29 Using Sensor Data for Predictive Maintenance of a Complex Transportation Asset
In this chapter one of the three industrial use cases will be presented of those which are going to be developed to evaluate the results achieved by the European project UPTIME (Unified Predictive Maintenance System). The main objective of the project is the development of an innovative maintenance platform, based on the latest technologies – such as IoT or big data analytics. The paper focuses on the application of future UPTIME results in the aviation sector.
29.1. Introduction
The UPTIME project develops an integrated predictive maintenance system for the manufacturing industry. The motivation comes from the increasing demand for product quality and reliability of production. Predictive maintenance can have a considerable influence, for example on the availability of production equipment, by carrying out maintenance and repair measures not statically but on the basis of permanently measured condition data.
The UPTIME maintenance system will be able to process heterogeneous data from different sources (e.g. sensors, machine and production control data, field reports). Based on this, smart analytics and tailored visualizations will allow the identification of impending machine failures and suggest countermeasures. UPTIME will thus expand and standardize new digital maintenance services and tools to unlock the full potential of predictive maintenance management by sensorgenerated big data processing, ...
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