Powua IoT Orchestration Platform integrates data from your existing PLCs and sensors, as well as from ERP and historian data sources. Additional non-intrusive sensors may be introduced to broaden data collection. Data is securely extracted using the most common protocols, or your company’s preferred industrial data connectivity protocol.
Our Predictive Maintenance tool is an industrial operations software, designed to be used on the shop-floor by the maintenance and operations people who need to keep things running smoothly and ensure that unplanned downtime stays down.
Users get an intuitive digital twin HMI to visualize and analyze the performance of their production line processes and assets. By drilling through the digital twin – with smart factory dashboards and alerts at each level of the digital twin – you will quickly pinpoint performance anomalies and their root cause.
For more advanced data analytics, teams build custom dashboards with actionable insights powered by machine learning and model-based AI. Insights are generated with the analysis of millions of data points from machines alongside historical data on machine failure, repairs, operating conditions and maintenance requirements. This allows operations managers to predict failure, identify performance anomalies, and perform root-cause analysis.
Powua is the only solution that offers scalable predictive maintenance. It uses machine learning to perform condition monitoring and prognostics analysis, without requiring deep pockets or a team of expert data analysts. Driven by Industry 4.0 / the Industrial Internet of Things (IIoT), industrial operations are increasingly autonomous. Factories contain numerous sensors that provide real-time data on the status of production and machinery to optimise operations. Welcome to the fourth Industrial Revolution.
Collect valuable information in real-time about the “health” of the equipment to properly analyze and evaluate their current status
Instantly predict failure patterns and identify the cause of the problems to set a baseline from the data and predefined KPIs.
Build a maintenance schedule that performs proper inspections and routine checks to prevent failures.
Eliminate unscheduled downtime caused by equipment and system failure increasing production capacity of the plant and reduce maintenance expenditures.
Optimize energy consumption by intelligently managing machine operations according to energy utilization objectives.
Extend the effective life of the plant equipment.
Download our case study to find out how manufacturers are building successful predictive maintenance strategies with Powua.