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    Sequential Design Process for Screening and Optimization of Robustness and Reliability Based on Finite Element Analysis and Meta-Modeling

    Source: Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 004::page 40902-1
    Author:
    Brix Nerenst, Tim
    ,
    Ebro, Martin
    ,
    Nielsen, Morten
    ,
    Bhadani, Kanishk
    ,
    Asbjörnsson, Gauti
    ,
    Eifler, Tobias
    ,
    Lau Nielsen, Kim
    DOI: 10.1115/1.4053074
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A new medical device can take years to develop from early concept to product launch. The long development process can be attributed to the severe consequences for the patient if the device malfunctions. As a result, three approaches are often combined to mitigate risks: failure modes and effects analysis (FMEA), simulation and modeling, and physical test programs. Although widely used, all three approaches are generally time consuming and have their shortcomings: The risk probabilities in FMEA’s are often based on educated guesses, even in later development stages as data on the distribution of performance is not available. Physical test programs are often carried out on prototype components from the same batch and, therefore, may not reveal the actual distribution of actual running performance. Finally, simulation and modeling are usually performed on nominal geometry—not accounting for variation—and only provide a safety factor against failure. Thus, the traditional use of safety factors in structural analysis versus the probabilistic approach to risk management presents an obvious misfit. Therefore, the aforementioned three approaches are not ideal for addressing the design engineer’s key question
     
    how should the design be changed to improve robustness and failure rates. The present study builds upon the existing robust and reliability-based design optimization (R2BDO) and adjusts it to address the aforementioned key questions using finite element analysis (FEA). The two main features of the presented framework are screening feasible design concepts early in the embodiment phase and subsequently optimizing the design’s probabilistic performance (i.e., reduce failure rates), while using minimal computational resources. A case study in collaboration with a medical design and manufacturing company demonstrates the new framework. The case study includes FEA contact modeling between two plastic molded components with 12 geometrical variables and optimization based on meta-modeling. The optimization minimizes the failure rate (and improves design robustness) concerning three constraint functions (torque, strain, and contact pressure). Furthermore, the study finds that the new framework significantly improves the component’s performance function (failure rate) with limited computational resources.
     
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      Sequential Design Process for Screening and Optimization of Robustness and Reliability Based on Finite Element Analysis and Meta-Modeling

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    contributor authorBrix Nerenst, Tim
    contributor authorEbro, Martin
    contributor authorNielsen, Morten
    contributor authorBhadani, Kanishk
    contributor authorAsbjörnsson, Gauti
    contributor authorEifler, Tobias
    contributor authorLau Nielsen, Kim
    date accessioned2022-05-08T09:30:36Z
    date available2022-05-08T09:30:36Z
    date copyright2/7/2022 12:00:00 AM
    date issued2022
    identifier issn1530-9827
    identifier otherjcise_22_4_040902.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285221
    description abstractA new medical device can take years to develop from early concept to product launch. The long development process can be attributed to the severe consequences for the patient if the device malfunctions. As a result, three approaches are often combined to mitigate risks: failure modes and effects analysis (FMEA), simulation and modeling, and physical test programs. Although widely used, all three approaches are generally time consuming and have their shortcomings: The risk probabilities in FMEA’s are often based on educated guesses, even in later development stages as data on the distribution of performance is not available. Physical test programs are often carried out on prototype components from the same batch and, therefore, may not reveal the actual distribution of actual running performance. Finally, simulation and modeling are usually performed on nominal geometry—not accounting for variation—and only provide a safety factor against failure. Thus, the traditional use of safety factors in structural analysis versus the probabilistic approach to risk management presents an obvious misfit. Therefore, the aforementioned three approaches are not ideal for addressing the design engineer’s key question
    description abstracthow should the design be changed to improve robustness and failure rates. The present study builds upon the existing robust and reliability-based design optimization (R2BDO) and adjusts it to address the aforementioned key questions using finite element analysis (FEA). The two main features of the presented framework are screening feasible design concepts early in the embodiment phase and subsequently optimizing the design’s probabilistic performance (i.e., reduce failure rates), while using minimal computational resources. A case study in collaboration with a medical design and manufacturing company demonstrates the new framework. The case study includes FEA contact modeling between two plastic molded components with 12 geometrical variables and optimization based on meta-modeling. The optimization minimizes the failure rate (and improves design robustness) concerning three constraint functions (torque, strain, and contact pressure). Furthermore, the study finds that the new framework significantly improves the component’s performance function (failure rate) with limited computational resources.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleSequential Design Process for Screening and Optimization of Robustness and Reliability Based on Finite Element Analysis and Meta-Modeling
    typeJournal Paper
    journal volume22
    journal issue4
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4053074
    journal fristpage40902-1
    journal lastpage40902-10
    page10
    treeJournal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 004
    contenttypeFulltext
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