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IBA: IoT in the medical industry

IBA is the worldwide leader in the field of proton therapy, considered to be the most advanced form of radiation therapy.  They teamed up with our colleagues from Xylos because of their experience with developing cloud solutions at scale. Xylos in turn brought us to the table for our expertise with the IoT. Together we were tasked to design a solution for their ambition to become more efficient.

The challenge

IBA is a global company pushing the limits of medical technology by developing innovative solutions for the diagnosis and treatment of cancer. IBA is the worldwide leader in the field of proton therapy, considered to be the most advanced form of radiation therapy. They develop, build and maintain proton therapy centers with costs reaching tens of millions of euros. 

Every downtime of a proton therapy system has significant impact on the patients. Because rescheduling a patient’s treatment results in the risk of cancer growth in the meantime. Fortunately, most downtime can be prevented with adequate monitoring and scheduled maintenance. Still, IBA has the ambition to go one step further and predict when their devices would malfunction so they can replace the worn parts outside the patient treatment hours.

IBA teamed up with our colleagues from Xylos because of their experience with developing cloud solutions at scale. Xylos in turn brought us to the table for our expertise with the IoT. Together we were tasked to design a solution for their ambition to become more efficient.

Proton-Therapy-System--IBA--Predictive-Maintenance

The approach

The ultimate goal is enabling predictive maintenance to keep the downtime on IBA's medical devices as low as possible. The foundation to this is securing a substantial learning data-set for a machine learning algorithm.

With projects like this it is vital that the solution is scalable and future-proof. We started with a roadmap, defining short term goals and future ones. We distinguished the primary focus: enabling remote monitoring and maintenance by connecting all devices.

This in turn can be used to realize the next goal: building a data set for the machine learning algorithm. After the AI has sufficiently trained itself by analyzing the captured values from real-world processes, the predictive maintenance model is ready to be implemented.

The solution

Together with IBA we chose Microsoft’s Azure cloud platform. Azure checks all the boxes for the project: it’s secure, able to handle and store the vast amount of data generated by the complex proton therapy systems and it offers several artificial intelligence solutions. 

Incomes the Internet of Things: by connecting all the proton therapy systems around the globe the total cost of service is reduced and the customer service is improved. IBA is now able to deploy new features for all systems at once. Moreover they can easily monitor the 10.000+ signals their systems output,  ensuring minimized downtime.  

By now most of IBA’s proton therapy systems are connected to the cloud. While the captured data is stored to create the learning dataset, we made sure the infrastructure offers flawless integration with the planned next steps: developing a predictive maintenance model to detect problems before they happen.

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