Periodic Reporting for period 2 - SERENA (VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce)
Okres sprawozdawczy: 2019-04-01 do 2021-03-31
The growing complexity of modern engineering systems and manufacturing processes is an obstacle to implementing Intelligent Manufacturing Systems (IMS) and keeping these systems operating at high levels of reliability. The number of sensors and the amount of data gathered on the factory floor increases constantly, while there are hidden resources, 85% of data and information are unstructured and 42% of all transactions (sending and receiving information) are still based on paper. This opens the vision of truly connected production processes where all machinery data are accessible allowing easier maintenance in case of unexpected events. Physical maintenance issues can cause costly disruptions in the manufacturing process. With predictive analytics, however, repairs and maintenance tasks can be prioritized and allocated to planned outages based on real-time probabilities of various future failures.
The strategy of predictive maintenance saves time and money and helps minimize costly production down times. Additionally, the use of remote predictive maintenance enables the minimization of the production dead time and the cost for spare parts and suppliers. Last but not least, predictive maintenance techniques such as vibration and thermal monitoring along with Reliability techniques such as Failure Modes and Effects Analysis (FMEA) and Root Cause Failure Analysis (RCFA) will result in bottom-line savings through early detection.
SERENA provides a lightweight, resilient, and scalable solution based on microservices for enabling predictive analytics at the edge level of a cloud system. SERENA is comprised of several logical components, which collectively provide its predictive maintenance functionality. These logical components reside on a cloud host, but the functionality extends to the edge gateways and sensors on the factory floor. Additionally, the platform is flexible enough to be hosted on either an on- premises environment, a cloud service provider environment, or a hybrid of the two. The SERENA system integrates a number of applications including:
- smart data generation from raw data
- predictive analytics
- maintenance planning and scheduling
- advanced visualization
- remote operator support
In conclusion, the SERENA system has been tested and validated in five (5) industrial use cases considering different deployments and configurations validating the resiliency of the SERENA approach and developments.
The strategy of predictive maintenance saves time and money and helps minimize costly production down times. Additionally, the use of remote predictive maintenance enables the minimization of the production dead time and the cost for spare parts and suppliers. Last but not least, predictive maintenance techniques such as vibration and thermal monitoring along with Reliability techniques such as Failure Modes and Effects Analysis (FMEA) and Root Cause Failure Analysis (RCFA) will result in bottom-line savings through early detection.
SERENA provides a lightweight, resilient, and scalable solution based on microservices for enabling predictive analytics at the edge level of a cloud system. SERENA is comprised of several logical components, which collectively provide its predictive maintenance functionality. These logical components reside on a cloud host, but the functionality extends to the edge gateways and sensors on the factory floor. Additionally, the platform is flexible enough to be hosted on either an on- premises environment, a cloud service provider environment, or a hybrid of the two. The SERENA system integrates a number of applications including:
- smart data generation from raw data
- predictive analytics
- maintenance planning and scheduling
- advanced visualization
- remote operator support
In conclusion, the SERENA system has been tested and validated in five (5) industrial use cases considering different deployments and configurations validating the resiliency of the SERENA approach and developments.
In the period from M01 to M42, the work performed resulted in the following main outcomes:
- Cloud based platform for remote diagnostics
- A solution for remote factory condition monitoring and control. This concerns a universal data collection mechanism (SW & HW) including data pre-processing and forwarding.
- An edge analytics service
- AR-based technologies for remote assistance and human operator support
- Maintenance planning and scheduling tool
- 3D Interactive technologies for Operator Maintenance Support
- Data driven predictive maintenance pipeline
As well as the instantiation of the SERENA system to its five use cases consisting the below:
- Pilot on versatile maintenance for tool providers (COMAU)
- Pilot cell for versatile maintenance in Elevators production industry (KONE)
- Pilot cell for versatile maintenance in Metrological engineering industry (TRIMEK)
- Versatile maintenance in Steel parts production and link to other industries (VDLWEW)
- Pilot cell for versatile maintenance in White goods industry (WHEMEA)
The above mentioned results, among others, have been extensively disseminated throughout the project lifetime. In summary the dissemination activities sum up to:
- 20 publications (book, book chapters, papers)
- Participation in 33 events
- 3 lectures
- Contribution to 4 thesis (PhD, MSc, Bachelor)
- 3 Newsletters
- 1 teaser video
- Participation in 6 joint events with the ForeSee cluster
Regarding the exploitation of the solutions, the SERENA partners will engage in joint exploitation activities within the project’s (business) ecosystem. To this end, partners will engage inflexible ‘supply-chain’ like agreements allowing for the provision of platform deployments as well as technical support services, training and other consulting services to enterprises (manufacturing companies, IT providers, maintenance companies, etc.) making use of the project platform and tools.
