QUANTIFYING RELIABILITY DEGRADATION IN PROCESS PLANTS EXPOSED TO CYBER-PHYSICAL INTERFERENCE ON ROTATING EQUIPMENT SENSORS

Rotating equipment sensors play a vital role in process plants ensuring continuity of operation but they are more
vulnerable to cyber-physical interference than ever before that can silently compromise the reliability as time goes
by. In this paper, I will discuss the ways in which physical degradation and intentional and accidental interference
of the cyber domain corrupt sensor functionality, thus invalidating condition monitoring and predictive
maintenance systems. Based on the recent findings of vibrating screens, IoT-based sensor networks, secure state
estimation, and cross-domain attack vectors, the review provides evidence synthesis of the fact that reliability
degradation does not take place frequently through the same path. Rather, it is an outcome of mechanical stress,
environmental noise, manipulation of data, and interference on a signal-level. The research study suggests a
quantification model that incorporates drift analysis, noise variance analysis, and hybrid fault analysis as a solution
to improve the multifaceted dynamics of cyber-physical degradation within a rotating machine setting. The results
indicate that there is a requirement of cohesive evaluation techniques and more robust sensing systems, especially
in safety-related sectors when sensor drift or manipulation go unnoticed and result into capacity systemic
breakdowns.