The UPTIME solution will combine and extend existing predictive maintenance tools and services (USG/BIBA, preIno/BIBA, PANDDA /ICCS, SeaBAR/Pumacy, and DRIFT/RINA-C) and will define the way for its implementation in a systematic and unified way with the aim to fully exploit the advancements in ICT and maintenance management by examining the potential of big data in an e-maintenance infrastructure.
Extended version of USG will implement the Signal Processing phase; extended version of preInO will address the Diagnosis and the Prognosis phases; extended version of PANDDA will deal with Maintenance Decision Making; extended version of SeaBAR will address the Maintenance and Operational Actions Implementation; and extended version of DRIFT will deal with data-driven FMECA.
Each extended UPTIME service will incorporate real-time data-driven information processing technologies and algorithms so that the integrated system is able to cover complete scenarios and fulfil the needs of the manufacturing companies participating in the consortium. The aforementioned tools will interact when necessary to the manufacturing company’s system (e.g. ERP, MES) in order to exchange data and information for scheduling production, quality and logistics activities together with maintenance activities (e.g. by using the production plan of the ERP system). Through the Continuous Improvement mechanism, UPTIME will be able to continuous learn with the aim to update and improve Diagnosis (Detect), Prognosis (Predict) and Maintenance Decision Making (Decide) phases by gathering actions-related and/ or failure-related sensor data (Act).