Applied Finite Element Methods (FEM) in Industrial Engineering: A Review

Abstract

Finite Element Methods (FEM) have revolutionized industrial engineering by providing accurate computational models for structural analysis, thermal simulations, fluid dynamics, and material behavior predictions. The application of FEM has enhanced efficiency, reliability, and cost-effectiveness in industries such as aerospace, automotive, civil engineering, and manufacturing. By breaking down complex geometries into smaller finite elements, FEM enables engineers to analyze stress distribution, deformation, fatigue, and failure mechanisms under varying loading conditions.

This review explores the evolution, principles, and various applications of FEM in industrial engineering, detailing its role in optimizing mechanical design, improving product lifecycle assessment, and enhancing predictive maintenance strategies. It highlights key advancements in computational techniques, including adaptive meshing, high-performance computing (HPC), and cloud-based simulations, which have significantly increased computational speed and accuracy. Additionally, the integration of FEM with artificial intelligence (AI) and machine learning (ML) has facilitated automated model generation, real-time simulation adjustments, and enhanced design optimization.

Despite its numerous benefits, challenges such as computational complexity, high processing power requirements, numerical instability, and implementation costs remain critical concerns. The review also discusses emerging trends such as digital twin technology, quantum computing for FEM, and AI-driven model reduction techniques, which aim to address these limitations and further expand the applicability of FEM in industrial engineering. As industries continue to evolve toward smart manufacturing and Industry 4.0, FEM will remain a cornerstone in engineering analysis, driving innovation and efficiency in modern industrial applications.