Case Study
Supervisory Control and Data Acquisition (SCADA) systems have long served as the critical backbone for monitoring and control of many waste water treatment plants. Internet of Things (IoT) systems and many new cloud platforms are augmenting and furthering the value of SCADA.
Predictive maintenance is one of the strongest new opportunities for cost savings, workload reductions, and overall improvement in operations. This opportunity now exists because IoT-based asset monitoring is easier to deploy, cheaper, and can be performed by non-experts. Traditional SCADA predictive maintenance or online vibration
monitoring has only been cost effective for critical assets because they are expensive and require specialized expertise to use them. Route-based monitoring requires skilled technician, and many faults are missed because data is taken infrequently (typically monthly or quarterly).
Now, IoT sensors are extending the value that has been achieved with online SCADA vibration monitoring to a much wider base of assets which is greatly expanding the ability to schedule maintenance at the right time to avoid unexpected equipment failures.
IoT devices like KCF’s Machine Health Platform can be plugged directly into existing SCADA system by connecting to a data historian like OSIsoft PI or Wonderware. Standard connectors like OPC DA can be used to share machine health data to the historian. The data can then be integrated into operator dashboards or screens. Native connections to range of different CMMS solutions enable seamless paring with existing maintenance management software.
KCF’s Platform is the most secure and mature IoT Machine Health solution on the market, with hundreds of integrated condition monitoring implementation and the most rigorous certification (ISO27001 and SOC II) used by the finance banking industry.
Learn more about gaining a competitive edge with the most advanced, comprehensive machine health optimization platform.