The automotive manufacturing industry is experiencing major transformation due to the increasing adoption of electric vehicles alongside continued demand for internal combustion engine (ICE) platforms. Conventional assembly systems often rely on fixed production structures that limit manufacturing flexibility during rapid market transitions. This study presents a reconfigurable assembly architecture designed for concurrent ICE and electric drive unit (EDU) manufacturing within a unified production environment. The proposed framework integrates modular assembly zones, AI-assisted scheduling systems, IoT-based monitoring infrastructure, AGV-supported material flow coordination, predictive maintenance functions, and digital twin-assisted production control. The study evaluates production flexibility, workstation utilization, throughput stability, scheduling adaptability, and reconfiguration performance under multiple manufacturing demand conditions. Simulation-based analysis compares the proposed architecture with conventional fixed assembly systems during transitions between ICE-dominant and EDU-dominant production scenarios. Results indicate lower reconfiguration time, reduced assembly downtime, balanced workstation utilization, stable throughput performance, and improved material flow coordination during mixed powertrain manufacturing operations. The findings indicate that modular reconfigurable assembly structures combined with intelligent production management technologies can support flexible automotive manufacturing without complete assembly line reconstruction.
Md. Faisal Bin Shaikat (2026) studied this question.