IBM and National Instruments testing a true Industrial IoT testbed

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IBM and National Instruments have joined forces to create an equipment monitoring tool that links to the public cloud – offering the potential of true predictive maintenance for industrial organisations. See also: 12 best uses of IoT in the enterprise.

The cloud-based testbed could allow manufacturers that use connected devices to monitor the efficiency of its tools, so companies can predict faults before they occur.

A major obstacle to the industrial internet of things amongst manufacturing firms is legacy equipment that cannot communicate with other devices.

Many organisations are modifying equipment so they can connect to the IoT, like installing sensors or software.

IBM and National Instruments have created an “Industrial Internet of Things (lloT) testbed” which is a cloud based platform that allows organisations to better monitor and manage the health and performance of any connected device, machine or industrial equipment with information from these sensors.

The partners claim the platform will be able to detect early indicators of performance issues or failure in advance of catastrophic and costly repairs.

The technology combines NI’s measurement and edge computing system with IBM’s BlueMix platform-as-as-service. The testbed is currently in the National Instruments lab in Austin, Texas where it is being piloted on motor and fan monitoring. In the next phase of the pilot the testbed will be set up in a plant next year, Jamie Smith, director of embedded product systems at National Instruments told the IDG news service.

The testbed is part of a broader effort by the Industrial Internet Consortium (IIC) to bring together various technologies in industrial IoT so companies can feel confident in adopting it.

IIC formed in March 2014, with IBM, General Electric, AT&T, Intel and Cisco Systems were the founding members of the group, which now includes more than 100 companies. IIC has also started testbeds for energy microgrids, tracking and tracing of tools in factories, and software-defined infrastructure. 

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