Yes, the software architecture can support predictive maintenance capabilities by utilizing data analytics and machine learning algorithms. By analyzing historical data and patterns, machine learning algorithms can be trained to identify potential issues and predict maintenance needs before they occur. The software architecture can incorporate data collection, storage, and processing components to gather and analyze data, as well as machine learning modules to develop predictive models. These models can then be integrated into the maintenance workflow to generate accurate predictions and optimize maintenance schedules.
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