CloudFlow is intended to provide a Cloud infrastructure Computing based on existing technology and standards that will allow SMEs that develop and commercialize software to offer to and future customers with new cloud services over the course of the year. the entire engineering and manufacturing chain. CloudFlow covers computer-aided design and manufacturing (CAD) and computer-aided manufacturing (CMM). / (CAM), in particular, computer-aided engineering (CAA), computer-aided computational fluid dynamics (CFD), including pre- and post-processing, and post-processing, the simulation of mechatronic systems (Functional Digital Mock-Up (FDMU) and product lifecycle management (PLM). (PLM), including data archiving. Within CloudFlow, our experiment focuses on the development of a cloud-based simulation tool for process replication of rubber injection molding. Rubber injection molds are typically designed on the basis of the experience and with the support of some numerical simulations. This has serious limitations when optimal designs are needed. To overcome this problem, the computational workflow in the cloud will exploit a procedure based on an adaptive DoE, simulations and and data mining techniques for the development of automatic CFD and data post-processing. This CloudFlow experiment is intended to reproduce a rubber injection process. Given a 3D design of the mold and its heating system, the workflow will analyze the parameters of the heating system and the process such as rubber mass flow rate and pressure at each process such as rubber mass flow rate and pressure at each power point, as well as the heating power. With this information, duly processed in the CloudFlow workflow, the end-user will be able to minimize injection time, fuel consumption, and energy and rubber product defects. This experiment is driven by the need of the rubber sector. Numerical techniques currently being used to aid design of the rubber mold do not comply with the manufacturer’s requirements on terms of accuracy of the material model, characterization of the material, and material model and optimum design time. We will focus here on this last point. Objective. This experiment aims to provide manufacturing end-users with opportunities to to evaluate beneficiaries in terms of improving the quality of their quality of parts using CAE design procedures in the cloud.
These are the partners participating in the experiment:
The data presented here refer exclusively to the experiment in which ITAINNOVA participates.
This project has received funding from the European Union’s 7th Framework Program.
