WeSenseAll Subscription

WeSenseAll Subscription is powered by WSA Solutions sp. z o.o.

WeSenseAll supports customers in their digital transformation by enabling data-driven decision-making for industrial assets. Our solution digitizes machine behavior using industrial sensors, secure data acquisition,cloud-based analytics.By applying statistical analysis and machine learning, we transform raw operational data into actionable insights that improve reliability, maintenance planning, safety,and overall operational efficiency,without disrupting existing production systems.

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Why Predict failures and optimize operations using data?

WeSenseAll is a software platform for industrial companies that need better visibility into machine condition and performance. It serves maintenance and operations teams by analyzing data sent via MQTT from various sources. The system detects anomalies, predicts failures, and helps eliminate unplanned downtime, reduce maintenance costs, and improve overall equipment efficiency.

Benefits

Reduction of unplanned downtime through early detection of anomalies and failure prediction. The system continuously analyzes incoming data and identifies deviations from normal operation, enabling maintenance teams to act before breakdowns occur and avoid costly production interruptions.
Optimization of maintenance activities by shifting from time-based to condition-based decisions. WeSenseAll uses real-time data and predictive models to indicate when intervention is actually needed, reducing unnecessary inspections, lowering maintenance costs, and improving resource allocation.
Improved operational efficiency and equipment performance through data-driven insights. The system identifies trends, inefficiencies, and hidden losses in machine operation, supporting better decision-making, increasing OEE, and enabling continuous process optimization.

Featured Capabilities

Analyze real-time machine data

Process and analyze data streams from sensors, PLCs, and other systems via MQTT. Detect deviations from normal operation in real time, enabling immediate visibility into machine condition and faster response to emerging issues.

Predict failures before they occur

Use machine learning and statistical models to identify patterns and trends in data. Predict potential failures in advance, allowing maintenance teams to plan interventions, avoid downtime, and reduce emergency repairs.

Monitor asset health and trends

Visualize machine condition, trends, alerts, and anomalies in clear dashboards. Track asset health over time, compare operating states, and support data-driven decisions for maintenance, reliability, and production planning.

Case Study

Robot Failure Reduction with Predictive Monitoring

At Toyota Manufacturing, WeSenseAll was implemented to monitor industrial robots assembling components.
As a result, the plant achieved at least a 15% reduction in failure frequency and costs.

Real World Applications

Predictive maintenance for production lines

Detects early signs of machine wear using data from sensors and PLCs via MQTT. Identifies anomalies in vibration or temperature, predicts failures, and enables maintenance teams to act before breakdowns, reducing downtime and improving production continuity in automotive lines.