Sequential Design Process for Screening and Optimization of Robust and Reliability Based on Finite Element Analysis and Meta-Modelling
Artikel i vetenskaplig tidskrift, 2022

A new medical device can take years to develop from early concept to product launch. 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. Thus, the traditional use of safety factors in structural analysis versus the probabilistic approach to risk management presents an obvious misfit. Therefore, the above 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 work builds upon the existing Robust and Reliability-Based Design Optimization (R2BDO) and adjusts it to address the key questions above 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 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 design's performance function (failure rate) with limited computational resources.

Virtual Prototyping

Multidisciplinary Optimization

Computer Aided Engineering

Data-Driven engineering

Computer Aided Design


Tim Brix Tim Brix Nerenst

Danmarks Tekniske Universitet (DTU)

Martin Ebro

Novo Nordisk

Morten Nielsen

Novo Nordisk

Kanishk Bhadani

Chalmers, Industri- och materialvetenskap, Produktutveckling

Gauti Asbjörnsson

Chalmers, Industri- och materialvetenskap, Produktutveckling

Tobias Eifler

Danmarks Tekniske Universitet (DTU)

Kim Lau Nielsen

Danmarks Tekniske Universitet (DTU)

Journal of Computing and Information Science in Engineering

1530-9827 (ISSN)

Vol. 22 4 040902


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