K6
SDM 2

Back to overview

10:40
conference time (CEST, Berlin)
The Virtual Lifecycle Manufacturing – Connecting the Real and the Virtual World for the Benefit of Industrial Products
26/10/2021 10:40 conference time (CEST, Berlin)
Room: K
I. Hahn (Simufact Engineering GmbH - Part of Hexagon, DEU); S. Huhn (Forming Technologies, CAN)
I. Hahn (Simufact Engineering GmbH - Part of Hexagon, DEU); S. Huhn (Forming Technologies, CAN)
Amongst all phases of the lifecycle of an industrial product, the biggest potential for cost saving as well as for the optimization of product properties is offered during component design. The majority of the cost of a component is defined here since early decisions into the design affect all the phases coming afterwards – engineering, prototyping and, of course, manufacturing. On the other hand, creating the best product design means to take into account many aspects of manufacturability and all the expectations towards the behaviour of the fully assembled final product. It is obvious that a complete and synchronized data flow throughout the whole product lifecycle is very beneficial for lowest costs and the best quality. Smart manufacturing means to have a specific digital twin in each phase of the product lifecycle. Particularly, during design and engineering, virtual data can already be measured - clearly before any physical prototype is available for physical inspection. Thus, appropriate decisions affecting the design and manufacturing of a component can be made very early with respect to quantitative knowledge rather than guessing. Later, when physical measurements from prototypes or manufactured products are available, those can be utilized to validate and optimize the digital twins. The physical and the virtual world are fully connected. Information exchange between all stages of the product lifecycle is maintained: The connected data flow in parallel to the path of the real product through its lifecycle is called the digital thread. It helps to feed back the right information to the right place in the right time. This paper describes the Virtual Lifecycle Manufacturing (ViLMa), an engineering backbone for smart manufacturing. This framework connects between the various engineering applications like CAD, CAE, CAM and metrology. It is therefore very different from a PLM system that purely manages all the product-related data. The paper shows particular examples of industrial application. These examples illustrate how different technologies can be merged to reach the optimum benefit.
smart manufacturing, product lifecycle, digital twin, virtual measurement, simulation, assembly
11:00
conference time (CEST, Berlin)
SPDM Requirements to Manage the Simulations of Smart Products
26/10/2021 11:00 conference time (CEST, Berlin)
Room: K
M. Schlenkrich (MSC Software GmbH, DEU)
M. Schlenkrich (MSC Software GmbH, DEU)
Products are becoming smarter having more sensorics and more complex control-logic incorporated, allowing them to more actively interact with the environment. Simulating such smart products becomes a challenge as the simulation models becomes more complex as also the whole interaction with the environment and the controller logic needs to be represented in the simulation model. With this added complexity, also the number of load cases and scenarios will increase as more and more interaction patterns and behaviors of the model need to be simulated. For autonomous system this can become an extremely huge number, actually getting to a point, where the identification (such as finding all the edge cases9of all possible situation is in-itself an simulation exercise. As companies adopt a more agile development process for such smart products, there is a growing demand to test and validated the development continuously (CI/CD; Continuous Integration, Continuous Delivery and Continuous Deployment)), especially the control-logic and a high frequencies which demands continuous testing and validation of the product throughout the development. To handle the sheer amount of simulations, all the different models of components and environment, the scenarios and load cases and the need to conduct simulation more automatically with every change in the design (particularly of the control-logic) makes it almost mandatory to have an simulation data and process management (SPDM) solution. In this paper we will outline all the main architectural challenges to support this of such an SPDM system. We will cover: • Management of the different model component constituting a simulation model. These models will be generated by different groups, which adds significant challenges in terms of collaboration, version and revisions management and automated integration to the final simulations model. • Providing an execution environment, where multiple (potentially 100’s to 1000’s) instances of complex co-simulation can be performed. • Having an result management environment which then aggregated the results and their KPIs into a form allowing dashboarding, analysis tools and AI/ML methods to easily process the data.
SPDM, CI/CD, cloud, DOE, trade-off, autonomous, ML, AI
11:20
conference time (CEST, Berlin)
The Impact of Business Process Modeling in the Context of SPDM Environment: A Human-in-the-loop Approach for Design Optimization and Business Decision Making
26/10/2021 11:20 conference time (CEST, Berlin)
Room: K
