Reliability expert Jack Nicholas discussed in a recent webinar how to transition maintenance teams to Industry 4.0.
He discussed how data and advanced analytics will transform operations, maintenance, and reliability (OM&R). In addition, he provided helpful steps for a digital transition.
Several attendees submitted questions to Nicholas during the webinar, and his answers can be found below.
Every time SCADA registers an alarm or alert that results in remedial action, an opportunity for cost avoidance calculation presents itself. The actual cost to return the asset to normal running condition (without any lost production) is compared to what theoretically would have been the cost of not having the warning from SCADA and having the asset run to complete failure. The difference is maintenance cost avoidance.
If you include unrecoverable lost production, this can be quite substantial. For example, if the lost unrecoverable output is $30,000/hour, that number times the number of hours of downtime would be added to the maintenance cost difference of repair to reflect total cost avoidance. Compare that number to the cost of SCADA (which may include labor cost for SCADA upkeep and analysis and capital investment –prorated over time in years, usually). That is your ROI in SCADA data management for a specified time.
Refer to the subject of Data Farming presented in the webinar. Look at the article in OCT/NOV 2019 Uptime magazine with that title at www.reliabilityweb.com/Uptime for more detail on this. Select failures derived from the methodologies discussed as “seed sources” – Reliability Centered Maintenance (RCM), Root Cause Analysis or Defect Elimination. Start with the most critical (e.g., costly failures you are trying to detect), and collect data that indicates the onset of those failure(s). Whether you do this manually (not recommended in today’s world) or with Industry 4.0/IoT digital approach, this will provide the best chance for success from both reliability and financial standpoints.
Most of the benefits will come from a data analysis at the edge or inside any firewalls you employ at your site. Start there. Educate yourself concerning sending data off site (e.g., to a cloud) based on information from prospective cloud service providers.
Cybersecurity is a specialty area in which all the leading providers invest significantly and employ experts to protect their data centers. They also provide support for their clients in the form of encryption regimes, services, and products that companies routinely update in the face of a continually increasing number of threats. Cybersecurity assurance and assistance should be an essential element of any competitive contract award for Industry 4.0 services.
The type(s) of sensors depends on the failure modes you’re able to derive from RCM analysis of the specific compressor you have. The device would almost certainly involve vibration, temperature, and pressure sensors as well as run-time tabulators (indicative of the amount of legitimate demand and leaks present in the system).
Lubricant condition sensors may also be needed, depending upon the design of that compressor sub-system. Online motor monitoring sensors (current, voltage, power with capability for waveform analysis) may also be needed to detect otherwise undetectable internal electrical defect emergence. These electrical sensors may be integral to the motor control center modules but should be digitally connected to a central analysis computer elsewhere in the plant.
To the best of my knowledge, there is no ISO standard just for cloud security. The ISO/IEC 27000 series of standards is getting the most up-to-date general cybersecurity attention now, but look at the Wikipedia write-up at https://en.wikipedia.org/wiki/Cyber_security_standards for much more on this subject from US sources like the National Bureau of Standards (800 series of documents).
For more from Jack Nicholas, listen to the complete webinar here.