A modelling framework to support design of complex engineering systems in early design stages

Abdoli, Shiva; Kara, Sami

doi:10.1007/s00163-019-00321-9

Cited by 9 publications

(12 citation statements)

References 56 publications

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“…2 The overall structure of the framework with applied methods and their data exchange flow to achieve an executable architecture and is named System-State Meta-Model (SSMM). These architecting guidelines are briefly explained here and interested readers are referred to this reference [31] for details.…”

Section: Framework Structure and Applied Methodsmentioning

confidence: 99%

“…The approach used the OO method to identify the elements in an RMS and suggested four classes as basic elements: material processing equipment, storage equipment, robot, and Automatic Guided Vehicle (AGV). From the OO and domain modelling perspective, the defined classes were not comprehensive enough Not defined [26, 27] [ 28, 29] [ 30] FSM [31] to illustrate a generic RMS. Generally, all RMSs do not use AGV and robots.…”

Section: System Architecting and Validationmentioning

confidence: 99%

“…Existing works mostly modelled operational policies as a fixed part of models, so simulation did not clarify the impact of different policies on performance. Abdoli and Kara [31] introduced architecting guidelines by incorporating the OO and Finite-State-Machine (FSM) methods to develop an executable system architecture (explained shortly).…”

Section: System Architecting and Validationmentioning

confidence: 99%

“…Besides a recent work by Abdoli and Kara [31], the reviewed works realize some modelling aspects of CEPS design but not all in an integrated manner [18]. However, integrating different models enhances the consistency of the exchanged data/information [38].…”

Section: Research Gapmentioning

confidence: 99%

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A modelling framework to support integrated design of production systems at early design stages

Abdoli

2022

Int J Interact Des Manuf

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Multidisciplinary, large scale, and dynamic essence of production-logistic systems make their design knowledge complex. As a result, designers from different disciplines mostly design these systems with sequential approaches. This does not address the impact of single design decisions on overall system performance, which may lead to inconsistencies between different disciplines or failures. This paper aims to realise the integrated design of such systems by introducing a framework that incorporates Systems Engineering and Object-Oriented methods to develop a model that holistically embodies design knowledge of such systems. This model is constructed in Finite-State-Machine formalism to achieve an executable architecture and integrated with optimization models to allow simulation of alternatives and to observe the impact of design decisions on system behaviour. Supportive algorithms are introduced for refinements of design alternatives according to the simulation results. A fuzzy assessment approach is introduced to also assess the alternatives against qualitative criteria. The framework integrates simulation and fuzzy assessment results and performs a multi-criteria assessment to select an alternative for the detailed design. Therefore, the framework can stand as a decision support framework at early design stages, giving insights to designers about the impact of single design decisions on system overall performance and satisfaction of various objectives.

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Section: Framework Structure and Applied Methodsmentioning

confidence: 99%

Section: System Architecting and Validationmentioning

confidence: 99%

Section: System Architecting and Validationmentioning

confidence: 99%

Section: Research Gapmentioning

confidence: 99%

See 2 more Smart Citations

A modelling framework to support integrated design of production systems at early design stages

Abdoli

2022

Int J Interact Des Manuf

Self Cite

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“…Complex engineering systems are characterised by having a large number of dimensions, non-linear models, strong interactions, unknown or inherently random plant parameters and time delays in the dynamical structure (Jamshidi, 1996; Eusgeld et al , 2011). Many modern engineering projects are large complex engineering systems within dynamic environments, which usually comprise a large number of interacting sub-systems for components, processes, activities, stakeholders, resources and information (Abdoli and Kara, 2020; Zhu and Mostafavi, 2017). As shown in Table 1, these complex engineering systems can be divided into four levels based on the unified classification from Uniclass, namely, the system-of-systems, system, sub-system and asset levels (Pimmler and Eppinger, 1994; Senthilkumar and Varghese, 2009; Chou and Tseng, 2010; Eusgeld et al , 2011; Delany, 2019).…”

Section: Introductionmentioning

confidence: 99%

Understanding design change propagation in complex engineering systems using a digital twin and design structure matrix

Chen

Whyte

2021

ECAM

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PurposeAs the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).Design/methodology/approachThe paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.FindingsThe digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.Originality/valueThis research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.

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Modelling engineering interfaces in big science collaborations at CERN: an interaction-based model

Nicquevert

Boujut

2021

Res Eng Design

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A modelling framework to support design of complex engineering systems in early design stages

Cited by 9 publications

References 56 publications

A modelling framework to support integrated design of production systems at early design stages

A modelling framework to support integrated design of production systems at early design stages

Understanding design change propagation in complex engineering systems using a digital twin and design structure matrix

Modelling engineering interfaces in big science collaborations at CERN: an interaction-based model

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