AI-Powered Manufacturing Command Centre for Operational Intelligence

Manufacturing operations often suffer from fragmented data, reactive maintenance, and costly unplanned downtime.

The Manufacturing Command Centre from NeenOpal leverages Amazon Q, AWS IoT SiteWise, Lambda, Timestream, S3, QuickSight, and Managed Grafana to provide operators and managers with a unified, real-time view of equipment performance, production workflows, and predictive insights. The solution integrates AI-powered diagnostic models and predictive maintenance capabilities to accelerate decision-making and improve operational efficiency.

Our turnkey accelerator can be deployed in your AWS environment in under 60 minutes, providing immediate access to actionable insights. From there, it can be customized to your manufacturing environment, connected to ERP, MES, and CMMS systems, and scaled to meet evolving operational needs.

Key Features

• AI-driven operational insights: Real-time predictive analytics and equipment health monitoring.
• Natural language interface: Query production, maintenance, and telemetry data conversationally via Amazon Q.
• IoT and OT integration: Collect, process, and visualize sensor data with AWS IoT SiteWise and Timestream.
• Knowledge retrieval with RAG: Access SOPs, manuals, and historical repair logs for contextual recommendations.
• Automated alerts & workflows: Trigger notifications or corrective actions in ERP/CMMS systems.
• Customizable dashboards: Pre-built visualizations in QuickSight and Managed Grafana for production monitoring and KPI tracking.

Benefits

• Reduced unplanned downtime: Predictive alerts and AI insights prevent equipment failures.
• Improved production efficiency: Optimize workflows and OEE with data-driven recommendations.
• Enhanced operational visibility: Centralized real-time insights across all manufacturing processes.
• Data-driven maintenance strategies: Move from reactive to preventive and predictive maintenance.
• Empowered workforce: Operators and engineers make faster, informed decisions.
• Rapid deployment: Start with a fully functional PoC in under 60 minutes.

Use Cases

• Predictive Maintenance: Anticipate failures and schedule repairs proactively.
• Production Optimization: Identify bottlenecks and improve throughput.
• Equipment Health Monitoring: Real-time monitoring of critical machinery.
• Knowledge Augmentation: AI-assisted guidance for operators and technicians.
• Workflow Automation: Integrate alerts and recommendations with ERP/MES/CMMS.

How It Works

• Operators and managers interact with the AI assistant via natural language.
• IoT and historical data, SOPs, and repair logs are queried using RAG.
• AI provides real-time diagnostics, predictive alerts, and actionable recommendations.
• Recommendations can automatically trigger work orders, alerts, or integration with operational systems.

Getting Started

• Engage NeenOpal to define user roles, processes, and data sources.
• Deploy the pre-built accelerator in your AWS environment in less than 60 minutes.
• Connect IoT sensor data, maintenance logs, and SOPs for a PoC.
• Fine-tune AI models and dashboards to scale for production-ready operational intelligence.