AmbaFlex spiral conveyors were failing unpredictably, causing millions in downtime losses and hours of work. As the Q2BSTUDIO team, we designed and developed a fast and scalable solution: a real-time dashboard built with Python that visualizes sensor data and enables instant diagnostics.
The idea came from observing that failures were visible in the data but not in operational routines. We implemented a lightweight telemetry pipeline that collects vibration, temperature, and motor status signals and sends them to a real-time ingestion service. Thanks to open source technologies and a Python backend with WebSockets, technicians see critical information in seconds at no license cost.
The dashboard offers intuitive visualizations, smart alerts, and historical traceability to identify failure patterns. With time-series storage and simple detection models based on rules and machine learning, we managed to reduce escalations and resolve on-site incidents in minutes. The result was the recovery of thousands of hours per year and a significant drop in downtime.
Q2BSTUDIO, a company specialized in custom software and application development, led the project and contributed expertise in custom software, artificial intelligence, and cybersecurity. We designed the architecture with integrations with AWS and Azure cloud services in mind to facilitate multi-site deployments and high availability without relying on proprietary licenses.
In addition to the Python dashboard, we integrated advanced analytics options and business intelligence services to turn operational data into actionable decisions. This included Power BI connectors that allow plant managers and executives to view corporate KPIs and perform ad hoc analysis.
The solution incorporates cybersecurity principles from the design stage to protect telemetry and ensure operational continuity. At Q2BSTUDIO, we combine communication hardening, strong authentication, and cloud security practices to protect connected industrial equipment.
To enhance diagnostic capability, we applied artificial intelligence components and enterprise AI: anomaly detection models, AI agents that prioritize alarms, and automatic recommendations for technicians. These AI agents help reduce the learning curve and make the solution accessible to plant staff.
The modular approach allowed the tool to scale to multiple plants with no licensing cost and minimal adaptations. As a result, operations gained autonomy, calls to specialized support were reduced, and predictive maintenance was optimized.
If you are looking for a similar solution, at Q2BSTUDIO we offer custom application development and custom software, integrations with AWS and Azure cloud services, business intelligence services, artificial intelligence and cybersecurity projects, as well as deployments with AI agents and Power BI dashboards so that industrial data drives real improvements in your operations.
This AmbaFlex case demonstrates how the combination of software engineering, artificial intelligence, cybersecurity, and cloud services can transform recurring problems into competitive advantages, reducing costs and empowering the operational team at every plant.
