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Optimization of Environmentally Friendly Material Selection for Automotive Mechatronics Components Using LCA Data and Multi‑Criteria Decision Making (MCDM) Ibrahim, Fauzi; Marjuni, Teuku; Febrina, Rina; Oktarina, Devi; Natalina, Natalina; Ergantara, Rani Ismiarti; Sulistyaningrum, Diah Ayu Wulandari
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.8

Abstract

The automotive industry faces an increasing demand for sustainable material selection as mechatronic components become more widespread in electrified vehicles. However, data-driven material selection approaches that simultaneously integrate environmental, economic, and technical criteria without laboratory experiments remain underdeveloped. This study addresses this gap by developing a computational framework that combines Life Cycle Assessment (LCA) with a Multi-Criteria Decision-Making (MCDM) approach, specifically the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, using Analytical Hierarchy Process (AHP)–based weights. The framework enables a transparent and reproducible evaluation of environmentally friendly materials for automotive mechatronic components. A case study on an actuator housing evaluates seven material alternatives: Al 6061 (die-cast), recycled Al (die-cast), Mg AZ91 (die-cast), PA6-GF30 (injection), PBT-GF30 (injection), PA12 (SLS 3D print), and bio-based PBT-GF30 (injection). The criteria include total global warming potential (GWP), cumulative energy demand (CED), water use, recyclability, cost, mass, stiffness index, thermal conductivity, and supply risk. Results show that recycled aluminum achieves the highest ranking (closeness coefficient = 0.939), followed by Al 6061 (0.727) and Mg AZ91 (0.547). A Monte Carlo analysis with 1,000 iterations confirms that recycled aluminum consistently remains the best option with 100% robustness under varying weighting conditions. The proposed workflow is replication-ready and can be directly integrated with established LCA databases such as GREET, Ecoinvent, or EPD, enabling engineers to perform sustainable and quantitative material decisions using only data and computational analysis.
Life Cycle Assessment (LCA) of Natural Fiber Reinforced Polymer Composites for Automotive Interior Panels: A Comparative Study vs. Glass Fiber Composites Ibrahim, Fauzi
Jurnal Rekayasa Teknologi dan sains Vol 10, No 1 (2026): Jurnal Rekayasa, Teknologi, dan Sains
Publisher : Fakultas Teknik Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jrets.v10i1.24960

Abstract

The growing demand for lightweight and sustainable vehicles is accelerating the adoption of fiber reinforced polymer composites, including natural fiber reinforced polymer (NFRP) systems for interior components. However, environmental benefits are highly dependent on resin selection, manufacturing route, transport distances, and end of life scenarios. This study presents a cradle to grave Life Cycle Assessment (LCA) comparing NFRP and conventional glass fiber reinforced polymer (GFRP) for an automotive interior panel application. A functional unit is defined as one interior panel meeting equivalent stiffness and service life requirements, enabling fair comparison between materials with different fiber density and specific mechanical performance. Life cycle inventory data are compiled from peer reviewed literature and established LCA databases, covering raw material extraction (natural fibers and glass fibers), polymer matrix production, compounding and forming processes, use phase considerations (mass related fuel/energy penalties where applicable), and end of life scenarios including landfill, incineration with energy recovery, and emerging recycling pathways. Environmental impacts are quantified using midpoint indicators (e.g., global warming potential, cumulative energy demand, acidification, eutrophication, and human toxicity), and uncertainty is addressed via sensitivity analysis on key parameters such as fiber content, resin type (petro based vs. bio based), regional electricity mix, and transportation assumptions. The results are expected to identify dominant “hotspots” across the value chain and to clarify conditions under which NFRP offers measurable reductions in greenhouse gas emissions and energy demand relative to GFRP, while also highlighting trade offs related to land use, eutrophication, and end of life emissions. The findings provide design relevant guidance for material selection and process optimization toward lower impact composite interior parts aligned with circular economy strategies.