The vision of RECLAIM is to demonstrate technologies and strategies to support a new paradigm for refurbishment and re-manufacturing of large industrial equipment in factories, paving the way to a circular economy. Its ultimate goal is to save valuable resources by reusing equipment instead of discarding them.
RECLAIM will support legacy industrial infrastructures with advanced technological solutions with built-in capabilities for in-situ repair, self-assessment and optimal re-use strategies. It will establish new concepts and strategies for repair and equipment upgrade and factory layouts' redesign in order to gain economic benefits to the manufacturing sector, with demonstration in friction welding (Harms und Wende, Germany), enamelling and robotics for white goods (Gorenje, Slovenia and Czech Republic), wood working (Podium, Switzerland), shoe making (Fluchos, Spain) and bleaching of textiles (Zorluteks, Turkey).
The technological core of RECLAIM is a novel Decision Support Framework that guides the optimal refurbishment and re-manufacturing of electromechanical machines and robotics systems. The framework uses IoT sensors, novel prediction, and process optimisation techniques to offer machine lifetime extension and thus increased productivity. Innovative fog computing and augmented reality techniques are combined with enhanced health monitoring and failure inspection and diagnosis methodologies that enhance the effective use of materials, improve maintenance capabilities and eventually, drastically increase the return of investments (ROI).
RECLAIM re-use approach also fosters servicing and upgrading of legacy equipment. For that, European machinery industry will move from an equipment-based business to a value-added business, where equipment servicing and equipment knowledge are main business drivers.
RECLAIM solution will be demonstrated in five real industrial environments to evaluate the lifecycle of the industrial equipment and show the feasibility of the approach for integration and scale-up to other industrial sectors. Having RECLAIM technology available, drastically increased efficiency, lifetime extension and high economic benefit will be achieved and a significant step towards 100% re-use will be made.
The standards that are proposed by RECLAIM are the "CWA 17492:2020-Predictive control and maintenance of data intensive industrial processes" standard, which focuses on predictive maintenance, defines machine learning / deep learning techniques for predicting process and equipment drifts, thereby providing recommendations on when to perform maintenance and the state of the machine.
Web resources: |
https://cordis.europa.eu/project/id/869884
https://www.reclaim-project.eu |
Start date: | 01-10-2019 |
End date: | 30-09-2023 |
Total budget - Public funding: | 15 725 187,00 Euro - 12 750 199,00 Euro |
Twitter: | @Reclaim_FoF |
Original description
The vision of RECLAIM is to demonstrate technologies and strategies to support a new paradigm for refurbishment and re-manufacturing of large industrial equipment in factories, paving the way to a circular economy. Its ultimate goal is to save valuable resources by reusing equipment instead of discarding them. RECLAIM will support legacy industrial infrastructures with advanced technological solutions with built-in capabilities for in-situ repair, self-assessment and optimal re-use strategies. It will establish new concepts and strategies for repair and equipment upgrade and factory layouts’ redesign in order to gain economic benefits to the manufacturing sector. The technological core of RECLAIM is a novel Decision Support Framework that guides the optimal refurbishment and re-manufacturing of electromechanical machines and robotics systems. The framework uses IoT sensors, novel prediction, and process optimisation techniques to offer machine lifetime extension and thus increased productivity. Innovative fog computing and augmented reality techniques are combined with enhanced health monitoring and failure inspection and diagnosis methodologies that enhance the effective use of materials, improve maintenance capabilities and eventually, drastically increase the return of investments (ROI). RECLAIM re-use approach also fosters servicing and upgrading of legacy equipment. For that, European machinery industry will move from an equipment-based business to a value-added business, where equipment servicing and equipment knowledge are main business drivers. RECLAIM solution will be demonstrated in five real industrial environments to evaluate the lifecycle of the industrial equipment and show the feasibility of the approach for integration and scale-up to other industrial sectors. Having RECLAIM technology available, drastically increased efficiency, lifetime extension and high economic benefit will be achieved and a significant step towards 100% re-use will be made.Status
CLOSEDCall topic
DT-FOF-06-2019Update Date
27-10-2022Standardisation helps the end client to have complete knowledge of the equipment's lifespan, which increases dependability and enables servitisation (for example, leasing) towards machine resale. The standardisation criteria that are described by RECLAIM centre on two key subjects: (1) maintenance procedures and predictive maintenance, together with (2) specifications and design for remanufacturing.
