Concurrent Design and Multi-Objective Optimization of a HEXA Parallel Mechanism with Hybrid Control for Additive Manufacturing

Current additive manufacturing is limited by its Cartesian linear movements, leading to poor surface finish and weak layer bonding. This study proposes a multidirectional deposition approach using a HEXA parallel mechanism as an alternative to industrial robotic arms, which are costly and slow. However, designing and controlling HEXA systems present challenges due to their closed kinematic chains and highly nonlinear dynamics, requiring advanced computational modelling and simulation for effective implementation. Additionally, conventional designs treat structural and geometric considerations separately from control strategies, leading to suboptimal systems. This research introduces a golden-section approach for workspace determination, a hybrid control strategy which integrates differential flatness and sliding modes, a manipulability index that does not depend on the use of identical actuators, a torque requirement index, a non-dimensional error control metric, and a multi-objective decision index. The objective is to fine-tune the controller, maximize workspace and manipulability, and minimize control effort and error. Validation through simulations demonstrated satisfactory performance: a workspace of 0.095 m³ m 3 , with upper and lower link lengths of 0.344 m and 0.499 m, respectively; a control effort of 0.261 Nm; a control error of 4.2 $$%$$ % ; a damping ratio of 0.819; and a stabilization time of 0.338 s. Furthermore, this study highlights that the computationally integrated design of HEXA has potential for manufacturing applications, emphasizing the importance of robust control and optimized design. The hybrid controller, combined with metaheuristic optimization, provides a tool for developing complex multidirectional additive manufacturing systems with nonlinear dynamics. The proposed approach can be extended to other control mechanisms, enhancing stability and efficiency while advancing precision manufacturing systems.