, digital twins can be deployed for preventive healthcare and other medical use cases.

Bringing the industrial metaverse to life will require substantial cross-industry collaborations on standards and infrastructure.

The proliferation of IoT is driven by process automation, digital transformation, and the rollout of 5G connectivity networks.

A key determinant of the utility of generative AI is the level of confidence humans place in the technology and how humans adapt to it.

Service organizations face many issues that increase the cost of providing services and limit gains in productivity. As such, many are turning to digital technologies for help.

One-third of manufacturers are hampered by “technology paralysis” that is preventing the success of their smart manufacturing efforts.

A new and improved strategy for detecting cyberattacks on manufacturing systems involves using AI to monitor a digital twin that mimics and is fed real-time data from the physical system.

Dashboards have limitations with today’s streaming and real-time data flows. The data may be changing so frequently that it is hard to even see what is changing.

Those choosing to start their AI journeys during a downturn face the dilemma of investing in expensive technology when revenues may be in short supply.