Enables AI assistants to analyze plant-floor data using OEE, Pareto, SPC, and yield-loss calculations, providing continuous-improvement insights from manufacturing data.
Enables predictive maintenance for electric motors by analyzing stator current signals to detect faults like broken rotor bars, bearing defects, and eccentricity, using spectral and envelope analysis techniques.
Enables natural language analysis of mechanical test data files (CSV, TDMS, MDF) by providing tools for channel statistics, spectrum analysis, rainflow fatigue counting, thermal state detection, and report generation.
Enables engineers and plant managers to interact with manufacturing systems using natural language, providing machine health analysis, KPI dashboards, predictive maintenance, and automated workflow execution via MCP.
An AI agent system that monitors manufacturing equipment health using the Model Context Protocol (MCP). Enables answering natural language questions about equipment status, maintenance, and anomalies through MCP tools.
Enables AI assistants to monitor and interact with industrial systems, providing real-time system health monitoring, operational data analytics, and equipment maintenance tracking. Built with Next.js and designed for industrial automation environments.