IIoT Devices and Work Management Processes in Reliable Operations

Reliable process manufacturing and production is one of the pillars of top performing companies. In the ARC Advisory Group’s Industrial IoT/Industrie 4.0 Viewpoints blog, IBM guest blogger Jim Crosskey highlights the role of the industrial Internet of Things (IIoT). In his post, Defining Asset Condition in the context of IIOT, he opens:

As I travel around speaking with organizations on the topic of leveraging the Industrial Internet of Things (IIoT) for assessing and acting upon asset condition, I find it interesting to understand different people’s definition of what “condition” means and how it can be represented and leveraged to improve asset reliability and maintenance efficiency. While one would think that condition is a universal assessment understandable by all, in most cases it depends on who you are and how you might want to leverage information related to the asset.

He highlights the different needs for asset condition information for different roles including maintenance managers, reliability managers and operation managers.

He closes the post with these thoughts and invites reader feedback:

As we leverage the IIOT then, collecting and analyzing real time information is but one element of understanding asset condition in a way that is useful to inform the people managing the lifecycle of that asset. For us to realize the true value of condition based maintenance, we must integrate the insights from IIOT with existing information in asset management systems, and other enterprise applications.

Emerson's Will Goetz


Emerson’s Will Goetz shared his thoughts on the post with me. He agrees with Jim’s points and thinks that reliability engineering is integral in assembling a composite view of asset condition from multiple inputs that IIoT-enabled sensors and final control elements provide.

The asset condition should be established based on the failure modes surfaced by the IIoT devices. Thoughtfully planned and established practices by the reliability engineering team helps to clearly define these failure modes.

Will noted that predictive analytics provide an additional layer as a safety net to provide early warning of failure conditions.

The bottom line is that IIoT-based condition monitoring capabilities can be used to drive a well-designed work management process in order to reduce safety risks, increase overall availability and lower maintenance costs.

The asset condition composite views enabled by IIoT devices ultimately help drive more objective business decisions on when to run and when to repair impaired equipment.

Add your thoughts to the original post on the ARC Advisory Group blog post or below in the comment section of this post.

Posted Thursday, October 22nd, 2015 under Asset Optimization, Industrial IOT, Reliability.

One comment so far

  1. Corrosion, vibration, valve leaks, trap leaks, and temperature etc., in my personal opinion, are good examples of where automatic data collection is taking the place of manual data collection with portable testers. All these can be done using wireless transmitters instead of portable testers. This is more productive. Personnel can spend their time acting on data rather than collecting it. Old plants are now being modernized and new plants are already being built this way:
    https://www.linkedin.com/pulse/dont-build-your-new-plant-old-jonas-berge

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