# Special Issue \"Feature Review Papers in Mechanical Engineering\"
###### Abstract  
The study and advancement of crank-slide actuating mechanisms based on four-link structural groups are promising for the development of new designs of crank presses and other stamping and forging machines [1; 2]. These mechanisms address existing limitations such as slider distortion during forging compression and design restrictions for implementing slider dwells. Press rigidity is a crucial factor affecting the loading and unloading phases, especially in hot stamping processes, but increased rigidity may lead to higher metal consumption. To address dwell requirements, six-link mechanisms like crank-knee mechanisms are utilized. Hybrid presses with multiple degrees of freedom (DOF) are designed for specific applications, employing adjustable electric motors and servo motors for trajectory and cyclogram control. Various studies explore the synthesis, modeling, and kinematic analysis of hybrid mechanisms with five to seven rods, aiming to optimize stamping efficiency and energy distribution while minimizing manufacturing complexity and cost [3]. Industry 4.0 (14.0) has revolutionized various industrial sectors by promoting digital and cyber-physical technologies, reshaping manufacturing plants to produce parts efficiently and adaptively [4]. The customization of products and coping with market changes necessitate automation equipment and intelligent machines capable of task reconfiguration and collaboration. However, adapting to engineering changes while supporting different platforms poses challenges in maintaining robustness, safety, and reliability. Industrial Robots (IRs), pivotal in modern smart factories, perform diverse tasks but face limitations due to closed architecture and rigid programming [5]. Overcoming these limitations requires flexible, modular, and open architecture solutions. The advent of Industry 4.0, IoT, big data, and cloud computing has revolutionized manufacturing systems, enabling enhanced adaptability to internal and external changes. However, classical systems like dedicated manufacturing systems (DMSs), flexible manufacturing systems (FMSs), and cellular manufacturing systems (CMSs) have limitations in adjusting to modern industrial trends [6]. CMSs, employing group technology, organize machines and resources into cells for efficient production of part families, balancing flexibility and efficiency. Recent research focuses on improving CMS responsiveness to dynamic changes through dynamic designs, virtual models, reconfigurable machines, and robust approaches. Sustainability efforts aim to reduce energy consumption and emissions, aligning with EU targets and UN Sustainable Development Goals. These recent trends highlight the enhancement of CMS responsiveness and sustainability efforts to ensure efficient energy use amidst dynamic manufacturing landscapes [7]. Research on smart materials, especially shape memory alloys (SMAs), has surged since the late 1980s. SMAs regain their original shape when heated after deformation, offering advantages like compact size and high actuation force. Various review papers have explored SMA applications, including linear and rotary actuators, bi-directional motion, and robotic and morphing wing applications [8; 9]. These works focus uniquely on SMAactuators for structural systems, covering the vibration and stiffness control of flexible structures and shape control in aerospace engineering. It summarizes research from the past decade, detailing system characteristics, control methods, and potential applications. While magnetic shape memory alloys are excluded, the review offers insights into SMAs' roles in advancing structural control systems, omitting detailed modeling techniques to concentrate on practical applications and control algorithms [10]. Constructal theory emphasizes the significance of flow system configuration in their efficiency and survival. It proposes Constructal Design, where flow architecture is a design input, highlighting Sveteness (Sv) as a parameter to characterize the system's geometry [11].