Ensuring High Performance and Reliability for Critical Medical Equipment with IoT Analytics

Readers of our Vitria blog know we are enthusiastic about our Analytics Value Chain concept as a methodology for generating value in IoT Analytics.

The Value Chain concept in Vitria’s IoT Analytics Platform can be applied to a wide array of use cases in many industries.  Predictive maintenance on complex manufactured equipment of various types is a significant use case that we see often.   Among those use cases, manufacturers of medical equipment have a particular challenge because of the obvious life critical nature of their equipment.

Because of that, maintaining highly efficient operations for the equipment and avoiding surprises in equipment performance is absolutely critical.

The rapid developments in sensors for these machines and improved IoT connectivity have set the stage for a new level of analytics to help achieve these business goals.

Vitria’s IoT Analytics Platform builds on the progress in IoT hardware and connectivity to deliver on the promise of IoT.  The business value of our platform for manufacturers of medical devices is best understood in the context of our Analytics Value Chain.


The building of value begins with ingestion of the critical diagnostic and performance data needed to understand operations and potential issues.

Fast Data Ingestion:  The first step in the value chain is to ingest all the critical data at speed and volume to ensure all the data needed to assess equipment health is available.

Context: The next step includes the integration of historical data such as the maintenance history of equipment – mean time between failures and other critical metrics.

Situational Intelligence:  The third step in the value chain process is the get the real-time status of the equipment – current error trends and detailed performance characteristics.

Predictive Analytics:  With all the critical data ingested and the context and real-time situational data available, the next major step in building value is to do predictive analytics.  This critical step is necessary to predict what might happen to a given piece of equipment given its current operational state and history.

Prescriptive Analytics:  Making predictions is not enough to fully address the challenges of maintaining medical equipment.  Prescriptive Analytics is needed to identify the next best action to pre-empt any of potentially serious issues identified with predictive analytics.  Often this is a set of instructions for fixing or maintaining a machine or device.

Intelligent Actions:  The final step of the value chain is to actually take the action of fixing or tuning a machine.  In some cases this might be an automated step, and in others it is dispatching a technician to execute the instructions identified with prescriptive analytics. Proactive action to prevent a problem is the key to generating value


Medical equipment companies can leverage the value chain concept within Vitria’s IoT Analytics Platform to dramatically improve their operations and service in a number of ways.  The business benefits include:

  • Eliminating or reducing machine downtime
  • Improving patient outcomes
  • Reducing technician visits
  • Better machine performance and longevity


Contact us to learn more

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