Page 7 - Predictive Maintenance and Enhanced Quality with
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1.5 Key Components of Predictive
Maintenance Systems
Systems for predictive maintenance are made up of numerous
important parts. Data acquisition entails gathering pertinent
information from sensors and other sources, such as old
maintenance logs. Cleaning, organizing, and getting the data
ready for analysis are all parts of data preprocessing. The data is
subjected to analytics approaches, such as machine learning
algorithms, in order to identify trends, abnormalities, and
probable failure mechanisms. In order to decide on maintenance
actions like planning repairs or changing out components, the
data is then analyzed. The efficacy and dependability of
predictive maintenance systems depend on integration with
current maintenance systems and ongoing refinement of the
predictive models.
