Optimizing Lightweight Automotive Connecting Rods Through Integrated Reverse Engineering and Lattice-Based Topology Methods

This study introduces an integrated, reverse-engineering-driven framework for optimizing automotive connecting rods under real-world industrial constraints. The geometric characteristics and material composition of a legacy component were experimentally characterized using high-resolution 3D scanning (Artec Spider Studio 16) and spectroscopy. The resulting data were incorporated into the optimization workflow. Computer-aided design tools, including SolidWorks 2022® Premium 2022 × 64 (Dassault Systèmes SolidWorks Corporation, Waltham, MA, USA) and Geomagic Design X 2022 (3D Systems, Rock Hill, SC, USA), captured precise geometry, while spectroscopy confirmed cast iron as the base material. An upgrade to structural steel is proposed, offering the potential for improved strength-to-weight performance. Although reverse engineering and topology optimization are well-established, previous studies have largely focused on idealized models and unconstrained domains. ANSYS Workbench 2022 R1 (ANSYS Inc., Canonsburg, PA, USA) topology optimization is constrained to preserve functional interfaces and manufacturability. Motivated by the demand for lightweight automotive solutions in the Middle East, this workflow achieves 2.63% mass reduction and an estimated 6.6% cost savings based on prior benchmarks. Incorporating the Octet lattice structure (nTopology, 2022 (nTopology Inc., New York, NY, USA)) further improves performance, yielding a 6.4% mass reduction and a 16% cost reduction. The optimized design is considered a promising candidate for future additive manufacturing and Industry 4.0 implementation. This preliminary procedure provides a transferable template for redesign, static evaluation, and experimental validation of legacy components, bridging the gap between academic research and industrial practice.

Authors

Institutions

Publication Details

Journal
Eng—Advances in Engineering
Published
2026-09-01
DOI
https://doi.org/10.3390/eng7090443
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Lightweight Automotive Connecting Rods Through Integrated Reverse Engineering and Lattice-Based Topology Methods

Mohamed A. Daha, Dehong Huo, May M. Youssef, Islam Shyha et al.
Eng—Advances in Engineering
Topology Optimization in Engineering
article

Optimizing Lightweight Automotive Connecting Rods Through Integrated Reverse Engineering and Lattice-Based Topology Methods

Mohamed A. Daha, Dehong Huo, May M. Youssef, Islam Shyha, Mohamed Elkholy
article en

Abstract

This study introduces an integrated, reverse-engineering-driven framework for optimizing automotive connecting rods under real-world industrial constraints. The geometric characteristics and material composition of a legacy component were experimentally characterized using high-resolution 3D scanning (Artec Spider Studio 16) and spectroscopy. The resulting data were incorporated into the optimization workflow. Computer-aided design tools, including SolidWorks 2022® Premium 2022 × 64 (Dassault Systèmes SolidWorks Corporation, Waltham, MA, USA) and Geomagic Design X 2022 (3D Systems, Rock Hill, SC, USA), captured precise geometry, while spectroscopy confirmed cast iron as the base material. An upgrade to structural steel is proposed, offering the potential for improved strength-to-weight performance. Although reverse engineering and topology optimization are well-established, previous studies have largely focused on idealized models and unconstrained domains. ANSYS Workbench 2022 R1 (ANSYS Inc., Canonsburg, PA, USA) topology optimization is constrained to preserve functional interfaces and manufacturability. Motivated by the demand for lightweight automotive solutions in the Middle East, this workflow achieves 2.63% mass reduction and an estimated 6.6% cost savings based on prior benchmarks. Incorporating the Octet lattice structure (nTopology, 2022 (nTopology Inc., New York, NY, USA)) further improves performance, yielding a 6.4% mass reduction and a 16% cost reduction. The optimized design is considered a promising candidate for future additive manufacturing and Industry 4.0 implementation. This preliminary procedure provides a transferable template for redesign, static evaluation, and experimental validation of legacy components, bridging the gap between academic research and industrial practice.

Eng—Advances in EngineeringVol. 7(9)
Edinburgh Napier University (GB), University of Business and Technology (SA), Alexandria University (EG), Newcastle University (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Topology Optimization in Engineering
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.