• Comment:

      The UPTIME platform is built upon the predictive maintenance concept, the technological pillars (i.e. Industry 4.0, IoT and Big Data, Proactive Computing) and the existing baseline tools (i.e. USG, preInO, PANDDA, SeaBAR, DRIFT) resulting in a unified information system for predictive maintenance. The extended UPTIME baseline tools (SENSE, DETECT, PREDICT, DECIDE, ANALYZE, FMECA, VISUALIZE) will address the various steps of the unified predictive maintenance approach and will incorporate interconnections with other industrial operations related to production planning, quality management and logistics management.

    • Comment:

      The UPTIME conceptual architecture was designed according to the ISO/IEC/IEEE 42010 “System and software engineering – Architecture description” and mapped to RAMI 4.0 in order to ensure that it can be represent predictive maintenance in the frame of Industry 4.0.

      The UPTIME vision converges and synthesizes predictive maintenance, proactive computing, the Gartner’s levels of industrial analytics maturity and the ISO 13374 as implemented in MIMOSA OSA-CBM in order to create a consistent basis for a generic predictive maintenance architecture in an IoT-based industrial environment. In this way, the Operational Technology and the Information Technology can also be converged in the context of Industry 4.0.

    • Comment:

      One of the main functionalities of UPTIME Platform is the batch data analytics implemented by UPTIME_ANALYZE component to analyse maintenance-related data from legacy and operational data and UPTIME_FMECA component that provides estimation of possible failure modes. The interoperability interfaces with UPTIME End-Users' (e.g. Whirlpool) legacy systems are defined, specified and developed according to latest practices and standards for APIs.