Certification of the designs of medical devices requires decisions to be made based on uncertainty. This is true whether the designer is basing the decision on information derived from empirical tests or computational simulations. Design of experiments (DoE) and sensitivity analysis (SA) can be used in both empirical testing and computational simulation to evaluate uncertainty. DoE and SA can be prohibitively expensive for empirical testing if more than just a few parameters are tested. And testing at the statistical limits of the parameters is seldom possible. Because computational simulations are often orders of magnitude less costly than empirical tests, they offer the possibility of fully examining the design space out to all conceivable limits. This provides the data needed to better understand the effect of uncertainty and the probability that a design will meet its desired function over its intended lifetime. Computational simulation allows for risk based designs with increased...
Uncertainty Management in Computational Simulations of Medical Devices1
- Views Icon Views
- Share Icon Share
- Search Site
Dey, A., Kulkarni, S., Mahadevan, S., Tryon, R. G., and Krishnan, G. (September 1, 2015). "Uncertainty Management in Computational Simulations of Medical Devices." ASME. J. Med. Devices. September 2015; 9(3): 030954. https://doi.org/10.1115/1.4030598
Download citation file: