Scalable Predictive Maintenance through the Eclipse Arrowhead Framework

With the rise of Industry 4.0 and the 4:th industrial revolution withthe Internet of Things, infrastructures have become more prevalent to connect and monitor many different systems within an industrial set-ting. With many candidates for this IoT infrastructure, there is a need to evaluate the different candidates to determine the different strengthsand weaknesses of the infrastructure.This thesis investigates the use of the Eclipse Arrowhead framework in the application of scalable infrastructure used for predictive mainte-nance. This investigation is conducted by converting an existing pre-dictive maintenance implementation that is using Amazon Web Services as the IoT infrastructure into a predictive maintenance implementationusing the Eclipse Arrowhead framework as the infrastructure.This design science artifact which results from this thesis shows that the Eclipse Arrowhead framework is suitable for a scalable infrastruc-ture though some shortcomings of the framework were found during the implementation. And though it is a suitable infrastructure, the usage ofthe framework should depend on the specific needs of the infrastructureand should not be used as a “one size fits all” solution