Machinery Lubrication magazine published by Noria Corporation
Issue link: https://www.e-digitaleditions.com/i/1463313
4 | March - April 2022 | www . machinerylubrication.com AS I SEE IT clockwise from the left side, you can see particle count, analytical ferrography, ferrous density, elemental analysis, etc. e tip of these spikes approximates the point of earliest detec- tion (P) in the time domain. e diameter of the spikes is the signal strength (amplitude) at that point in the time domain. e signal strength becomes greater as failure progresses. From the CAM graphic, you can get an idea of the condition monitoring methods that are the most promising for early detec- tion. Note that the placement and shape of the spikes can vary as influenced by various factors, including skill, technology, frequency of use, machine type, etc. As such, the CAM graphic can be tweaked to more accurately fit the application. While this CAM is representing mechan- ical looseness as the failure mode, other similar CAMs would be constructed for each highly ranked failure mode, such as contaminated oil, wrong oil, misalignment, etc. Detection-Based CAM Graphic While Figure 2 presents a single failure mode (looseness) against multiple detection methods, Figure 3 presents the chart in inverse form. Specifically, it shows a single detec- tion method (sight glass inspection) against multiple failure modes. Each spike has the same meaning as previously described. Early detection and effectiveness of detection are characterized by the length and width of the spike. Similar CAM graphs could be constructed for each of the other detection methods being considered, such as vibration, ultrasound, etc. Pareto-Based CAM Graphic e Pareto Principle provides a practical ranking of failure modes based on the prob- ability of occurrence and consequences. is ranking comes from experience and RCM methods such as Failure Modes Effects Anal- ysis (FMEA). Root Cause Analysis (RCA) can be extremely helpful too. e CAM graphic in Figure 4 shows the failure modes for rolling element bearings What's included in the Infographic GRAPHIC FORM RANKED FAILURE MODES DETECTABLE FAILURE SIGNALS TIME DOMAIN TO FAILURE CONDITION MONITORING DETECTION METHODS P-F Interval X X X Remain Useful Life Chart X X X Pareto Principle X X X Weibull Analysis X X X Condition Alarm Mapping (CAM) Figure 1. How conventional infographics used in condition monitoring compare to Condition Alarm Mapping Figure 2. Mechanical Looseness (FM) DB - Detection-Based PB - Pareto-based