M. Turchetto, A. Viola (Esteco SPA, ITA)
M. Turchetto, A. Viola (Esteco SPA, ITA)
Manufacturing companies look at reliable digital technologies to address increasing product complexity, innovate the engineering design process and reduce investment in physical prototypes. The ability to use simulation and perform design space exploration studies usually remains in the domain of a relatively small group of simulation experts too often isolated from the rest of the organization. Regardless of the adoption of Simulation Process and Data Management (SPDM) systems, there is still a siloed approach to share projects and results. Simulation models are sent by emails or placed on a shared drive with no version control, and disconnected from a common repository with other actors involved in the product development. The lack of a digital infrastructure that enables model integration and interconnectivity makes it difficult to share requirements, design objectives, constraints, simulation models and optimization results across the extended enterprise. Without a representation of the flow of activities and data in place, decision makers struggle to access the key product metrics that might be the results of design optimization studies over all stages of the product development. What if you could break technical silos across engineering disciplines and ensure corporate knowledge is captured and re-used to drive business decisions? What if you could make simulation routine analysis accessible to engineers and everyone else involved in the design process, enabling CAE democratization? What if you could maximize the scope of a SPDM system by integrating the Business Process Modeling technology to automate models, coordinate user tasks, and track the activity of each single analyst? This paper shows how an actionable Business Process Model and Notation (BPMN) workflow has been set up in a SPDM platform to create a business decision support system in the context of design optimization of an automotive composite leaf spring suspension. This innovative methodology makes it possible to connect and establish communication between different company departments involved in the product development process.
Simulation Process and Data Management, Business Process Modeling, Design Optimization, Simulation Democratization, BPMN, Business Process Modeling Notation
11:40
conference time (CEST, Berlin)
Next Generation Information System Architecture for Simulation-led Engineering of a Fusion Reactor
26/10/2021 11:40 conference time (CEST, Berlin)
Room: K
M. Norris (the SDMConsultancy, GBR)
M. Norris (the SDMConsultancy, GBR)
Nuclear fusion offers the prospect of pollution and carbon dioxide-free energy to significantly reduce climate change. Recent advances in high temperature superconducting magnets enable significantly higher magnetic fluxes to contain the plasma in which the fusion reaction occurs. Higher magnetic fluxes offer the possibility of a commercially viable fusion reactor with a major radius of 1.85m which could be manufactured economically. The design of such a spherical tokamak is extraordinarily challenging due to the extreme physical conditions of a vacuum vessel containing a 100 million degree centigrade plasma producing a strong neutron flux and surrounded by cryogenically cooled super-conducting magnets. The electrical power supplies need to deliver millions of amps of current. The cooling of the plasma facing components is particularly challenging, analogous to gas turbine blades which operate in a gas flow which is hotter than their melting point. Since a Spherical Tokamak with a positive energy output has yet to be constructed, the only way to design the system is to use numerical simulation to model first the plasma and then to model the behaviour of the engineering systems which confine the plasma, deliver power into the plasma, extract heat from the plasma-facing components and extract waste products. The development of the reactor system begins with a system model in a Model-based Systems Engineering (MBSE) tool. The performance of a system concept is first evaluated using 0D simulation of the reactor system including the behaviour of the plasma. Then 2D and 3D plasma simulations of steady state operation, start up and shut down are carried out to understand the required performance and various physical loads on the reactor systems. Based on the loadings derived from the physics simulations, 3D engineering simulations including CFD, structural, thermal electromagnetic and neutronics FEA are then carried out to size the engineering systems and components. In order to manage the system design, the evaluation and maturation of concepts with hundreds of design parameters based on multi-fidelity simulations, an information system managing requirements, MBSE and simulations is needed. Such an information system combining the management MBSE models, 0D simulations based on MBSE system models and 3D simulations using classic SPDM techniques was beyond the state of the art in 2020. This paper describes how an information system to manage spherical tokamak evaluation was architected, designed and Proof of Concepts build on an agile, open PLM platform.
Simulation Data Management, SDM, Simulation Process and Data Management, SPDM, Digital Thread, System of Record, Nuclear Fusion Reactor, Spherical Tokamak
×

[TITLE]

[LISTING

[ABSTRACT]

[DATE]

[ROOM]

[KEYWORDS]