It is well said that “Diagnosis is not the end but a beginning for the professionals.” For an equipment diagnosis, all needed is details of equipment data in real-time, an ounce of inferencing intelligence, and a pound of computational accuracy. A diagnosis is a combination of Reliability and Validity of the Machine. Reliability refers to measuring how long the equipment performs its targeted processes, and Validity indicates its usefulness.
Reliability of equipment focuses on the efficiency of the equipment to operate consistently under mentioned regulations. Reliability is tested over time, across the equipment availability and the functioning of the equipment. For a manufacturing and processing industry, reliability is estimated based on equipment history, maintenance records, and equipment feasibility.
Diagnostic Services deliver information that can benefit maintenance and production officials by selecting the proper maintenance strategy. It sets appropriate production targets, stocking the maintenance spares, implementing suitable preventive measures, and providing vital prognostic data to optimize care pathways and management.
This serves to route the existing maintenance policy to Predictive Maintenance. Diagnostics generate relevant data (vibrations, temperature, acoustics, pressure, current, voltage, etc.) that can be transformed into a knowledge bank, thereby promoting and forecasting the reliability of the equipment.
The primary task of a diagnostic service is to obtain the equipment facts, automatically transform them into projections, deliver actionable insights, and prescribe initiatives to avoid unwanted equipment failures. The primary sources associated with the collection of equipment data are the deployment of sensors, from examination of the equipment history, or industrial standards or expertise of the maintenance team.
Subsequently, an AI-driven principle based on the study of the likelihood of symptoms of the faults encountered an earlier frequency of failures, followed by creating a correct and precise prediction supported with a remedial recommendation, accomplish a routine diagnostic service.
Without a definitive diagnosis of the abnormal or discrepant equipment performance, ordinary maintenance may be ineffective, laborious, and economically worthless. Trending the machine data, showcasing the spectra, a root cause analysis of the discrepancy in the behavior, and a professional point of view to confirm the breakdown with advancement to prevent the equipment failure further increase the equipment’s reliability.
For an OEM, Diagnostic Services supported with a Vibration Monitoring System equate a caring facility proposing a value chain triggered with data screening, systematic observation, and rule-based analysis. Moreover, the manufacturer gets the live equipment data to ensure the abiding of recommendations and thus ensure higher reliability of the equipment.
Infinite Uptime Diagnostic Service include deployment of an edge computing vibration monitoring sensor aptly named Industrial Data Enabler (IDE vEdge), obtaining the data on the mobile compatible dashboard and providing notifications and advice to enhance the availability and reliability of the equipment.
The Plug-and-Play service captures streaming triaxial vibrations, acoustic signals and temperature, trends and analyses to produce a spectrum as and when required. These data-driven insights authorize recommendations and corrective actions to avoid sudden unwanted downtime of the equipment.