Periodic Reporting for period 1 - STREAM-0D (Simulation in Real Time for Manufacturing with Zero Defects)

The vision of STREAM-0D is to prevent defect generation and propagation by minimising product variability, exploiting to the maximum level the potential of simulation models, generating real time running models to optimise the production process through smart decision making...\n\nThe vision of STREAM-0D is to prevent defect generation and propagation by minimising product variability, exploiting to the maximum level the potential of simulation models, generating real time running models to optimise the production process through smart decision making, based on the combination of input data from the real world and output data from the simulation model. The core of this approach is constituted by the Reduced Order Modelling (ROM) approach, which allows the generation of real time capable models. These models, fed with actual data measured in-line during the process, will generate the control data for the production line machines in order to adjust the process parameters to get a ?perfect? product, fitting exactly the target design specifications.
This closed loop between simulation, measurements and production will allow us to continuously adjust the production process and quickly customise it for new batches with different design targets. It will allow marking each unit with its exact indicators and reducing down times related to readjustment of the line for new designs. Moreover, it will generate a big amount of data which can be stored, processed and exploited for generating and managing knowledge which can be used to improve the production process, keep traceability, enable early detection of defect patterns, and generate rules for improving decision-making.
STREAM-0D will allow industries:
?To adjust the manufacturing process in real time, introducing smart decisions based on the forecast of the models, thus reducing the product variability, increasing the efficiency, saving time and costs and reducing the number of rejected units or discarded material.
?To absorb the effect of component variability, and even reduce the tolerance requirements for suppliers, as it will be possible to adjust process variables during the production process itself.
?To exploit the full potential of knowledge-based and data-driven simulation models not only in the design process but also in the assembly process.
?To increase the flexibility of manufacturing processes, by setting design targets online through the control software, customizing batches of units with different features, and reducing down time related to changing design specifications.
?To generate and exploit data-driven models built upon the stored data from measurements and models, that will be used for further improving the process, detecting fault patterns, managing alarms and keeping traceability.\n\nDuring the first year the following work has been performed:
WP1 ?Requirements and specifications? has been finished. For each of the three industrial applications, the industrial processes have been thoroughly described, with their needs and constraints, the measurements already available, the current data management structure and control structures of the line. Moreover, the critical performance/quality indicators for each product have been identified, as well as the critical process parameters. This information has been compiled in Application Project Charters.
Within WP2, ?Real-time simulation modelling?, real-time reduced order models are being developed. The final result will be a solution for the output variables of interest as a function of the input parameters (time, dimensions, material parameters and applied loads), that will be able to run in real time. These models are based on detailed physics-based models, including all the key components, materials and physical phenomena needed to accurately forecast the product quality indicators. Key Performance Indicators have been identified as well as the critical factors that affect these KIPs.
Within WP3, ?Online data gathering systems and data-driven models? innovative sensors and instruments are being developed to gather online, in real-time, the input parameters for the ROMs. The development of the online data gathering systems has started: selection and implementation of measurement systems for standard quantities, such and temperatures, as well as the development of innovative ways for directly or indirectly measuring in a non-destructive way the more complex parameters, such as geometries and rheological material properties. Preparation steps are being taken to gather complete data sets that allow the development of data-based models. These steps consist in developing traceability procedures so that input and output parameters are perfectly matched.
Finally, within WP7, ?Dissemination, exploitation and IPR management?, a detailed dissemination plan has been defined, with the high-level communication objectives, the target stakeholders, messages to be delivered, channels to be used, and activities to be performed. We have put in place all the tools needed for communication purposes, that is the project identity, including the logo; on-line tools, like the official project website, and social media; and off-line tools, like brochures, posters, roll-up, gadgets, etc. A detailed plan for the identification, protection and exploitation of results has been defined. The background table has been consolidated, and the (expected) results table has been determined, which comprises the definition of ownership and preliminary protection actions.\n\nDynamic Data-Driven Application Systems is the linkage of modelling tools with measurement devices for real-time control of applications. This synergistic feedback control loop among applications, models and measurements is a novel technical direction that has been applied in some sectors, but its huge potential for manufacturing remains untapped. The ambition of this project is to show the technical and economic viability of implementing this novel technological solution in an operational industrial environment. To overcome the industrial challenges that will allow us to deliver the project objectives, the following advances will be made:
-Adaptive process control based on real-time simulation integrated in the production chain, linking physics-based models of product/process with measurement devices for real-time control and customisation of industrial processes.
-Reduced Order Modelling techniques for real-time simulation and real-time process control, applying ROMs for real-time simulation and control of multi-stage industrial processes.
-Online data gathering systems, measurements of complex properties/variables and online inspection tools, developing fast, robust and accurate measurement systems for the online measurements of complex dimensional and material properties.
- Application of data-based models for real time control and adjustment of production processes, creating data-based models based on extensive data storage and processing, combining it with physically based models in an optimal way.
The expected impact of the project is:
-Achievement of zero defects in multi-stage production lines
-Reduction of production costs by 15%
-Increased production flexibility. Higher production rates by 15%
-Reduction of waste and scrap by 10%
The three products are representative of a broad number of industrial products, processes, materials and physical phenomena of the European manufacturing industry. The project will be demonstrated on these three lines, but the exploitation and dissemination plan that will be developed during the project will make it possible to leverage the effect of the project results, impacting a large number of industries after the project.
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Simulation in Real Time for Manufacturing with Zero Defects
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