<![CDATA[Maintenance is as important as any other company function. Because of the criticality of maintenance activities, careful planning is needed to carry it out so that the stoppage of the production process due to damage can be minimized. This can be prevented by diagnosing the machine to determine the fault or potential fault. Several diagnosis methods available for maintenance have been applied over the years including oil analysis, vibration signal analysis, particle analysis, corrosion monitoring, and wear debris analysis. Among these analyses, vibration signal analysis is emerging as a popular option as faults can be identified without stopping the machine as these signal changes often indicate the presence of faults. The method used in this study is vibration analysis using the GX microlog analyzer which will identify the vibration signal captured by the sensor and converted into a spectrum and stored in the cloud solution service so that the signal can be a reference for identifying overall problems with the equipment. The method used in this research is vibration analysis using GX microlog analyzer which will identify the vibration signal captured by the sensor and converted into a spectrum and stored in the clouds solution service so that the signal can be a reference for identifying overall problems in the equipment. From the results obtained enveloping spectrum bearing 22220CC horizontal side FFT analysis Indications on local defects in the inner track of the bearing on the bearing are shown with impulse frequencies 1X, 2X, 3X, 4X, 5X, and 6X FFT aligned with the peak amplitude of the vibration spectrum with a value of 18.02gE called Ball Pass Frequency Outer (BPFO). the results obtained velocity spectrum equipment horizontal side FFT analysis Indications on equipment misalignment that occurs 1X, 2X, peak.]]>
