Highlights
- •The optimum plate model was designed as an alternative to the conventional plate.
- •Proposed approach significantly reduced computation time.
- •Higher reliability for the optimum plate was achieved.
- •Stiffness of the fixation plate was significantly reduced.
Abstract
Background
Due to high stiffness, metal fixation plates are prone to stress shielding of the
peri-prosthetic bones, leading to bone loss. Therefore, it has become important to
design implants with reduced rigidity but increased load-carrying capacity. Considering
the uncertainties in the parameters affecting the implant-bone structure is critical
in making more reliable implant designs. In this study, a Response Surface Method
based Reliability-based Topology Optimization approach was proposed to design a fixation
plate for humerus fracture having less stiffness than the conventional plate.
Methods
The design of the fixation plate was described as an Reliability-based Topology Optimization
problem in which the probabilistic constraint was replaced with a meta-model generated
using the Kriging method. The artificial humerus bone model was scanned, and the 3D
simulation model was used in the finite element analysis required in the solution.
The optimum plate was manufactured using Selective Laser Melting. Both designs were
experimentally compared in terms of rigidity.
Findings
The volume of the conventional plate was reduced from 2512.5 mm3 to 1667.3 mm3; nevertheless, the optimum plate had almost one-third less rigidity than the conventional
plate. The probability of failure of the conventional plate was computed as 0.994.
However, this value was almost half for the optimum fixation plate.
Interpretation
The studies showed that the new fixation plate design was less rigid but more reliable
than the conventional one. The computation time required to have the optimum plate
was reduced by one-tenth by applying the Response Surface Method for the Reliability-based
Topology Optimization problem.
Graphical abstract
Graphical Abstract
Keywords
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Article info
Publication history
Published online: September 15, 2022
Accepted:
September 12,
2022
Received:
July 19,
2022
Identification
Copyright
© 2022 Elsevier Ltd. All rights reserved.
