DRIVING MANUFACTURING PERFORMANCE FORWARD WITH INDUSTRY 4.0 PREDICTIVE MAINTENANCE

Equipment performance and predictable capacity are critical to manufacturing operations. At Blue Willow, we help manufacturers reduce downtime and increase productivity by improving asset performance with our turnkey comprehensive predictive maintenance solution.

　　Our combination of advanced machine monitoring technologies and AI -enabled (Artificial Intelligence) predictive analytics with maintenance leadership enables real-time visualization of streaming data, provides machine health forecasts which in turn reduces machine downtime and increases production efficiency and revenues. We have a successful and accomplished executive team bringing over expertise in manufacturing and industrial software systems which fuses the spirit of hi-technology innovation with rock-solid industrial experience.

Equipment Predictive Maintenance Solution Highlights:

　　• Provide 24/7 dashboard with industry leading AI analytics
　　• Monitor component installed sensors and targeted PLC data
　　• Connect multiple brands of equipment and sensors
　　• Prevent unplanned machine failures and conduct maintenance in planned time windows
　　• Increase capacity and reduce capital expense

　　Failure or loss of equipment and parts is a common type of industrial loss.In unpredictable situations, such losses often cause production line shutdowns and affect productivity. What's more, it can cause serious breakdown and bring great loss to industrial production. Although current preventive maintenance can eliminate faults in advance to a certain extent, it is also prone to over-maintenance (excessive maintenance frequency) or lack of maintenance.

　　Our predictive maintenance solution combines IIoT, industrial AI, big data and predictive analytics to reduce the uncertainty of equipment maintenance by providing actionable information and accurate predictions, and more reasonable planning of production and maintenance plans.
　　• Data Acquisition:　　　 　　 Obtain available data through low-energy wireless sensor networks, and also provide wireless
　　　　　　　　　　　　　　　   gateways to acquire existing device data.
　　• Data Preprocssing:　　 　　 Filter and sort data, and identify data working condition information.
　　• Feature Extraction:　　 　　 Describe the overall manufacturing change process and extract data feature values.
　　• Model Training:　　　　 　　Use historical data of equipment to train a AI-based health model to evaluate equipment health status.
　　• Equipment Failure Warning:   Predict and forecast the health status of the equipment based on the AI-enabled health Model;
　　　　　　　　　　　　　　　　Informs equipment operation and maintenance personnel in time and prevent machine downtime ahead of time.
　　• Visualization:　　　　　 　　The identification of equipment health patterns can be monitored in real time through live graphs.

　　Our IIOT sensor-based predictive analytics with AI and big data technologies set us apart as a holistic, technology-driven partner. Add to this our many years of maintenance experience with best-in-class processes and people, you can count on us to deliver actionable insights that will ensure greater performance of your critical assets.