Internet of Things Integration Platform
Remote Monitoring, M2M and Device Management Software Platform
AggreGate Platform

Predictive Maintenance

AggreGate as a preventive maintenance system enables OEM equipment vendors and service providers to build predictive maintenance (PM) solutions in rapid and cost effective manner. Allowing to switch from schedule-based or lifecycle-based to "health-based" service, PM delivers one of the most important business optimization opportunities that was made available by the Industrial IoT technology.

Predictive maintenance technologies bring univocal business value materialized by higher equipment uptime, lower OPEX due to reduced repair costs, and more strict Service Level Agreements (SLAs).

AggreGate ecosystem is adopted for ensuring quick time-to-market for PM (preventive maintenance) initiatives. Here's how a typical project lifecycle looks like:

  • Your equipment is fitted with various sensors to enable telemetry acquisition. In most cases sensors are already there.
  • The "brain" of your unit (normally a PLC or an industrial PC) is extended by a small piece of software that is called AggreGate Agent. The agent takes care of bridging all collected data from the unit to central server installed in public or private cloud.
  • If modifying an existing unit firmware/software is not possible, an external Agent (a small PLC, e.g. based on Tibbo Project System) can be added to the unit design. This external Agent may connect to the sensors directly or retrieve data from the main control computer.
  • The data gets reliably routed to the server and stored in a high-performance NoSQL database. In rapid deployment scenarios it's also possible to import historic data collected ealier.
  • Once a sufficient amount of data is available, it's necessary to teach the system which unit behaviour patterns should be deemed negative.
  • Further operation continutes in headless mode, AggreGate applies intelligent machine leaning and Big Data mining algorithms for predicting unit health degradation.

In many cases, predictive maintenance is even not an option, since telemetry data received from a unit is a principal argument in solving disputes between equipment vendor and operator. Agent embedded into a unit can work autonomously, allowing vendor to ensure that temperature, humidity, inclination, acceleration and other parameters were compliant during unit transportation and storage.

Being deployed properly, preventive maintenance software is predicting two valuable device health indicators: Time to Failure (TTF) and Remaining Useful Life (RUL). Those metrics are easily converted into operating cycles, mileage, transaction counts, and other unit-specific metrics. RUL estimation is a sophisticated matter, but it's proven to work rather good for rotating machinery, such as fans, pumps, and engines.

Predictive maintenance system is typically integrated with a Computerized Maintenance Management System (CMMS), automatically generating maintenance requests upon equipment health degradation. Another advanced function is service logistics.

Acting as a predictive maintenance software, AggreGate has deep knowledge about equipment behaviour. This knowledge may be used for intelligent tuning and optimization of device control logic and life cycle.

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