What is UPTIME Platform?
The UPTIME Platform enables manufacturing companies to fully exploit real-time and historical data.It takes assisted decision-making to the next level by presenting maintenance scenarios with the optimal maintenance actions to implement at the optimal time. The operators are then able to mitigate risks, minimize maintenance costs and improve OEE.
UPTIME VISION
UPTIME provides next-generation predictive maintenance aiming to optimize in-service efficiency, to self-improve over time and adapt to dynamic manufacturing environments. It proposes a novel predictive maintenance management model along with an associated information system.
Unifying Operational Intelligence and Business Analytics for Next-generation Maintenance
UPTIME unifies operational intelligence and business analytics in the context of Industry 4.0 in order to provide visibility and insights into data and maintenance operations. This unification not only enables observing deviations in the manufacturing processes, but also predicting failures, deciding optimal maintenance plans and acting ahead of time, in a proactive way.
With UPTIME, manufacturing firms are able to harness different technologies, data sources (e.g. sensors, SCADA, PLC, asset management systems) and expert knowledge in order to drive maintenance operations through better decisions.
UPTIME ARCHITECTURE
The UPTIME Platform has been designed according to Systems Engineering principles to address both generic and specific user needs & technical requirements. The platform architecture accommodates different specific needs as demonstrated by its six main modules.
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UPTIME BENEFITS
- Reduced downtime
- Minimized costs
- Increased asset lifecycle
- Optimized maintenance plans
- Visualization of asset performance
- Reduced implementation costs
UPTIME Modules
UPTIME_SENSE
UPTIME_SENSE serves as modular data acquisition and manipulation components of the UPTIME Platform. The SENSE component captures data from a high variety of sources and cloud environments. It can connect to both analogue and digital data sources via numerous protocols, acquire data from these heterogeneous data sources, and integrate them towards a configurable data set. It is also capable of storing and intelligently handling and filtering the data acquired and can provide it to other subsequent UPTIME components in the form of sensor data streams for further analysis and processing. Moreover, it brings configurable diagnosis capabilities on the Edge, e.g. for real-time or off-the-grid applications.
UPTIME_DETECT & _PREDICT
UPTIME_DETECT aims to identify the topical state/condition of technical equipment by continuously observing sensor data streams. UPTIME_PREDICT includes abnormal behaviour of technical equipment and accordingly the classification of the condition state (simple example could be traffic light indication such as green, yellow red state). This is done by the possibility to orchestrate so‐called calculation flows based on diagnosis and prediction algorithms that are already built in the algorithmic framework of the tool or that are built on purpose by implementing a simple programming interface.
UPTIME_ANALYZE
UPTIME_ANALYZE is a data analytics engine driven by the need to leverage manufacturers’ legacy data and operational data related to maintenance, and to extract and correlate relevant knowledge. The ANALYZE component is designed to handle data‐at‐rest which signify data collected from various sources and physically stored across different manufacturers’ information systems.
UPTIME_FMECA
UPTIME FMECA, Failure Modes Effects and Criticality Analysis, aims to assess failure impacts of a system components. The FMECA component starts from the identification of the failure modes (i.e. how something can break down or fail) associated to each system’s component of an equipment and analyse the impact of such failures on the whole system according to its physical and logical design.
UPTIME_DECIDE
On the basis of (near) real-time predictions about future failures that lay outside the “normal states space”, DECIDE is enacted online in order to generate proactive action recommendations, i.e. recommendations about optimal (perfect or imperfect) maintenance actions and the optimal times of proactive action implementation. To do this, it estimates when the Expected Maintenance Loss will be minimized.
UPTIME_VISUALIZE
UPTIME_VISUALIZE provides configurable visualization to save time analysing data and getting insights, to support decision making and develop new solutions.