The quality and quantity of lubricants used in vital machines impact their performance and longevity. Innovations in lubrication software and sensor technology add intelligence to lubrication programs. IIoT systems leveraging oil condition data further enhance preventive and predictive maintenance.
Lubrication process improvement
Mobile apps and oil monitoring systems streamline routine tasks. The new eLube app from SKF Lincoln spawned a new family of products, including its CLP Smart Series compact lubrication pumps that can be wirelessly set, monitored, and controlled using the app on a smartphone.
From the SKF eLube app, users “can check the status of their system or even initiate a lube sequence remotely. This feature streamlines the workflow for lube technicians, virtually eliminating the need to physically visit their individual systems,” observes James Verseman, automated lubrication systems (ALS) product manager at SKF Lincoln. “Time saved means more efficient operations and enhanced productivity.”
The LubePM mobile app from Noria Corporation extends its lubrication program management platform to include lubrication route management and execution. The cloud-based app elevates lube route efficiency, reduces lubricant waste, increases accountability, and provides real-time reporting and analytics.
Noria Corporation President Bennett Fitch says LubePM “enables technicians with a mobile tool to tackle daily lubrication tasks and help them learn best practices on the go. Behind the scenes, it doesn’t just store data; it contains algorithms to dynamically build lubrication job plans, optimize lubrication intervals and volumes, prioritize cost-avoidance initiatives, and report key metrics from everyday lube routes.”
The new LUBExpert ON-GUARD online monitoring system from SDT Ultrasound Solutions supports smart ultrasound-assisted relubrication. For Dylan Heit, a reliability manager in the pulp and paper industry, transitioning to ON-GUARD enabled continuous frontline asset health monitoring and alarming, precise autonomous condition-based lubrication functionality, and real-time temperature indication.
“We put SDT’s ON-GUARD to the test on a highly lubrication-sensitive asset, considering both temperature and response variabilities. The system’s condition-based lubrication data revealed a nearly 50% reduction in grease requirement at the non-drive end bearing location compared to the drive-end bearing on the same rotor, offering valuable insights for future program strategies,” Heit explains.
Lubrication meets IIoT
Real-time, continuous condition monitoring with the WearDetect IoT platform from Gill Sensors & Controls provides early warning of mechanical damage to ferrous components. It can detect and differentiate between normal wear (fine particles) and damaged component scenarios (coarse particles), trend fine particle wear rates, and send alerts to key personnel to avoid critical component failure.
According to John Warhurst, technical product specialist at Gill Sensors & Controls, no special training is required to interpret the data produced, making it a highly effective but simple addition to a condition monitoring strategy. “The maintenance team receives the earliest awareness of equipment wear and greater control over their preventative maintenance and production schedules,” he adds.
The OPTIME Ecosystem from Schaeffler merges smart condition monitoring with lubrication management, forming a comprehensive IoT predictive maintenance solution. Operated from a mobile app, it supports day-to-day maintenance operations and helps in creating data-based maintenance plans.
“By combining the plug-and-play functionality of our OPTIME CM sensors with the convenience of our intelligent OPTIME C1 automatic lubricator, the OPTIME Ecosystem allows customers to simplify two very important maintenance tasks, while at the same time benefitting from significant cost savings and contributing to sustainability by reducing unplanned downtimes and waste,” says Felix Tenner, VP of Schaeffler Lifetime Solutions Americas.
Collecting real-time data from a network of online oil quality sensors from Poseidon Systems and combining it with traditional lab samples and SCADA data enables robust oil analysis. Oil condition monitoring software in Poseidon Live, the company’s IIoT solution, enables this holistic view and understanding of oil health.
“There is a lot of buzz about generic failure prediction algorithms using ML or AI,” observes Jeff Lubkowski, director of product development at Poseidon Systems. “Our predictive algorithms integrate high quality, asset-specific data collected by our next-generation, real-time oil condition sensors, ensuring that we identify and prevent the ‘unexpected’ failures as well as those that are statistically likely.”
Machine Vitals sensor technology from Trico Corporation, a new addition to its Sensei IIoT Network, integrates into the headspace of oil reservoirs for real-time condition monitoring data collection to help bridge the gap between oil analysis intervals.
The integration of Machine Vitals' health data with historical maintenance logs offers a robust framework for comparative analysis when reviewing oil analysis results, notes Dan Freeland, application engineer at Trico Corporation. “And, if opting for oil analysis through Trico, it ensures that these results are woven into the Machine Vitals platform, providing a detailed and comprehensive insight into your machinery's condition.”
