The way maintenance is carried out is altering rapidly. The introduction of Cyber Physical Systems (CPS) and cloud technologies are providing new technological possibilities that change dramatically the way it is possible to follow production machinery and the necessity to carry out maintenance. In the near future, the number of machines that can be followed from remoteness will explode. At the same time, it will be conceivable to carry out local diagnosis and prognosis that support the adaptation of Condition Based Maintenance (CBM) i.e. financial optimisation can drive the decision whether a machine needs maintenance or not. Further to this, the cloud technology allows to accumulate relevant data from numerous sources that can be used for further improvement of the maintenance practices. The paper goes through the new technologies that have been mentioned above and how they can be benefitted from in practise.

This article discusses how a business model based on traditional maintenance can evolve to generate servitization strategies, with the help of remote maintenance support. The application of cyber-physical systems and cloud technologies play a key role for such maintenance purposes. In fact, the utilization of large quantities of data collected on machines and their processing by means of advanced techniques such as machine learning enable novel techniques for condition-based maintenance. New sensor solutions that could be used in maintenance and interaction with cyber-physical systems are also presented. Here, data models are an important part of these techniques because of the huge amounts of data that are produced and should be processed. These data models have been used in a real case, supported by the Machinery Information Management Open System Alliance Open System Architecture for Condition-Based Maintenance standard architecture, for streamlining the modeling of collected data. In this context, an industrial use case is described, to enlighten the application of the presented concepts in a working pilot. Finally, current and future directions for application of cyber-physical systems and cloud technologies to maintenance are discussed.

The Condition-Based Maintenance (CBM) strategy has got new, powerful toolset recently: the concepts of Internet of Things (IoT) and CyberPhysical Systems (CPS). These can provide flexible but powerful data collection and analysis methods for Proactive and Predictive Maintenance. In the landscape of new digitalization and interconnection of products, services, processes, enterprises and people, IoT/CPS-based platforms are increasing in their size and target applications in a steady manner. Beside the fundamental research challenges regarding the reference architecture, interoperability, performance, quality and deployment issues, the challenges regarding system maintenance are also burning. There are various issues that are specific to the maintenance domain: interoperability and data flow management, data representation models, and data processing models and tools. The paper describes a maintenance reference architecture and platform, which aims to tackle all these challenges. The architecture suggested by the MANTIS project covers edge and cloud level interoperability, data flow management, and data processing issues. Furthermore, it provides domain-specific methods for root cause analysis, failure prediction, and models for predicting remaining useful life. The architecture is strengthened by the concept of MIMOSA, a data model definition that allows data representation models that are easy to fit into relational object and information management models required by CBM. The MANTIS platform utilizes the Arrowhead framework for tackling interoperability and integrability issues.

In chapter 2 local clouds was discussed followed by a local cloud automation architecture in chapter 3. The automation architecture supports the implementation of local automation clouds. Such implementation is supported by the Arrowhead Framework and its core Systems and Services. The Arrowhead Framework core systems enables the creation and operation of local clouds. First implementation of these systems and their services are described in detail in this chapter. There currently are two types of core services within the Arrowhead Framework: - Mandatory core systems - needed to establish the minimal local cloud - Automation support core systems – extending local cloud capabilities intending to provide support for the design and operation of local automation clouds an interaction between local clouds.