Alpamayo offers PREKIT, an IoT and predictive analytics solution that integrates machine process data with expert insights to enhance machine availability and productivity in manufacturing. The platform enables real-time monitoring, predictive maintenance, and process optimization, significantly reducing unplanned downtime and total cost of ownership for production equipment.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often struggle with unplanned downtime and inefficient processes due to a lack of real-time visibility into machine performance and limited ability to predict potential failures. This results in increased costs, reduced productivity, and difficulty in optimizing machine operations.
Solution
Alpamayo's PREKIT is an IoT and predictive analytics solution designed to enhance machine availability and productivity in manufacturing environments. The platform integrates machine process data with expert insights, providing real-time monitoring, predictive maintenance capabilities, and process optimization tools. By connecting to machines via a preconfigured edge gateway and leveraging flexible data storage options, PREKIT enables users to gain a 360-degree view of their production processes, identify anomalies, and implement proactive measures to prevent downtime. The system uses AI-powered condition monitoring and process monitoring to detect potential issues early, allowing for targeted interventions and improved overall equipment effectiveness (OEE).
Target Audience
The primary target audience includes technology leaders in machine manufacturing and production, specifically OEMs and end-users seeking to improve machine performance and reduce downtime.
Features
- Preconfigured edge gateway with various hardware interfaces (e.g., RJ45-Ethernet) and standards (OPC-UA, MQTT) for easy machine connectivity
- Flexible data storage options, including cloud, on-premise virtual machines, and edge storage
- Real-time dashboards for visualizing machine data and key performance indicators (KPIs) without requiring IT expertise
- Root cause analysis tools that link data with system elements and failure modes, supported by AI-driven pattern recognition
- Online monitoring that calculates virtual data points for each machine cycle and triggers alarms based on predefined thresholds
- DeepFMEA framework to guide users through the process of tailoring monitoring to specific machines and potential issues
- Integration with Grafana and PowerBI for custom data visualization and dashboard creation
- Secure remote access via VPN (optional)