Objectives
Scientific Objectives
Efficient PdM algorithm design and implementation
Design and implement a set of intelligent algorithms that extract signature patterns from monitoring data and aim to (i) reduce the frequency of unnecessary maintenance tasks and (ii) proactively recommend to proceed to maintenance in case of non-expected failures according to the periodic maintenance guidelines; thus, minimizing the unnecessary and unexpected disruption to their business, respectively. The failures will be mapped to the broader diagnostic trouble code (DTC) taxonomy and the input data will include monitoring vehicle data (parameter IDs - PIDs) collected on the fly. Special attention will be placed to avoid known pitfalls in PdM and being able to yield incrementally and continuously enhancing solutions without excessive needs in training datasets.
Interoperability layer implementation
Upgrade of the existing NAVARCHOS 2 data collection gateway to receive data from multiple vehicle tracking modules from different manufacturers and stored them in a common data model. Currently, NAVARCHOS 2 gateway receives data from only one manufacturer. The scope is to extend the existing NAVARCHOS’s Gateway to support multiple protocols from different manufacturers and stored them in a common data model for supporting interoperability.
Technological Objectives
Cloud-based scalable PdM algorithm implementation
The algorithms designed and implemented will be deployed in cloud-based scalable and fault-tolerant infrastructure to enable big data support. Big data aspects of interest to be covered include both volume, variety, and velocity of data to be ingested by the NAVARCHOS’s Gateway.
Integrated application - prototype
Develop an end-to-end (vehicle to infrastructure) solution building on top of NAVARCHOS2 to prove and evaluate the usability, effectiveness, and value of the proposed integrated framework and developed mechanisms in an industrial, real-life FMS use case. The Integrated application prototype will be fall within (TRL) 6-7.