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Proven Methodology to implement Predictive Maintenance Solutions in Healthcare industry that drive results


Case study : Implementing Predictive Technical Diagnoses 2017.

Development of a predictive maintenance solution for laboratory systems from Siemens Healthineers, using SAS.

Predictive maintenance in Healthcare // SAS Data Management Platform // SAS Enterprise Guide // SAS Visual Analytics

Goals of our client Siemens Healthineers

Conceptual design and implementation of a predictive maintenance framework for an innovative laboratory diagnosis system to

  • Minimize system downtimes
  • Optimize maintenance and service
  • Enable long term application possibility

Our approach for Predictive Maintenance in Healthcare

  • Identifying and making provisions for the necessary sensor technology during the development process
  • Design of a predictive maintenance framework on the basis of SAS Data Management Platform
  • Extensive automation of the process from the transmission of the sensor data to warnings
  • Visualization of the key performance indicators


  • 58 system and process components monitored proactively
  • Downtimes have significantly lowered compared to the reactive services
  • Optimized deployment of service technicians, as they know in advance the parts are needed at a particular location

Initial Situation

In the future, reporting malfunctions to customer service should be the exception rather than the “rule” for users of the laboratory diagnostics system Atellica® Solution from Siemens Healthineers. To fulfil the mentioned objective, the client partnered with us and our experts in data analytics and data science.

The company developed a predictive service and maintenance solution. This allows for:

  • Increases in the laboratory system’s availability
  • Reduces service costs

The solution is based on the data analytics platform from SAS, one of the world’s biggest software providers of analytical software. (external link)

Clinical laboratory diagnostics with a vision to transform to Pharma 4.0

Siemens Healthineers is among the world’s leading companies in healthcare. It focuses on imaging for diagnosis and therapy, as well as clinical laboratory diagnostics Atellica Solution sets groundbreaking standards in immunoassay and clinical chemistry analysis via innovations designed to optimize workflow and clinical performance.

Atellica Solution for Predictive Maintenance pharma
Atellica Solution

The system features patented bidirectional magnetic sample-transport technology and supports a multi-camera vision system to independently control every sample.

At the same time, the software offers intelligent scheduling for the individual management of samples throughout the testing process. Atellica Solution immunoassay system can perform up to 440* tests per hour, the highest productivity per square meter in the industry**.

For customers, it’s crucial that throughput is uninterrupted. Therefore, the engineers from Siemens Healthineers in product development wished to incorporate the integration of a predictive service and maintenance solution as early as the development phase, they defined which data could be relevant for predictive maintenance.

This brought a key benefit, that the necessary sensors were integrated and provisions were made for the principle connection to the Siemens Healthineers database. Thereafter, enabling the subsequent processing of the data.s

Proactive service on the SAS Platform

Once the first development phase for the product series was complete, the next step was the dedicated development of the predictive service and maintenance solution. Here, Siemens Healthineers decided to use the SAS Data Analytics Platform, comprising the SAS Data Integration Server and the SAS Data Integration Studio.

Furthermore, in its predictive service and maintenance project, Siemens Healthineers opted to deploy SAS Visual Analytics for data preparation while SAS Enterprise Guide was selected for data analysis.

Otofacto’s role for the project implementation for Predictive Maintenance in Healthcare industry

For the conceptual design and implementation, Siemens Healthineers chose the SAS partnered with us, with whom they had already worked successfully on earlier projects.

The Otofacto team was tasked with the complete process: from implementing the data loading points, through setting up the predictive service and maintenance framework, to preparing the data for the creation of reports.

To work as time-efficiently and cost-effectively as possible, the team took an iterative approach, where the basic requirements were first determined, and then modified during the project as needed.

Efficient analysis – remotely

The predictive service and maintenance solution offered to the users of Atellica® Solution within the framework of the Guardian Program™ is almost fully automated.

As far as circumstances in the individual countries permit, the data is first transmitted to the respective country databases via the Siemens Healthineers Smart Remote Service (SRS). It comes from various sources, for example, pre-structured sensor data or log files.

The data is then transferred to the SAS system by means of SRS. Based on analytic models developed by Siemens Healthineers in a team of data scientists and system experts, the data is then analyzed and failure probabilities are determined.

The results are processed, visualized, and made available via a web-based front end!

Data insights: Predictive Maintenance pharma

Additional feature that aids in driving results

To simplify and automate the process still further, Otofacto had also developed an e-mail notification service. The employees responsible recieved an automatic warnings with detailed information.

This happened as soon as new information about an Atellica Solution component is received, that requires an action.

In addition, the incoming information is used to assess the entire solution. This is processed with SAS Visual Analytics.

  • 58 system and process components are being monitored proactively
  • System downtimes are significantly lower compared to the reactive service: Interim analyses of the first system installations show that, generally, the proactive service produces 36% less system downtime compared to the reactive service.
  • Optimized deployment of service technicians, because they know in advance which parts are needed at a particular location.

Successful realization of Predictive Maintenance in Healthcare industry

The starting point for this was the development of the equipment with the aim of implementing predictive service and maintenance solutions. The software from SAS is an ideal platform. Due to the fact that it can be used for all analyses and can be easily scaled, if required.

And, finally, Otofacto’s structured realization of the framework ensures tremendous flexibility.

The solution evolves through the continuous expansion of the analytical data models and the data basis.

The modular structure and intuitive framework ensures that the Siemens Healthineers team can make modifications on their own.

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