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- Arjomandi Rad, Mohammad, et al.
(författare)
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Correlation-based feature extraction from computer-aided design, case study on curtain airbags design
- 2022
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Ingår i: Computers in industry (Print). - : Elsevier. - 0166-3615 .- 1872-6194. ; 138
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Tidskriftsartikel (refereegranskat)abstract
- Many high-level technical products are associated with changing requirements, drastic design changes, lack of design information, and uncertainties in input variables which makes their design process iterative and simulation-driven. Regression models have been proven to be useful tools during design, altering the resource-intensive finite element simulation models. However, building regression models from computer-aided design (CAD) parameters is associated with challenges such as dealing with too many parameters and their low or coupled impact on studied outputs which ultimately requires a large training dataset. As a solution, extraction of hidden features from CAD is presented on the application of volume simulation of curtain airbags concerning geometric changes in design loops. After creating a prototype that covers all aspects of a real curtain airbag, its CAD parameters have been analyzed to find out the correlation between design parameters and volume as output. Next, using the design of the experiment latin hypercube sampling method, 100 design samples are generated and the corresponding volume for each design sample was assessed. It was shown that selected CAD parameters are not highly correlated with the volume which consequently lowers the accuracy of prediction models. Various geometric entities, such as the medial axis, are used to extract several hidden features (referred to as sleeping parameters). The correlation of the new features and their performance and precision through two regression analyses are studied. The result shows that choosing sleeping parameters as input reduces dimensionality and the need to use advanced regression algorithms, allowing designers to have more accurate predictions (in this case approximately 95%) with a reasonable number of samples. Furthermore, it was concluded that using sleeping parameters in regression-based tools creates real-time prediction ability in the early development stage of the design process which could contribute to lower development lead time by eliminating design iterations.
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| 3. |
- Arjomandi Rad, Mohammad, et al.
(författare)
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Data-driven and Real-time Prediction Models for Highly Iterative Product Development Processes
- 2022
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Ingår i: Transdisciplinarity and the Future of Engineering. - : IOS Press. - 9781643683386 - 9781643683393 ; , s. 463-472
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Konferensbidrag (refereegranskat)abstract
- Some high-level technical products are associated with transdisciplinary simulation-driven design processes. Therefore, their design process involves many stakeholders and is prone to frequent changes, leading to a highly iterative process with a long lead time. Despite the decades of statistical approximations and metamodeling techniques on prediction models, companies are still striving toachieve fully automated real-time predictions in early design phases. The literature study shows a gap in existing methods such as not being fully real-time or suffering from high dimensionality. This paper presents a generic model for the development process of such described products and motivation for such modeling through a series of semi-structured interviews with an automotive sub-supplier company. The proposed process model points to the digital verification in every design loop as the bottleneck which is then confirmed by interviewees. As alternative solutions to overcome the problems, a method for data-driven and real-time prediction models is presented to enable the designer to foresee the consequence of their decision in the design phase. To evaluate the method, two examples of such real-time metamodeling techniques, developed in an ongoing research project are discussed. The proposed examples confirm that the framework can reduce lead time spent on digital verification and therefore accelerate the design process in such products.
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| 4. |
- Arjomandi Rad, Mohammad
(författare)
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Data-driven and real-time prediction models for iterative and simulation-driven design processes
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The development of more complex products has increased dependency on virtual/digital models and emphasized the role of simulations as a means of validation before production. This level of dependency on digital models and simulation togetherwith the customization level and continuous requirement change leads to a large number of iterations in each stage of the product development process. This research, studies such group of products that have multidisciplinary, highly iterative, and simulation-driven design processes. It is shown that these high-level technical products, which are commonly outsourced to suppliers, commonly suffer from a long development lead time. The literature points to several research tracks including design automation and data-driven design with possible support. After studying the advantages and disadvantages of each track, a data-driven approachis chosen and studied through two case studies leading to two supporting tools that are expected to improve the development lead time in associated design processes. Feature extraction in CAD as a way to facilitate metamodeling is proposed as the first solution. This support uses the concept of the medial axis to find highly correlated features that can be used in regression models. As for the second supporting tool, an automated CAD script is used to produce a library of images associated with design variants. Dynamic relaxation is used to label each variant with its finite element solution output. Finally, the library is used to train a convolutions neural network that maps screenshots of CAD as input to finite element field answers as output. Both supporting tools can be used to create real-time prediction models in the early conceptual phases of the product development process to explore design space faster and reduce lead time and cost.
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- Arjomandi Rad, Mohammad, 1987, et al.
