Challenge
The client builds and maintains large-scale conveyor lines used in distribution centers worldwide. Each line consists of dozens of independent conveyor modules and hundreds of sensors that track temperature, vibration, belt tension, rotation speed, and other operational metrics.
Before the project, engineers manually inspected each conveyor on site, checked data from different sensor vendors, and decided when a component needed replacement. Every conveyor line had its own local manager, and data was fragmented across multiple tools.
This created three critical risks:
- High chance of unexpected line stoppage due to late replacement
- Large capital freezes from overstocking spare parts
- Long reaction times because engineers needed to physically visit the site
The client needed a unified digital system that visualizes all equipment, analyzes sensor behavior in real time, predicts part wear, and automatically triggers spare part orders based on actual data instead of assumptions.
Our Approach
We combined edge sensor data, ML (machine learning) algorithms, predictive modeling, and a fully redesigned interface to create a single source of truth for every conveyor line worldwide.
Product and Design
Comprehensive workflow discovery and modernized interface
- Discovered workflows with engineers and maintenance teams
- Updated UI and UX for real time monitoring
- Created 3D models showing live status of each component
- Conducted usability tests and stakeholder workshops
Development and Stack
Scalable backend with unified sensor integration
- Unified data from multiple sensor providers via OPC UA and MQTT
- Built a scalable backend with .NET 8 and Azure Functions
- Integrated global CRM and warehouse systems for inventory checks
- Enabled instant updates through SignalR driven live dashboards
Predictive Intelligence and Automation
ML-powered wear prediction and automated ordering
- Implemented wear prediction models analyzing tension, vibration, heat, and rotation patterns
- Set thresholds for automated pre ordering based on lifetime forecasts
- Reduced manual inspections by modeling part degradation behavior over time
Solution
We delivered a predictive maintenance platform with a fully modernized interface and real time 3D visualization. The system analyzes each conveyor module independently, tracks the health of every component, calculates expected lifetime, and predicts the exact moment when a part should be replaced.
The platform enables the company to monitor every conveyor line they installed for their customers across the globe, consolidating data into a single control center. Engineers can now supervise hundreds of facilities worldwide without being physically present onsite.
To extend accessibility, we also built a lightweight mobile version using React Native. It provides simplified dashboards, quick alerts, real time notifications, and fast status checks designed specifically for field technicians and on site maintenance teams.
It checks spare part availability across warehouses, sends automated supplier requests if stock is low, and considers delivery time to prevent any disruption. Monitoring now happens from a single unified interface covering facilities across continents.
Key Capabilities
- Real time 3D monitoring of every conveyor line
- Predictive wear modeling for each component
- Automated spare part ordering and supplier requests
- Global visibility across all customer facilities
- Mobile app for field engineers on React Native
- Unified sensor data from different vendors
- Updated UI aligned with engineer workflows and real usage
Why It Matters
This project showcases how ML powered analytics, modern cloud architecture, and intelligent automation can transform industrial maintenance. The results prove that predictive maintenance dramatically reduces operational risk and eliminates unnecessary costs tied to oversized spare part warehouses.
It also highlights Excality’s strengths in large-scale project development, cloud automation, and product design integration. By unifying complex sensor ecosystems, enhancing UX with real-time 3D interfaces, and orchestrating AI-driven workflows, we help industrial companies achieve a new level of efficiency and reliability.