Predictive Asset Maintenance Analytics for Injection Moulding Operations
Predictive asset maintenance analytics in injection moulding operations has certainly revolutionized over the decades. Many plastic manufacturing industries monitor and improve their injection moulding plants to perform at their best potential. But there are a few that rely on manual inspection of three main stages: mould design, mould development and injection moulding process. The debate of whether machine predictive maintenance is a valuable and reliable strategy to enhance the performance and functionality of the injection moulding machine still remains futile. However, to make a breakthrough to survive in this fast-pacing digital revolution, one should optimize and implement digital solutions. BLE technology devices are surely making their way into industries to provide better visibility across zones to understand the current equipment condition, predict future events in the injection moulding operations and based on the analytics to make responsive decisions.
Predictive Asset Maintenance Analytics Transforms Conventional to Smart Injection Molding Industry:
Integrating condition monitoring is a substantial necessity in injection moulding industries. The appointed officials and staff of mould design operations have to keep a keen eye on the process as if an error arises, it will be costly to redesign and modify. Other stages of injection moulding are equally essential. The production performance of each stage relies on each other, and hence, it is crucial to instate a real-time monitoring system that delivers impactful insights and corrective actions. This allows the appointed officials of every stage to track and monitor the production operations remotely, predict machine breakdowns and downtimes, improve asset traceability and availability, handle any unexpected hazards and better plan maintenance strategy, saving essential resources.
BLE adoption in condition monitoring strategy helps the plastic processing industry to enhance its manufacturing process. By predicting and analysing the root cause of the equipment, it is increasing the Remaining Useful Life of the machine. Niruha Systems’ BLE cod device enables machine health monitoring and empowers the manufacturers to produce products in high volumes, curb heavy maintenance costs and increase ROI. Due to the injection moulds varying from their complexity to size and material, manufacturers need to deploy BLE IoT-enabled products within their plants.
Let’s see some of the prominent advantages of predictive maintenance services conceptualizing smart injection moulding operations.
Advantages:
- cod enables machine condition monitoring and detects early machine failures to curb future damage
- Eliminates regular manual maintenance inspection
- Increases production, reduces material/ product wastage
- 24X7 Remote machine monitoring
- Several parameters are measured and monitored in a one-time frame
- Predicting machine failures minimizes the stoppage of the production line
- Provides cognitive analytics of abnormal vibrations in the equipment, increasing productivity and throughput
- nible BLE beacon Beacon-enabled sensors alert the appointed officials, executives, staff about any impending situations
- Allows you to shift from unplanned to planned maintenance strategy
- Captures critical data regarding temperature, pressure, shock, and humidity
Takeaways:
Predictive asset maintenance analytics is evolving the way injection molding industries work. It enhances the production system, delivering amplified outcomes and improving client satisfaction. Manage three core injection molding operations at ease with Niruha Systems’ BLE-enabled IoT products that stabilizes the production line and keeps them running efficiently for a longer period of time. Connect with us today.