The standards that are proposed by RECLAIM are the "CWA 17492:2020-Predictive control and maintenance of data intensive industrial processes" standard, which focuses on predictive maintenance, defines machine learning / deep learning techniques for predicting process and equipment drifts, thereby providing recommendations on when to perform maintenance and the state of the machine. A set of key performance indicators is defined in "EN 15341:2019-Maintenance-Maintenance Key Performance Indicators" to quantify and improve the efficacy, efficiency, and sustainability of maintenance actions for physical assets. “prEN 17485-Maintenance-Maintenance within physical asset management-Framework for improving the value of the physical assets through their whole life cycle” and “EN16646:2015-Maintenance-Maintenance within physical asset management” introduce the physical asset management and address the role and importance of maintenance within physical asset management system during the whole life cycle of an item. The maintenance process is depicted by all the characteristics and steps of the stated processes in "EN 17007:2018-Maintenance process and associated indicator," along with the construction of a maintenance model that provides instructions for defining indicators. This is a crucial step in standardising the entire maintenance procedure. By doing so, all the maintained equipment will be comparable to one another, allowing lifetime extension tactics to be eventually more accurate in their analysis. The "ANSI RIC001.1-2016-Specifications for The Process of Remanufacturing" standard, which focuses on the definition of remanufacturing and clearly distinguishes it from other activities, is one that addresses remanufacturing standards. Additionally, it offers a benchmark, specification, and characterisation of the remanufacturing process.
The standards that are proposed by RECLAIM are the "CWA 17492:2020-Predictive control and maintenance of data intensive industrial processes" standard, which focuses on predictive maintenance, defines machine learning / deep learning techniques for predicting process and equipment drifts, thereby providing recommendations on when to perform maintenance and the state of the machine.
Volunteers from FEUP, CERTH, and UNI collaborated to compile all the technical and standard data for the formulation of the technical specification based on the specifications specified by the pilots' leaders. A full explanation of the use cases and the machines involved in the refurbishment, remanufacturing, and retrofitting during the RECLAIM project has been developed using the needs that were determined during the information gathering phase. The matrix of requirements for the identification of the prospective issues to be the challenge at the RECLAIM project has been finished by the industrial partners Gorenje, Fluchos, Podium, Harms & Wende, and Zorlutek. The demand and gap in the standardised field were included in these matrices, which is a crucial factor to consider the technical solution in the future. UNI carried out the standardised analysis plan from the input data given by other partners involved in this endeavour.
The main standardisation gaps to be considered during the RECLAIM project were: Monitoring Sensors: Alignment verification, quality and density of water pipeline, energy consumption of the furnace, real time monitoring; Predictive Maintenance: Definition of standards to predict shutdown; Human Error: Need of standardized procedure to record spare parts.
Standardisation helps the end client to have complete knowledge of the equipment's lifespan, which increases dependability and enables servitisation (for example, leasing) towards machine resale. The standardisation criteria that are described by RECLAIM centre on two key subjects: (1) maintenance procedures and predictive maintenance, together with (2) specifications and design for remanufacturing.
The standards that are proposed by RECLAIM are the "CWA 17492:2020-Predictive control and maintenance of data intensive industrial processes" standard, which focuses on predictive maintenance, defines machine learning / deep learning techniques for predicting process and equipment drifts, thereby providing recommendations on when to perform maintenance and the state of the machine. A set of key performance indicators is defined in "EN 15341:2019-Maintenance-Maintenance Key Performance Indicators" to quantify and improve the efficacy, efficiency, and sustainability of maintenance actions for physical assets. “prEN 17485-Maintenance-Maintenance within physical asset management-Framework for improving the value of the physical assets through their whole life cycle” and “EN16646:2015-Maintenance-Maintenance within physical asset management” introduce the physical asset management and address the role and importance of maintenance within physical asset management system during the whole life cycle of an item. The maintenance process is depicted by all the characteristics and steps of the stated processes in "EN 17007:2018-Maintenance process and associated indicator," along with the construction of a maintenance model that provides instructions for defining indicators. This is a crucial step in standardising the entire maintenance procedure. By doing so, all the maintained equipment will be comparable to one another, allowing lifetime extension tactics to be eventually more accurate in their analysis. The "ANSI RIC001.1-2016-Specifications for The Process of Remanufacturing" standard, which focuses on the definition of remanufacturing and clearly distinguishes it from other activities, is one that addresses remanufacturing standards. Additionally, it offers a benchmark, specification, and characterisation of the remanufacturing process.