Core Concepts | AI-Automation
1 . Automation : Computers handling manual tasks by following stepby-step instructions ( scripts ) and rules ( conditions ) to streamline a process . ( Tool for Autonomy )
• Automated Data Entry : Automatically inputting sensor data from field instruments into project management systems , streamlining internal data collection for maintenance activities .
2 . Machine Learning ( ML ): Computers learning patterns by studying large data sets and various sources . ( Subset of AI )
• Sensor Data Analysis : Analyzing sensor data from machinery to identify patterns of wear and tear for more accurate internal maintenance scheduling .
3 . Machine Learning Model ( MLM ): The guidebook created for computers to predict outcomes by comparing new data to the learned patterns . ( Product of ML )
• Maintenance Prediction Models : Developing custom models to predict machinery component failure based on sensor data , client feedback , manufacturer specs , and historical project data to refine predictions and optimize internal service standards .
4 . AI ( Artificial Intelligence ): Computers deploying MLM ’ s to perform tasks that would be otherwise dependent on human intelligence . ( The Domain )
• Automated Maintenance Scheduling : Using AI and automation to schedule maintenance tasks based on predictions from the maintenance prediction models , enhancing internal processes and resource allocation .
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