NeenOpal Assisted Diagnosis and Troubleshooting for Industry

## Key Features

• **AI-powered diagnostic assistant**: Real-time troubleshooting guidance using Amazon Q and Amazon Bedrock.
• **Natural language interface**: Query systems conversationally for faster insight retrieval.
• **Sensor and OT data integration**: AWS IoT SiteWise integration for equipment health monitoring.
• **Knowledge retrieval with RAG**: Access SOPs, manuals, and maintenance logs for contextual answers.
• **Automated work order creation**: AI recommendations trigger corrective actions within ERP/CMMS systems.
• **Seamless workflow integration**: Works across SCADA, MES, ERP, and ticketing platforms.

## Benefits

• **Reduced downtime**: Faster root cause detection minimizes operational disruptions.
• **Improved OEE**: AI-optimized diagnostics maximize equipment uptime.
• **Operational visibility**: Real-time health and performance insights across production lines.
• **Data-driven maintenance**: Preventive strategies powered by IoT sensor data.
• **Optimized workforce efficiency**: Empower operators to resolve issues without deep technical expertise.
• **Rapid time-to-value**: Get started with a fully functional PoC in under 60 minutes.

## Security and Data Handling

The solution deploys entirely within your own AWS account, ensuring your operational data never leaves your environment. Data at rest and in transit is encrypted using AWS-native encryption services. Access controls leverage AWS IAM policies, and the solution is FTR (Foundational Technical Review) validated by AWS, confirming adherence to AWS security best practices.

## Use Cases

• **Predictive Maintenance for Manufacturing**: Anticipate and prevent breakdowns on production equipment such as CNC machines, compressors, and conveyor systems using AI analysis of IoT sensor data streams.
• **Production Line Troubleshooting**: Quickly resolve bottlenecks and equipment failures in automotive assembly, food and beverage packaging, or pharmaceutical batch processing environments.
• **Knowledge Augmentation for Technicians**: Provide maintenance teams with AI-curated guidance drawn from historical resolutions, SOPs, and equipment manuals.
• **Automated Workflow Orchestration**: Streamline ticketing, work orders, and corrective actions across integrated ERP and CMMS platforms.

## Prerequisites and Scope

• An active AWS account with permissions to deploy CloudFormation stacks.
• AWS IoT SiteWise configured for target equipment (or NeenOpal can assist with setup).
• Access to relevant documentation (SOPs, maintenance logs, equipment manuals) for RAG indexing.
• The pre-built accelerator supports standard industrial protocols and is designed for initial deployments covering production lines with IoT-connected assets.

## How It Works

• Operators interact with the AI assistant using natural language.
• The system queries IoT sensor data, maintenance logs, and SOPs using RAG.
• AI delivers real-time recommendations for diagnosis and corrective actions.
• Insights can trigger automated work orders and integrate with ERP/CMMS systems.

## Getting Started

• **Discovery**: Engage NeenOpal to scope user roles, equipment, and workflows.
• **Deploy**: Launch the pre-built accelerator in under 60 minutes in your AWS environment.
• **Validate**: Run a Proof of Concept by connecting IoT sensor data, maintenance logs, and SOPs.
• **Scale**: Fine-tune and expand for production-ready troubleshooting and predictive maintenance.

To begin, contact us at aws_marketplace@neenopal.com to schedule a discovery call and plan your 60-minute PoC deployment.