Platform for rapid deployment of self-configuring and optimized predictive maintenance services

Informacje na temat projektu

PROPHESY

Identyfikator umowy o grant: 766994

DOI

10.3030/766994

Projekt został zamknięty

Data podpisania przez KE 11 Lipca 2017

Data rozpoczęcia 1 Października 2017

Data zakończenia 30 Września 2020

Finansowanie w ramach

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing

Koszt całkowity

€ 7 100 131,79

Wkład UE

€ 5 528 318,51

Koordynowany przez

NETCOMPANY SA
Belgium

Periodic Reporting for period 2 - PROPHESY (Platform for rapid deployment of self-configuring and optimized predictive maintenance services)

Okres sprawozdawczy: 2019-04-01 do 2020-09-30

Podsumowanie kontekstu i ogólnych celów projektu

Predictive maintenance (PdM) technologies continually monitor machines and equipment in order to identify symptoms of wear and other failures. In this way there is no need to keep excessive inventory through overproduction, as a means of alleviating the effects of break-downs, and the manufacturers can proactively undertake repairs and replacements, prior to experiencing more expensive problems. However, despite these proclaimed benefits of predictive maintenance, the majority of manufacturers have not fully implemented PdM in their FMECA (Failure Mode, Effect and Criticality Analysis) operations and, instead, apply less efficient approaches such as condition-based or preventive maintenance.
PROPHESY project targets is to provide, validate and develop a viable route to market for a novel PdM platform, which will enable end-to-end development, deployment and operationalization of adaptive self-configurable PdM services, based on the combination of leading-edge CPS components (i.e. CPS architectures, data analytics algorithms for PdM, augmented reality) and novel business models. PROPHESY enables the development of PdM services considering both the technical excellence and the business relevance of the solution, by optimizing technical characteristics and business parameters (e.g. Overall Equipment Effectiveness, product quality). PROPHESY also facilitates the deployment of new maintenance concepts, such as the expanded use of remote support and AR as part of predictive maintenance solutions.
The main elements of the PROPHESY solution are the following:
- PROPHESY-CPS: A CPS platform tailored to and optimized for predictive maintenance, with features associated with automatic data collection, data sources interoperability, data analytics and maintenance-driven production processes.
- PROPHESY-ML: Predictive Data Analytics Toolbox for Self-Configuring and Self-Adaptive PdM.
- Remote Visualization & PROPHESY-AR: Development and Integration of Visualization and Augmented Reality Services for Remotely Supported maintenance.
- PROPHESY-SOE: Methodologies and tools for the dynamic composition of PdM components into integrated PdM turn-key solutions.
PROPHESY focus on the development and delivery of the integrated PROPHESY system and its components, in a unified service platform, and the validation of the system in real-life conditions in the plants of the manufacturers of the consortium (Philips and JLR).

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

All the PROPHESY system components have been developed and integrated into a unified service platform which has been tested in two pilot demonstrators at Philips and JLR in specific Use Cases. In both the factories an end-to-end PDM solution has been validated, using real-life data, handled by the PROPHESY data bus, analysed by the PROPHESY ML component and visualized via the PROPHESY dashboarding solution.
At the CPS level a middleware infrastructure was developed that can support data streaming and analytics and includes the Asset Administration Shell (AAS) that provides a standardized way for the communication with external systems and and the Data Streaming component that can provide data streams between the various components inside the CPS.
PROPHESY-ML toolkit provides a very useful framework which enables the deployment, discoverability, configuration, and runtime management of a diverse set of analytics algorithms with the help of a user-friendly interface. This environment allows the quick and efficient application of algorithms to different use cases. The toolkit incorporates a set of different algorithms and interoperates smoothly with the rest of the platform. The toolkit is flexible and extensible, allowing data analytics designers to add their new algorithms with a fast and effective process.
The PROPHESY-AR components have developed into a multi-purpose tools for both remote support as well as providing specific work instructions and visualization of (predicted) tooling information to the maintenance mechanic, using Augmented Reality. PROPHESY-AR demonstrated its usability in the two demonstrators.
The project also developed a tool for comparing alternative PdM solutions comprising of PROPHESY developed modules, the PROPHESY-SOE (Service Optimization Engine). PROPHESY SOE presides on top of an integrated portfolio of complementary tools specialized in PdM, as being the final decision and governing endpoint. It incorporates a set of tools and calculators, uses input by the components and their properties, and delivers decisions not only for the two PROPHESY use cases, but also for any other general PdM deployment.
A portal has been established (www.pdm4industry.eu) for the longer-term viability of the project’s results and to promote their exploitation potential.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

The PROPHESY system and its underlying components will provide the means for manufacturers, machine vendors and PdM solution providers to innovate in predictive maintanence services and processes. Based on the algorithms of the PROPHESY-ML toolbox, manufacturers and machine vendors will be able to derive predictive insights and continually monitor the degradation patterns of the various assets, while at the same time anticipating failures. PROPHESY-CPS will provide support for closed loop manufacturing processes, which will be driven by predictions about the status and anticipated operating life of components. Using PROPHESY-SOE manufactures and machine vendors will be able to assemble solutions that schedule maintenance in a way that reduces failure rates. PROPHESY-AR will additionally shorten the time needed for actually performing the repair (e.g. based on faster remote support by the machine vendor if needed).
The two complex demonstrators of the project provided tangible and realistic showcases on the benefits of using PdM, including benefits associated with increased OEE, extended life of components, reduction of unplanned downtimes and more. Based on the produced predictions of manufacturing problems, PROPHESY will also mitigate the possibility of accidents that could be caused as a matter of unanticipated machine failures or poor maintenance.
The project results will positively impact a range of stakeholders outside the consortium, including manufacturers, providers, and integrators of PdM solutions, as well as the research and academic community. Information about the case studies and lessons learnt are also part of the PdM4Industry ecosystem portal (www.pdm4industry.eu) which is accessible to registered stakeholders outside the consortium. The project has also created a range of publicly accessible tools and calculators of PdM parameters, which can facilitate manufacturers in their techno-economic and business analysis about the viability of the adoption of predictive maintenance solutions.
Overall, PROPHESY’s new PdM tools will create new positions, new paradigms, and more added-value jobs throughout Europe, where PROPHESY technologies will be deployed.

The main elements of the PROPHESY solution.