Computational Cloud Services and Workflows for Agile Engineering

CloudFlow will enable the remote use of computational services distributed on the cloud, seamlessly integrating these within established engineering design workflows and standards. CloudFlow aims to empower the different engineering disciplines with on-demand access to scalable computational services, allowing them to start any process when desired and without the need for a complex local infrastructure of cutting-edge high performing computers. The new engineers’ workplaces do not need to be equipped with expensive software (CAD, CAM, CAE, PLM, data archival) and their required operating systems and versions, or with special hardware (CPU, RAM, GPU) and their dedicated drivers. Therefore, the engineer will not need multiple computers for different tasks; or in the case of limited computers, the engineers will not need to wait for the availability of the resources. In order to master these challenges, CloudFlow will address different aspects of computational cloud services for engineering. From a technical point of view, the project will focus on: data (exchange and integration); services (adaptation, interoperability); and workflows (integration, co-operation). The technical aspects will consider the current situation at the engineering workplaces and they will adapt and customize the existing technology to better serve the current needs in an agile and flexible manner. From a user prospective, the project will deal with: usability and accessibility; business models; and competitive calls (for application experiments). In this context, it will prepare the engineers to use the computational services on the cloud, it will investigate and create new business models to use these kinds of services on demand and it will continuously be refined by means of involving more users and more system vendors, with different needs, and with different application experiments being called for in competitive calls.
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Start date: 01-07-2013
End date: 31-12-2016
Total budget - Public funding: 8 742 828,00 Euro - 6 623 000,00 Euro
Call topic: Application experiments for robotics and simulation (I4MS) (FoF.ICT.2013.7.1)
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Traditionally, the European manufacturing industry is characterized by innovative technology, quality processes and robust products which have leveraged Europe's industrialization. However, globalization has exposed Europe's industry to new emerging and industrialized manufacturing markets and the current economic challenges have decelerated the internal boost and investment, respectively. Hence, new ICT infrastructures across Europe need to be established to re-enforce global competitiveness.The motivating idea behind CloudFlow is to open up the power of Cloud Computing for engineering WorkFlows (CloudFlow). The aim of CloudFlow is to enable engineers to access services on the Cloud spanning domains such as CAD, CAM, CAE (CFD), Systems and PLM, and combining them to integrated workflows leveraging HPC resources. Workflows are of key importance in today's product/production development processes were products show ever increasing complexity integrating geometry, mechanics, electronics and software aspects. Such complex products require multi-domain simulation, simulation-in-the-loop and synchronized workflows based on interoperability of data, services and workflows.CloudFlow is an SME-driven IP incorporating seven SMEs: Missler (CAD/CAM), JOTNE (PLM), Numeca (CAE/CFD), ITI (Systems), Arctur (HPC), Stellba Hydro (hydraulic machines/hydro turbines) and CARSA (business models and security). Four renowned research institutions comple¬ment the consortium: DFKI, SINTEF, University of Nottingham and Fraunhofer.CloudFlow will build on existing standards and components to facilitate an as-vendor-independent-as-possible Cloud engineering workflows platform. Open Cloud Computing Interface (OCCI), STEP (for CAD and CAE data) and WSDL (for service description and orchestration) are amongst the core standards that will be leveraged. The key aspects (from a technical and a business perspective) are: Data, Services, Workflows, Users and Business models including Security aspects.CloudFlow will conduct two Open Calls for external experiments investigating the use of the CloudFlow infrastructure in new and innovative ways, outreaching into the engineering and manufacturing community and engaging external partners. Each of these two Open Calls will look for seven additional experiments to gather experience with engineering Cloud uses and gaining insights from these experiments.CloudFlow is striving for the following impacts: a) increasing industrial competitiveness by contributing to improve performance (front-loading, early error detection, time-to-market, ...) and innovation (co-use of models, early virtual testing) and b) improving in innovation capabilities by enabling more engineers to gain insights and to create innovation by accessing 'new' tools and easing the use of Cloud Infrastructures.All in all, CloudFlow wants to contribute to a wider adaption of Cloud infrastructures and making them a practical option for manufacturing companies.



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Economic sustainability Supply chain and value network efficiency Circular economy Social sustainability Increasing human achievements in manufacturing systems Occupational safety and health Environmental sustainability Reducing the consumption of energy, while increasing the usa...
Reducing the consumption of water and other process resource... Material efficiency Waste minimisation Reduction of energy consumption (in %) Reduction of CO2 emissions (in %) Reduction of waste (in %) Reduction of material consumption (in %)
    Comment: 6 of the CloudFlow application experiments are rooted in the design and engineering chain for hydrowater plants which are one important pillar of the green energy sector
      Comment: reduce the waste of raw material
        Comment: Biocurve manufactures condensing biomass boilers for central heating and hot water systems for domestic users. Development of a virtual model of the current 25 kW boiler model in which the number of pipes has been reduced from ten to three. The reduction of the number of pipes in this model represents a saving of 18 kg of stainless steel (a 32% of the original weight of the pipes of this boiler). This lower number of pipes implies savings of raw material, but also, savings in fabrication costs (lower hours of workforce required, smaller insulation needed, less paint) and transport costs (lower volume of the boiler). The total cost saved estimated for this model is around 400 € per unit. Within the experiment for optimizing energy consumption and noise emission of the cooling airflow for compressors some of the physical
      Comment: Simulation-based optimization of product designs, reduced number of physical prototypes contribute - in general - to a reduction of errors and scraps
        Comment: The experiments about optimizing heat exchanger design of biomass boilers through CFD simulation has achieved that five to six initial biomass boiler prototypes or separate parts (heat exchanger, outer jacket, burner) could be saved with the cloud-enabled environment.
      Comment: reduction of waste of raw material through better machining simulation
        Comment: One of the experiment partner is the Spanish SME Biocurve. The company manufactures condensing biomass boilers for central heating and hot water systems for domestic users. The design of such boilers is currently based on the experience of the Biocurve technical staff. Thanks to the experiment, one of the main components of the boilers, the exchanger, has reduced the volume and materials needed without altering the efficiency, thus leading to a lower "CO2-emission to inverse cost" ratio.
      Comment: Machining simulation and finding optimal machining strategies contribute to wasting lass raw material (e.g. metal) and energy (electricity consumed by NC machines)
        Comment: One CloudFlow application experiment aims at minimizing energy consumption and noise emissions created by the fan and the cooling airflow of compressors. One of the physical improvements is the reduced fan power consumption from 4kWel to 2,75kWel (>30%). Clients from the experiment partner BOGE will save electricity cost that amounts to about 350,000 euros per year. The design and layout of the splitter-type silencer can be calculated within hours instead of days which also reduces the use of energy. ESS design MEMS sensor components for commercial high-end applications. Cost savings due to chip area reduction is a major driver. With the CloudFlow portal ESS have access to high quality chip-design tools and can optimize chip size. 5% savings on a relatively small quantity of 1 million of ESS chips originally sized at 1640x1600 um each give approximately 235gr of savings in Si chips. This saves • 188kg of fossil fuel • 8.46 kg of chemicals • 3.76 tons of water

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Manufacturing the products of the future Complex structures, geometries and scale
Customised products Resource efficient, sustainable products