More details can be retrieved in D7.4 which is publicly available through the SERENA web site.
- Cloud based platform for remote diagnostics
- A solution for remote factory condition monitoring and control. This concerns a universal data collection mechanism (SW & HW) including data pre-processing and forwarding.
- An edge analytics service
- AR-based technologies for remote assistance and human operator support
- Maintenance planning and scheduling tool
- 3D Interactive technologies for Operator Maintenance Support
- Data driven predictive maintenance pipeline
As well as the instantiation of the SERENA system to its five use cases consisting the below:
- Pilot on versatile maintenance for tool providers (COMAU)
- Pilot cell for versatile maintenance in Elevators production industry (KONE)
- Pilot cell for versatile maintenance in Metrological engineering industry (TRIMEK)
- Versatile maintenance in Steel parts production and link to other industries (VDLWEW)
- Pilot cell for versatile maintenance in White goods industry (WHEMEA)
The above mentioned results, among others, have been extensively disseminated throughout the project lifetime. In summary the dissemination activities sum up to:
- 20 publications (book, book chapters, papers)
- Participation in 33 events
- 3 lectures
- Contribution to 4 thesis (PhD, MSc, Bachelor)
- 3 Newsletters
- 1 teaser video
- Participation in 6 joint events with the ForeSee cluster
Regarding the exploitation of the solutions, the SERENA partners will engage in joint exploitation activities within the project’s (business) ecosystem. To this end, partners will engage inflexible ‘supply-chain’ like agreements allowing for the provision of platform deployments as well as technical support services, training and other consulting services to enterprises (manufacturing companies, IT providers, maintenance companies, etc.) making use of the project platform and tools.
More details can be retrieved in D7.4 which is publicly available through the SERENA web site.
The progressive and pervasive digitization of industry brings a paramount opportunity to enhance the productivity of manufacturing and assembly operations. In this context, state-of-the-art production systems implement Predictive Maintenance (PdM) solutions to complement preventive maintenance scheduling and avoid costly unexpected breakdowns and corrective maintenance actions, and this where the SERENA R&D project is framed.
SERENA was built upon the needs for saving time and money, minimizing the costly production downtimes, covering the requirements for versatility, transferability, remote monitoring and control by a) a plug-and-play cloud-based communication platform for managing the data and data processing remotely, b) advanced IoT system and smart devices for data collection and monitoring of machinery conditions, c) artificial intelligence methods for predictive maintenance and planning of maintenance and production activities, d) AR-based technologies for supporting the human operator for maintenance activities and monitoring of the production machinery status.
In this sense, the main difference of SERENA with existing solutions is based on the operator support service; integrated along with the entire predictive maintenance solution and real-time data monitoring. This interface helps technicians to identify the source of the error and go through determined steps in the problem-solving procedure, including all visualization systems and AR tools, as well as the scheduling options integrated, or working along, with this system.
In addition, SERENA was built to be flexible and scalable merging cloud based and edge deployed components. Through the SERENA architecture and its outcomes, various applications can be enabled with cyber-physical features within the Industrie4.0 and connected factories vision. In this regard, the SERENA system addresses some common needs of industrial enterprises:
# compatibility with both the on-premise and the in-the- cloud environments
# exploitation of reliable and largely supported Big Data platforms
# virtually unlimited horizontal scalability
# easy deployment through containerized software modules
SERENA was built upon the needs for saving time and money, minimizing the costly production downtimes, covering the requirements for versatility, transferability, remote monitoring and control by a) a plug-and-play cloud-based communication platform for managing the data and data processing remotely, b) advanced IoT system and smart devices for data collection and monitoring of machinery conditions, c) artificial intelligence methods for predictive maintenance and planning of maintenance and production activities, d) AR-based technologies for supporting the human operator for maintenance activities and monitoring of the production machinery status.
In this sense, the main difference of SERENA with existing solutions is based on the operator support service; integrated along with the entire predictive maintenance solution and real-time data monitoring. This interface helps technicians to identify the source of the error and go through determined steps in the problem-solving procedure, including all visualization systems and AR tools, as well as the scheduling options integrated, or working along, with this system.
In addition, SERENA was built to be flexible and scalable merging cloud based and edge deployed components. Through the SERENA architecture and its outcomes, various applications can be enabled with cyber-physical features within the Industrie4.0 and connected factories vision. In this regard, the SERENA system addresses some common needs of industrial enterprises:
# compatibility with both the on-premise and the in-the- cloud environments
# exploitation of reliable and largely supported Big Data platforms
# virtually unlimited horizontal scalability
# easy deployment through containerized software modules