Reliability monitoring can include reactive, predictive, and proactive measures to extend service life of rotating equipment. While reactive measures are clearly defined as reacting to alerts rather than acting first to change or prevent the alerts, it is somewhat of a gray area for predictive and proactive measures as they are often interchangeably used. Predictive monitoring is quite different as it relates to the ability to predict future events based on past observations. It is increasingly and successfully performed with support from machine learning techniques where large amounts of data are available that are proven to be related to failure in the long run. To be more precise, using machine learning techniques do not make your reliability monitoring proactive, it makes it more predictive and provides alerts based on past data. To the contrary, proactive reliability monitoring can be defined as identifying and controlling alerts rather than just responding to alerts after they have occurred, basically acting earlier. For a priori and proactive reliability monitoring, one must be able to see the future operating performance, even before the operation has begun. The technology must be able to anticipate risks based on the design of the rotating equipment so you can establish and sharpen evidence-based maintenance strategies.
Quite often, operators are hesitant to implement innovative proactive technologies to support their current setup. Operators are faced with paradoxical situation from which they, at first, cannot escape from when asked by their management: “Why should use a priori and proactive technology and apply lower-cost corrective actions at all if neither damage nor failure has occurred yet? What is the added value for me at this point? It seems like magic – I’d rather conduct traditional condition monitoring because it actually alerts me that damage has occurred that leads to failure, even if the necessary countermeasures will be more costly.” As an analogy: it is largely undisputed that ignoring proactive measures such as exercise, plant-based nutrition, and avoiding smoking reduces the risk of major adverse health effects – healthcare professionals can predict and know that unhealthy life choices promote illness and premature death. Unfortunately, only too often are people starting to implement reactive measures once their health has declined in order to salvage any health they have left – it can still be beneficial but, in the long-term, the costs of reactive health measures are much higher than proactive measures. Thus, personalized, precision medicine has been on the rise over the past decades to provide a priori and proactive measures by identifying genetic risk factors in patients before health issues arise and burdens the healthcare system – the same principles can be applied in reliability monitoring of rotating equipment.
Based on the pure nature of a priori and proactive monitoring, risk alerts are expected changes to the system. However, these changes may not be directly linked to failure of the operation – just yet. This loop must be closed so a priori and proactive risk assessment becomes a useful condition monitoring strategy with risks that are known to lead to failure. In tribology, failures are caused by cascading events and their effects can be monitored by various sensors utilized throughout the service life of the rotating equipment.
At 4LinesFusion, we have developed algorithms proven to simulate cascading events and decipher lubricated chemistry together with the interface in an unique way as part of our product, SeerWorksTM Reliability. In our recently published, peer-reviewed publication we have illustrated how SeerWorksTM Reliability provides a priori and proactive alert for lubricants prior to their use in bearing tests and these alerts were directly linked to bearing failure. SeerWorksTM Reliability is a fully automated cloud solution that is offered following a Software-as-a-Service business model and allows our customers to look at future risk potential of their operation, throughout the lifecycle of their application.
Early detection of damage onset in rotation equipment is an essential part of successful condition monitoring. It is undisputable the a priori and proactive reliability monitoring can provide the operator of rotating equipment with massive cost saving. Not only is SeerWorksTM Reliability able to provide a priori and proactive alerts as part of quality control, prior to operation, but also during continuous monitoring to support evidence-based maintenance. No lubricant stays pristine throughout its application in the field; minor differences within the lubricant can make all the difference to reliability. Together with a priori alerts and with highly sensitive sensors (e.g., “Oil Quality” sensors), early changes in the lubricant can be detected and trigger oil sample analyses, followed by SeerWorksTM Reliability risk assessments. Combining a priori risk assessment, real-time “Oil Quality” monitoring, and oil sample analyses snapshots, SeerWorksTM Reliability increases the precision of industry-standard reliability monitoring to provides you with the most proactive reliability monitoring of your operation on the market today – at the click of a button!
To learn more about SeerWorksTM Reliability, contact 4LinesFusion at [email protected]