Preparation of CAD model for collaborative design meetings: proposition of a CAD add-on

Khatib, Ahmad Al; Fleche, Damien; Mahdjoub, Morad; Bluntzer, Jean-Bernard; Sagot, Jean‐Claude

doi:10.1007/978-3-319-45781-9_86

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…So, one scenario to overpass the topological issues can be to trace also the evolution of the product design requirements that have an impact on the decision making. For instance, it is possible to ease the preparation of collaborative design meetings using CAD add-on that shows the link between the CAD model and the design requirement (Al Khatib et al, 2017). Based on this kind of tool, it is easier to trace the link between the validation of design requirements and the variation in the topology of the CAD part.…”

Section: Discussionmentioning

confidence: 99%

Collaborative project: Evolution of computer-aided design data completeness as management information

Fleche

Bluntzer

Khatib

et al. 2017

Concurrent Engineering

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Today, product design process is facing a market globalisation led by distributed teams. The international market context, in which industrial companies evolve, leads design teams to work in a large multidisciplinary collaborative context using collaborative practices. In this context, product design process is driven by the integration and optimisation of stakeholders’ collaboration. Thus, to facilitate collaborative steps, new management strategies are defined and new information systems can be used. To this end, we have focused our article on the topic of collaborative product design project management. We have underlined the necessity to use quantitative and non-intrusive indicators during the management of collaborative design phases besides subjective evaluations. Tracking these indicators is performed in parallel to the existing approaches in order to evaluate the performance of collaborative design project. Moreover, these indicators can show the impact of the collaboration steps on the design project evolution. The computation of proposed indicators is based on precise metrics which details the completeness of the computer-aided design model and its evolution depending on the used collaborative tools and the project milestones. This computation uses the importance of each computer-aided design model part and the transformation rate of each part of the computer-aided design model.

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Section: Discussionmentioning

confidence: 99%

Collaborative project: Evolution of computer-aided design data completeness as management information

Fleche

Bluntzer

Khatib

et al. 2017

Concurrent Engineering

Self Cite

View full text Add to dashboard Cite

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Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

2023

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Complexity is often regarded as a “problem” to solve. Instead of attempting to solve complexity, we follow systems engineering practices and switch back to the problem domain, where a major obstacle is the impossibility to universally define complexity. As a workaround, we explored complexity characterization and its existing shortcomings, including: lack of standardization, inconsistent semantics, system-centricity, insufficiently transparent reasoning, and lack of validation. To address these shortcomings, we proposed a compilatory framework to characterize complexity using the Five Ws information-gathering method. The answer to the WHO question proposed four complexity viewpoints; the answer to the WHY question proposed a two-dimensional structure for complexity drivers; and the answer to the WHAT question derived generalized complexity challenges. As a preliminary step to show the potential of the framework to characterize complexity, we used and validated it as a tool to structure general literature related to complexity. In general, our findings suggest that papers with complexity solutions do not frame their research within the complexity problem domain, hindering the contribution evaluation. Through the viewpoints, we identified general research gaps of six solution directions. From the drivers, we noted three observations in the discourse of complexity origins: (1) a system-driven tendency, (2) a preference for concreteness vs. abstraction, and (3) an unclear distinction between origins and effects. Through the challenges’ findings we explored two hypotheses: (1) a system-centric preference; and (2) a solution-oriented vision, both of which were supported by the results (most challenges relate to the system viewpoint and challenges are defined based on solution directions).

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Preparation of CAD model for collaborative design meetings: proposition of a CAD add-on

Cited by 2 publications

References 15 publications

Collaborative project: Evolution of computer-aided design data completeness as management information

Collaborative project: Evolution of computer-aided design data completeness as management information

Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

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