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Predictive maintenance evaluates the condition of equipment by performing periodic (offline) or continuous (online) equipment condition monitoring.The ultimate goal of the approach is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold.
An intelligent maintenance system is a system that uses data analysis and decision support tools to predict and prevent the potential failure of machines. The recent advancement in information technology, computers, and electronics have facilitated the design and implementation of such systems.
Condition monitoring techniques are normally used on rotating equipment, auxiliary systems and other machinery like belt-driven equipment, (compressors, pumps, electric motors, internal combustion engines, presses), while periodic inspection using non-destructive testing (NDT) techniques and fit for service (FFS) [1] evaluation are used for ...
MindSphere is an industrial IoT-as-a-service solution [1] developed by Siemens for applications in the context of the Internet of Things (). [2] MindSphere stores operational data and makes it accessible through digital applications (“MindSphere applications”) to allow industrial customers to make decisions based on valuable factual information. [3]
Predictive maintenance techniques are designed to help determine the condition of in-service equipment in order to estimate when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance , because tasks are performed only when warranted.
Advanced ways of product and asset maintenance and management come within reach as there is a digital twin of the real 'thing' with real-time capabilities. [ 40 ] Digital twins offer a great amount of business potential by predicting the future instead of analyzing the past of the manufacturing process. [ 41 ]
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