IIoT is important for several reasons:

• Data-driven insights: IIoT allows businesses to gather vast amounts of data from their industrial processes. This data can be analyzed to gain valuable insights into efficiency, performance, and potential areas for improvement.
• Predictive maintenance: By monitoring equipment in real-time, IIoT enables predictive maintenance. This means that potential issues can be identified before they cause major problems, reducing downtime and maintenance costs.
• Optimized operations: IIoT can help optimize operations by providing real-time data on processes and equipment performance. This data can be used to make informed decisions and adjustments to improve efficiency and productivity.
• Remote monitoring and control: IIoT enables remote monitoring and control of industrial processes and equipment. This allows for more flexible and efficient operations, as well as the ability to respond quickly to issues or changes in conditions.
• Safety and compliance: IIoT can contribute to improved safety by monitoring environmental conditions, detecting hazards, and ensuring compliance with regulatory requirements.

Now the time has come to optimize existing condition monitoring program with proper procedures, tools & techniques, smart vibration sensors (Mems based Wireless), big data integration, well established asset strategy models & diagnostics capabilities that prepare you to adopt the new technologies of AI/ML based IIOT solutions for advance level of automated machine health predictions with actionable insights.

AIVA Team with more than 50+ years of machine condition monitoring background help our customers to optimize the existing condition monitoring programs by thoroughly understanding their software systems configuration, proper data analysis structure & integrating asset condition data and process data & guiding with right direction for the implementation of AI/ML based IIOT Asset Predictive Analytics solutions as part of Fourth Industrial Revolution (Industry 4.0).

Our extensive support includes in building following KPI’s for IIOT platform.

Support to the software team includes in building AI/ML based Asset modelling, predictive asset monitoring, automatic diagnostics, and alerts as well as an advanced machinery analysis & web-based dashboards and reports.

Providing extensive support to the software team in building the machine learning algorithms of various vibration failure modes in different use cases as follows.