(författare)
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Datasets in design research: needs and challenges and the role of AI and GPT in filling the gaps
- 2024
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Ingår i: Proceedings of the Design Society. - 2732-527X. ; 4, s. 1919-1928
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Konferensbidrag (refereegranskat)abstract
- Despite the recognized importance of datasets in data-driven design approaches, their extensive study remains limited. We review the current landscape of design datasets and highlight the ongoing need for larger and more comprehensive datasets. Three categories of challenges in dataset development are identified. Analyses show critical dataset gaps in design process where future studies can be directed. Synthetic and end-to-end datasets are suggested as two less explored avenues. The recent application of Generative Pretrained Transformers (GPT) shows their potential in addressing these needs.
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| 6. |
- Arjomandi Rad, Mohammad, 1987, et al.
(författare)
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Image regression-based digital qualification for simulation-driven design processes, case study on curtain airbag
- 2023
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Ingår i: Journal of engineering design (Print). - : Taylor & Francis. - 0954-4828 .- 1466-1837. ; 34:1, s. 1-22
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Tidskriftsartikel (refereegranskat)abstract
- Today digital qualification tools are part of many design processes that make them dependent on long and expensive simulations, leading to limited ability in exploring design alternatives. Conventional surrogate modelling techniques depend on the parametric models and come short in addressing radical design changes. Existing data-driven models lack the ability in dealing with the geometrical complexities. Thus, to address the resulting long development lead time problem in the product development processes and to enable parameter-independent surrogate modelling, this paper proposes a method to use images as input for design evaluation. Using a case study on the curtain airbag design process, a database consisting of 60,000 configurations has been created and labelled using a method based on dynamic relaxation instead of finite element methods. The database is made available online for research benchmark purposes. A convolutional neural network with multiple layers is employed to map the input images to the simulation output. It was concluded that the showcased data-driven method could reduce digital testing and qualification time significantly and contribute to real-time analysis in product development. Designers can utilise images of geometrical information to build real-time prediction models with acceptable accuracy in the early conceptual phases for design space exploration purposes.
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| 7. |
- Arjomandi Rad, Mohammad, et al.
(författare)
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System properties to address the change propagation in product realization
- 2020
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Ingår i: Transdisciplinary engineering for complex socio-technical systems – Real-life applications. - Clifton, VA : IOS Press. - 9781643681108 - 9781643681115 ; , s. 343-352
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Konferensbidrag (refereegranskat)abstract
- Demanding markets and complex products are only some of the reasons that make changes and variations inevitable through different stages of product realization. From early phases of product development to downstream production phase, these changes or variations cause failure either directly or by propagating to other phases, triggering more fluctuations like the well-known butterfly effect. In this paper, first, the definition of changes in product realization will be reviewed and then different papers and their classification on change related system properties (illites) will be discussed and compared. It was argued that considering a system-level view, one could trace these propagations in the systems as a result of not being robust, flexible, or adaptable, etc. Some of the ambiguity in this semantic field demonstrated and most repeated definitions are identified as the unanimous and agreed-upon definitions in the literature. In the end, a historical comparison of the three identified properties presented. The results of this study help us to understand the multidisciplinary nature of these propagations and identify their stemming turbulent environment. This will be used as a foundation for forthcoming research either to prevent these propagations or utilize their attributes in the product realization.
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| 8. |
- Stolt, Roland, 1970-, et al.
(författare)
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Transiting Between Product Development and Production : How IT in Product Development and Manufacturing Integrate
- 2023
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Ingår i: IFIP Advances in Information and Communication Technology. - Cham : Springer. - 9783031251818 - 9783031251825 ; , s. 136-143
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Konferensbidrag (refereegranskat)abstract
- One crucial moment in product development is when all specifications of a product are ready, and the start of production is imminent. Companies very often have a milestone gate at this point where the development project is signed off and approved making sure that everything is ready and handing it over to the production department. This is a crucial moment involving checking a lot of information that has originated from different departments in the company. It can result in errors since the checking often is done manually and based on that staff check and report the results to a central function managing the transition. The situation is worsened by interoperability problems between different IT systems and databases used for different purposes in the company. In this paper it is examined how an automotive company currently is conducting the handover, gathering and checking all specifications before start of production. Risks of mistakes and unnecessary time loss are identified. In the paper it is discussed how the integration can be improved and the amount of manual work reduced. Results indicate that there is a potential for both saving time and reducing risk of error by automating parts of the handing over and integrating the IT systems and databases.
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