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)

Manufacturing performance characteristics - (15)


    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: reduction of waste of raw material through better machining simulation
        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: 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

Manufacturing future products - (4)


Computational Cloud Services and Workflows for Agile Engineering
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