Develop an enterprise asset management system with modules for equipment tracking, maintenance scheduling, and reporting. Use AI to predict maintenance requirements, reducing downtime and extending equipment lifecycle.
Implement modules for asset registration, maintenance schedules, and status reporting.
Design a database to store asset information, usage logs, and maintenance history.
Implement secure login and role-based access for maintenance teams and managers.
Preprocess historical maintenance and usage data to train AI models for predictive maintenance.
Integrate AI predictions into the maintenance scheduling module.
Develop dashboards to monitor asset health, upcoming maintenance, and cost analytics.
Test all modules and AI predictions for accuracy and reliability.
Implement error handling, logging, and backup mechanisms.
Document system architecture, AI workflow, and deployment methodology.
