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What do digital manufacturing technologies gain from IoT technologies?

IoT technologies can support a digital manufacturing approach in a myriad of ways, especially in data gathering. Here's a deeper look.

Digital manufacturing is a blanket term that describes the growing presence of digital processes and information related to product definitions and specifications, manufacturing instructions, production data, performance and service data, and so on, which support the actual design, manufacturing and distribution of products.

A digital thread, which is part of the digital manufacturing technologies concept, is the data that connects the myriad digital manufacturing processes and records together to document a product's progress through its entire lifecycle and to drive efficiencies.

The internet of things (IoT) environment is made up of the inexpensive, connected sensors and smart devices that are pervading our world, and making a veritable flood of data available to people and organizations.

In the industrial manifestation of IoT -- aptly called industrial IoT, or IIoT -- these sensors and devices capture and deliver data that provides unprecedented visibility and control in the plant and throughout the supply chain.

While digital manufacturing can exist without IIoT, the presence of automated data collection points can greatly enhance the digital trail and bolster the extent of what digital manufacturing technologies can accomplish.

At its most basic level, digital manufacturing is concerned with engineering data -- product definitions, bills of material and engineering specifications -- supported by engineering data from computer-aided design/computer-aided manufacturing systems, including analytics, process definitions, manufacturing details and simulations. As this basic data is carried through the digital thread, manufacturing data and field performance can be added to complete the record for the product.  This enables further analysis in support of advanced design, product improvement, support and logistics; for example, the data collected can assist with spares and service planning.

IIoT provides the tools to both multiply the amount of data that can be collected in the manufacturing, distribution and use of the product, and to improve the quality of the data. Connected, automated sensors and devices can collect data more frequently, even continuously, if that is justified. The data is also collected more accurately, since eliminating the human element reduces the opportunity for erroneous entries, lost data and mistakes. IIoT can also relay the data to the digital thread instantly over the internet or a cellular network.

One of the biggest challenges with IIoT is handling and making productive use of the IIoT data. New software is evolving to deal with the volume, velocity and variety of big data, and new, expanded analytics capabilities are racing to catch up with the growing need to uncover the valuable information buried in this data tsunami to make it useful.

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