Computational Assessment of Orthopedic Implant Durability Using Finite Element Analysis

Finite Element Analysis (FEA) provides a rapid and cost-effective method to evaluate orthopedic implants. This research investigates the mechanical performance and long-term durability of a seven-hole SS 316L Basic Fragment Set (BFS) reconstruction plate designed for pelvic fractures. Adhering to ASTM standards, material properties were defined via tensile testing (ASTM E8), while static and fatigue analyses were performed using a displacement control method in a four-point bending test setup in SOLIDWORKS 2024 (ASTM F382). The static analysis predicted failure from plastic deformation at a force of 367 N, with a maximum stress of 621.92 MPa. The fatigue simulation predicted a lifespan of 483,754 cycles. To validate the simulation, these computational results were compared to experimental data, demonstrating high accuracy with deviations of only 3.34% for maximum force and 1.19% for fatigue life. These findings confirm that FEA is a highly reliable tool for predicting mechanical performance, enabling the orthopedic industry to optimize implant designs, enhance patient safety, and improve production efficiency.

Authors

Institutions

Publication Details

Journal
Advance Sustainable Science Engineering and Technology
Published
2025-07-19
DOI
https://doi.org/10.26877/77v9k615
Primary Topic
Orthopaedic implants and arthroplasty
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational Assessment of Orthopedic Implant Durability Using Finite Element Analysis

Rifky Ismail, Januar Parlaungan Siregar, Tezara Cionita, Ismoyo Haryanto et al.
Advance Sustainable Science Engineering and Technology
Orthopaedic implants and arthroplasty
article

Computational Assessment of Orthopedic Implant Durability Using Finite Element Analysis

Rifky Ismail, Januar Parlaungan Siregar, Tezara Cionita, Ismoyo Haryanto, Riondityo Soni Bagastomo
article en

Abstract

Finite Element Analysis (FEA) provides a rapid and cost-effective method to evaluate orthopedic implants. This research investigates the mechanical performance and long-term durability of a seven-hole SS 316L Basic Fragment Set (BFS) reconstruction plate designed for pelvic fractures. Adhering to ASTM standards, material properties were defined via tensile testing (ASTM E8), while static and fatigue analyses were performed using a displacement control method in a four-point bending test setup in SOLIDWORKS 2024 (ASTM F382). The static analysis predicted failure from plastic deformation at a force of 367 N, with a maximum stress of 621.92 MPa. The fatigue simulation predicted a lifespan of 483,754 cycles. To validate the simulation, these computational results were compared to experimental data, demonstrating high accuracy with deviations of only 3.34% for maximum force and 1.19% for fatigue life. These findings confirm that FEA is a highly reliable tool for predicting mechanical performance, enabling the orthopedic industry to optimize implant designs, enhance patient safety, and improve production efficiency.

Advance Sustainable Science Engineering and TechnologyVol. 7(3)
Universiti Malaysia Pahang Al-Sultan Abdullah (MY), Diponegoro University (ID), INTI International University (MY)
Universitas Diponegoro
Openalex Percentile: Top 70%
Orthopaedic implants and arthroplasty
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Computational Assessment of Orthopedic Implant Durability Using Finite Element Analysis — Rifky Ismail, Januar Parlaungan Siregar, et al. · Advance Sustainable Science Engineering and Technology (2025) | TGRS Research Map | TGRS