Asset Management Automation Condition Monitoring IIoT Predictive Maintenance Reliability

Research Study Provides ‘Real-Time’ Findings for Maintenance 4.0

Grant Gerke | June 14, 2018

A lot of Industrie 4.0 research or analysis provide big takeaways for operations personnel, management, quality departments and maintenance technicians. Many takeaways from recent research or case studies reveal the influx of how predictive analytics— data visibility— and processes are dramatically changing workforce roles, like in the case of this oil and gas example with Pantera Energy Company, below.

In this case study of remote oil wells in the western part of the U.S., Pantera was able to transform their operations and maintenance technicians processes to act on “anomaly readings” with their Weatherford pump jacks in the field, according to Kepware.

Those rod pumps, pump jacks, they have their own local control systems that are monitoring some things, but you’re able to communicate to those from a central standpoint or wherever those pumpers are or whoever wants to be monitoring these things; they can check it out remotely and check out the efficiencies. Operators and Maintenance teams don’t want rod pumps going too fast when they hit, when they plunge down into the liquid and reservoir, equipment can be damaged.

These types of applications are transforming the original mission of maintenance teams and technicians and a recent study from Emory University provides even more depth to the topic with their “Future of IIoT Predictive Maintenance” report.  The study’s goal was to identify the gaps between business drivers and the reality of implementation, according to the press release.  The study surveys 103 O&M professionals across Europe, North America, and Asia Pacific. A combination of quantitative research (online survey) and in-depth interviews were used.

The research is great deep dive into many related topics to Industrie 4.0 and maintenance. Here’s a short list of some topics:

  • The current state of Predictive Maintenance in industrial plants
  • The level of satisfaction with current Predictive Maintenance systems
  • IIoT Maintenance systems most likely to be adopted within the next five years
  • The extent to which the Digital Twin is likely to be deployed
  • The disconnect between executives and O&M professionals responsible for implementation
  • Reasons for delays in investments in new IIoT Predictive Maintenance solutions

Efficient Plant’s take: There’s a lot of meat on the bone with this report, even though 103 people is a small online survey sample. With the interview as a counterpoint, this report provides thorough predictive maintenance information with the backstop of Industrie 4.0. Below is part of the report’s summary and take it for what’s its worth:

Concerns that are raised about PdM4.0 and Maintenance 4.0 stem from practical considerations regarding the feasibility of deployment and the lack of resources. O&M professionals view PdM4.0 positively but expect an incremental change in the form of improvements to existing systems and processes.

>> Find the “Future of IIoT Predictive Maintenance report” here (login reqd)

 

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Grant Gerke

Grant Gerke

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