UPTIME will seek to reframe predictive maintenance strategy by proposing a unified framework and to create an associated unified information system in alignment to the aforementioned framework. Therefore, UPTIME will extend and unify new digital, e-maintenance services and tools in order to exploit the full potential of a predictive maintenance strategy with the UPTIME solution, will deploy and validate the UPTIME solution in the manufacturing companies participating in the UPTIME consortium and will diffuse the UPTIME solution in the manufacturing community.
UPTIME will enable manufacturing companies having installed sensors to fully exploit the availability of huge amounts of data with respect to the implementation of a predictive maintenance strategy. Moreover, production, quality and logistics operations driven by predictive maintenance will benefit from UPTIME.
UPTIME will enable manufacturing companies to reach Gartner's level 4 of data analytics maturity (optimized decision-making) in order to improve physically-based models and to synchronise maintenance with quality management, production planning and logistics options. In this way, it will optimize in-service efficiency through reduced failure rates and downtime due to repair, unplanned plant/production system outages and extension of component life.
Moreover, it will contribute to increased accident mitigation capability since it will be able to avoid crucial breakdown with significant consequences. Consequently, UPTIME will exploit the full potential of predictive maintenance management and its interactions with other industrial operations by investigating a unified methodology and by implementing a unified information system addressing the predictive maintenance strategy.
- ISO TC 184 SC4 and SC5 on industrial data, ISO/IEC JTC1 on Information Technology, ISO TC 184 IEC TC 65 JWG 21 on Smart Manufacturing Reference Model - in link with RAMI 4.0
- IOF, Industry Ontologies Foundry, ontologies for Industry particularly the working group on maintenance ontologies
- In contact with MIMOSA e.g. for ISO 18101 for Oil and Gas Interoperability
| Web resources: |
https://www.uptime-h2020.eu/
https://cordis.europa.eu/project/id/768634 https://www.linkedin.com/in/uptime-h2020/ https://twitter.com/uptimeH2020 https://www.youtube.com/channel/UCqHA62sd4zxc8-knPDREcAw |
| Start date: | 01-09-2017 |
| End date: | 28-02-2021 |
| Total budget - Public funding: | 6 248 367,00 Euro - 4 847 836,00 Euro |
| Twitter: | @uptimeH2020 |
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Original description
UPTIME will seek to reframe predictive maintenance strategy by proposing a unified framework and to create an associated unified information system in alignment to the aforementioned framework. Therefore, UPTIME will extend and unify new digital, e-maintenance services and tools in order to exploit the full potential of a predictive maintenance strategy with the UPTIME solution, will deploy and validate the UPTIME solution in the manufacturing companies participating in the UPTIME consortium and will diffuse the UPTIME solution in the manufacturing community.UPTIME will enable manufacturing companies having installed sensors to fully exploit the availability of huge amounts of data with respect to the implementation of a predictive maintenance strategy. Moreover, production, quality and logistics operations driven by predictive maintenance will benefit from UPTIME. UPTIME will enable manufacturing companies to reach Gartner’s level 4 of data analytics maturity (“optimized decision-making”) in order to improve physically-based models and to synchronise maintenance with quality management, production planning and logistics options. In this way, it will optimize in-service efficiency through reduced failure rates and downtime due to repair, unplanned plant/production system outages and extension of component life. Moreover, it will contribute to increased accident mitigation capability since it will be able to avoid crucial breakdown with significant consequences.
Consequently, UPTIME will exploit the full potential of predictive maintenance management and its interactions with other industrial operations by investigating a unified methodology and by implementing a unified information system addressing the predictive maintenance strategy.
Status
CLOSEDCall topic
FOF-09-2017Update Date
27-10-2022- ISO TC 184 SC4 and SC5 on industrial data, ISO/IEC JTC1 on Information Technology, ISO TC 184 IEC TC 65 JWG 21 on Smart Manufacturing Reference Model - in link with RAMI 4.0
- IOF, Industry Ontologies Foundry, ontologies for Industry particularly the working group on maintenance ontologies
- In contact with MIMOSA e.g. for ISO 18101 for Oil and Gas Interoperability
The standardisation goal in UPTIME is to simplify the integration of the components in the the UPTIME Platform and to make easier the integration of the UPTIME Platform in new industrial environments.
Below list of some relevant standards to UPTIME:
- IEC 62541 (OPC-UA) and ISO/IEC 20922 (MQTT) for Modular Edge Data Collection & Diagnosis - also JSON, XML, MSGPACK, I2C, SPI
- IEEE 802.15.4 for low rate personal area networks
- ISO 13374, MIMOSA OSA-CBM and OSA - EAI for Mapping, Extraction and Analysis of Legacy DB, Configurable Diagnosis, Configurable Prognosis, Prescriptive Analytics for Proactive Decision Making
- IEC 60812 FMEA and FMECA for Maintenance Actions Parametrization and Management interface
- EN 13306 for common maintenance terminology
- ISO 17359 for condition monitoring and diagnostics on machine
- ISO 13373 for vibration monitoring, ISO 18435, ISO 10303, ISO 15926 for interoperability
- ISO 14224 for maintenance data in oil and gas
09/04/21 - 08:41
UPTIME Newsletter - March 2021 edition
Welcome to the 8th edition of the UPTIME Newsletter.
