Predictive Maintenance

Predictive maintenance support

Predictive Maintenance

Predictive maintenance support

WHAT WE OFFER YOU

Anticipating failures is now possible thanks to data analysis and a data-driven approach.
KyberEdge helps you transition from reactive maintenance to predictive and planned maintenance by leveraging data collected from machines to identify drifts, anomalies, and early warning signs. We integrate these systems with ERP or CMMS platforms to automate intervention management and reduce unplanned downtime.

01

WHAT WE SOLVE

  • Unexpected and costly failures

  • Interventions performed too late or too early

  • Inefficient maintenance planning

  • Limited use of machine data

02

CUSTOMER BENEFITS

  • Fewer downtimes, greater productivity

  • More efficient and less expensive maintenance

  • Increased plant reliability

  • Better technical and economic planning

03

WHAT WE DO

  • Operational Data Collection
    Acquisition of temperatures, vibrations, event logs, and consumption data from PLCs/sensors.

  • Data Cleaning, Storage, and Enrichment
    We consolidate and prepare data for predictive analysis.

  • Predictive Model Development and Training
    We use ML/AI algorithms to estimate remaining useful life and detect anomalies.

  • Predictive Alerts and Smart Scheduling
    We generate early alerts integrated with CMMS/ERP systems for automated maintenance.

04

TECHNOLOGIES AND APPROACH

EXPECTED OUTPUT FOR THE CUSTOMER

TECHNOLOGIES AND APPROACH

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Machine Data Collection via Industrial Protocols (OPC UA, MQTT, Modbus, REST)

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Data Engineering on Historical and Real-Time Streams (Azure Data Explorer, Fabric, Data Factory)

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AI/ML Models Developed on Platforms such as Azure Machine Learning or scikit-learn in cloud/on-premises environments

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Predictive Dashboards for Maintenance Technicians and Managers, displaying current status and future projections

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Integration with CMMS (Computerized Maintenance Management System) and ERP Software to orchestrate activities

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EXPECTED OUTPUT FOR THE CUSTOMER

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Reduction of Unplanned Downtime, with a positive impact on productivity and quality

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Optimization of Maintenance Costs by avoiding unnecessary interventions

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Proactive and Intelligent Scheduling of maintenance activities

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Extension of the Useful Life of machinery and critical components

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Improved Operational Reliability, measurable through KPIs such as MTBF, MTTR, failure rate, etc.

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