Engineering Design with Digital Thread

Singh, Victor; Willcox, Karen

doi:10.2514/6.2018-0569

Cited by 10 publications

(7 citation statements)

References 13 publications

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“…That means CSM and DCSM need to be executed by the same simulation times as SM. Therefore, we compared the total time consumption with the one using the automated (10) From the result, we find that the time-saving rate is 78.1%, meaning less time is needed to implement all the simulations. When the developers design the MDP algorithm in the case study, our MBSE tool-chain captures 14 tool operations (shown in Table V) in order to support automated parameter value selections (e.g., loading model in the simulation tool, generating FMUs).…”

Section: Discussion and Evaluationmentioning

confidence: 99%

“…Second, together with data integration, process management is required to support traceability management of data across the whole lifecycle. Stakeholders access the required data for different parameter configurations and architecture design expected as the digital thread [10]. Third, formalizations of the complex dependencies between architectures and parameter spaces are prerequisite for automated parameter value selection [11].…”

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confidence: 99%

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Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

Chen

Wang

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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Cyber-physical systems (CPSs) integrate heterogeneous systems and process sensor data using digital services. As the complexity of CPS increases, it becomes more challenging to efficiently formalize the integrated multidomain views with flexible automated verification across the entire lifecycle. This article illustrates a model-based systems engineering tool-chain to support CPS development with an emphasis on automated parameter value selection for co-simulation. First, a domain-specific modeling approach is introduced to support the formalizations of CPS artifacts, development processes, and simulation configurations. The domain-specific models are used as the basis to generate a Web-based process management system for automated parameter value selections, which coordinates Open Services for Lifecycle Collaboration services of development information and technical resources (models, data, and tools) in order to support automated co-simulation. The services are deployed by a service orchestrator based on a decision-making algorithm for parameter value selection. Finally, developers make use of the WPMS to implement simulations and to select system parameter values for co-simulation automatically. The approach is illustrated by a case study on auto-braking system development and we evaluate the efficiency of this tool-chain by both qualitative and quantitative methods. The results show that parameter values are selected more efficiently and effectively when implementing co-simulations using our tool-chain. Index Terms-Automated parameter value selection, cyberphysical systems (CPSs), model-based systems engineering (MBSE).

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Section: Discussion and Evaluationmentioning

confidence: 99%

mentioning

confidence: 99%

Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

Chen

Wang

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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“…This improved ability for configuration control of project information being digitally available will lead to a preference for model-centric certification, not our current approach for document-centric certification. Several examples include (Zimmerman, 2017;Singh & Willcox, 2018;Mavris, 2018).…”

Section: Modelmentioning

confidence: 99%

An “EPIIC” Vision to Evolve Project Integration, Innovation, and Collaboration with Broad Impact for How NASA Executes Complex Projects

Moreland

Evans

McGowan

et al. 2018

INCOSE International Symp

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Evolving Project Integration, Innovation, and Collaboration (EPIIC) is a vision defined to transform the way projects manage information to support real‐time decisions, capture best practices and lessons learned, perform assessments, and manage risk across a portfolio of projects. The foundational project management needs for data and information will be revolutionized through innovations on how we manage and access that data, implement configuration control, and certify compliance. The embedded intelligence of new interactive data interfaces integrate technical and programmatic data such that near real time analytics can be accomplished to more efficiently and accurately complete systems engineering and project management tasks. The system‐wide data analytics that are integrated into customized data interfaces allows the growing team of engineers and managers required to develop and implement major NASA missions the ability to access authoritative source(s) of system information while greatly reducing the labor required to complete system assessments. This would allow, for example, much of what is accomplished in a scheduled design review to take place as needed, between any team members, at any time. An intelligent data interface that rigorously integrates systems engineering and project management information in near real time can provide substantially greater insight for systems engineers, project managers, and the large diverse teams required to complete a complex project. System engineers, programmatic personnel (those who focus on cost, schedule, and risk), the technical engineering disciplines, and project management can realize immediate benefit from the shared vision described herein. Implementation of the vision also enables significant improvements in the performance of the engineered system being developed.

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“…Wettach et al [7] asserts that the digital transformation sparked by industry 4.0 is meant to be a lot more than a technology-driven change. Over the past few decades, industries have frontloaded their modelling, simulation and design exploration activities with the intention to improve knowledge early-on, make informed decisions already in conceptual stages of the product development process [8] and use this knowledge in manufacturing. Manufacturing plants all over the world, in diverse sectors, are now being upgraded in accordance with industry 4.0.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Industry 4.0 on Product Design and Development: Conceptual Foundations and Literature Review

Tatipala

Larsson

Johansson

et al. 2021

Smart Innovation, Systems and Technologies

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Since its introduction in 2011, industry 4.0 has been coined the "4th industrial revolution" following mechanization, industrialization and IT/automation as the first three, and represents the current trend of automation technologies (cyber-physical systems, internet of things, cloud computing, etc.,) in the manufacturing industry, with their potential for disruption of the manufacturing paradigm as we know it. However, the effect and role of industry 4.0 on the design and development of the new products to be manufactured in industry 4.0 facilities is not clear. This research presents a literature review to; 1) understand the concept of industry 4.0 from an implementation (state of practice) viewpoint, 2) learn about approaches and considerations currently deployed for developing products to be produced in manufacturing plants progressively transforming into industry 4.0 environments. Results reveal that the potential of industry 4.0 is underexploited within product design and development, especially in the conceptual stages lacking methods, tools, and approaches. While later stages of the product development (production planning, ramp-up) have received some attention in regards with optimizing production operations, several publications acknowledge its potential to benefit earlier process stages.

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Engineering Design with Digital Thread

Cited by 10 publications

References 13 publications

Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

An “EPIIC” Vision to Evolve Project Integration, Innovation, and Collaboration with Broad Impact for How NASA Executes Complex Projects

The Influence of Industry 4.0 on Product Design and Development: Conceptual Foundations and Literature Review

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