The UPTIME project has officially ended in February 2021. After 3,5 years of research and development, the UPTIME Platform is ready now for the market. The UPTIME consortium has defined a concrete go-to-market strategy to optimize the impact of the UPTIME Platform on the market and maximize its chances of success. The consortium feels this is the right time to launch a new solution for predictive maintenance with all of the advanced features the UPTIME Platform and its substituent components offer.
UPTIME proposes a differentiating value proposition, and its business model offers enough flexibility to reach a wide range of companies of different size and type. The market-oriented website – www.uptime-predictive-maintenance.com – with clear key messages and its demo-space is a good tool to get new leads and will be further built upon and utilized going forward in the exploitation activities. An adoption methodology for UPTIME deployment has been also created according to the successful deployment in the three business cases and is introduced in this Newsletter.
The consortium plans to drive forward the convergence of the UPTIME Platform with Industry 4.0 standards and beyond that, to address the issues that are beginning to be championed under the banner of Industry 5.0.
A strong foundation has been laid for the convergence with Industry 4.0 in the full compliance of the UPTIME Platform with the RAMI 4.0 reference architecture and addressing Asset Administration Shell (AAS) interoperability. The next step is to realise the AAS interface more fully and establish the UPTIME Platform as a Digital Twin for asset maintenance.
Events such as the 2nd UPTIME showcase event will be repeated since they proved extremely helpful in overcoming constraints imposed by the COVID-19 pandemic, however a live and in-person event will be organized as soon as possible in the post-project commercial phase. As a first step, UPTIME will be hosted by BIBA at Digital Hannover Messe event, which will take place from 12 – 16 April 2021. We’d like to take this opportunity to invite you to join us virtually at this event. You can register your participation free of charge using the ticket code “CVJVm” through this link.
On a wider scale, the cooperation begun in the framework of the ForeSee cluster will also be maintained by the UPTIME partners, to contribute in the implementation of its structured Predictive Maintenance roadmap and to have a greater impact on standards and production of commons for European industry, which will shape the access to the new market of maintenance, which is key for the industry of the future.
A full newsletter is available: https://www.uptime-h2020.eu/index.php/2021/03/31/uptime-8th-newsletter-edition-03-2021/
09/12/20 - 12:59
UPTIME Newsletter - November 2020 edition
Welcome to the 7th edition of the UPTIME Newsletter.
The UPTIME project has entered the final phase. The prototype of the UPTIME Platform has been deployed into the three industrial business cases in its final configuration.
The UPTIME Platform gives you a competitive advantage by empowering everyone involved in your maintenance activities. Operational staff and managers benefit from real-time visualization of asset conditions, correlation analyses and accurate predictions. Maintenance managers benefit from actionable plans based on accurate predictions, increasing efficiency and reducing costs. All stakeholders gain valuable insights into the data thanks to intuitive, customizable visualization. In this edition, we gladly present you 10 main added-values of UPTIME Platform perceived by our industrial end-users.
In addition to the six main components of the UPTIME Platform introduced in the previous newsletters, in this issue, we are proud to announce the UPTIME Workers’ Mobile Application, which helps workers on the shop floor stay up-to-date in real-time about their maintenance tasks.
A full newsletter is available: https://www.uptime-h2020.eu/index.php/2020/11/20/uptime-7th-newsletter-edition-11-2020/
09/12/20 - 12:50
UPTIME 3rd Live Webinar: Predictive Maintenance: Lessons Learned and Best Practices in Aviation Industry - 10 Dec 2020
Date: Thu, 10 December 2020
Time: 11:00 - 12:30 CET
The UPTIME 3rd Webinar will address benefits of predictive maintenance in a highly complex transportation asset operations deployed in the aviation industry. UPTIME Partner from FFT Produktionssyteme GmbH & Co. KG will share his experiences, challenges and some lessons learnt from the implementation of the UPTIME Platform in the FFT use case.
The use case focusses on one specific production logistics asset used in the aviation industry, so-called “jig” for the transport of wing covers of commercial aircraft. The reliability of production logistics assets is a critical cost factor in the production of high-value products such as aircraft and needs to be considered along with the reliability of other production equipment to ensure a timely, cost-effective and high-quality production processes. Due to the critical nature of the deployment of these assets, the requirements are both technically and organisationally very high. The need has arisen to increase efficiency in maintenance execution as well as in reporting to the client, who in most of our projects is responsible for the logistics coordination of their assets.
The web seminar is free of charge, dedicated to people who want to learn and see a concrete implementation of the UPTIME Predictive Maintenance Platform in a real business case. It is interactive, where you have the opportunity to ask questions to the experts panel and we are happy to receive your feedback.
If you have any questions or comments, please contact us.
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| BIBA - BREMER INSTITUT FUER PRODUKTION UND LOGISTIK GMBH (Coördinator)
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| FFT PRODUKTIONSSYSTEME GMBH & CO. KG
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| INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS
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| ISADEUS
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| Institute of Communication and Computer Systems (ICCS)
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| M.J.MAILLIS S.A. INDUSTRIAL PACKAGING SYSTEMS AND TECHNOLOGIES
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| Pumacy Technologies AG
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| RINA CONSULTING SPA
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| SUITE5 DATA INTELLIGENCE SOLUTIONS LIMITED
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| SUITE5 DATA INTELLIGENCE SOLUTIONS LIMITED
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| UBITECH LIMITED
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| Vinci Consulting
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| WHIRLPOOL EMEA SPA
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| Whirlpool Europe srl