## 1 Introduction  
The sustainable energy transition is currently one of the major challenges that are being addressed by the global scientific and industrial community. This requirement is pushing the development of novel solutions, such as the digitalization of industrial processes and the use of smart technology, with the goal of reducing material and energy waste [1]. Under these conditions, additive manufacturing (AM) in all of its forms is gaining popularity in a variety of fields because it allows for a significant reduction in required and wasted material through a variety of means, ranging from stock material reduction to the realization of free form topologically optimized components, due to the ability of these technologies to add material only where needed [2]. Eliminating unnecessary material from components is especially beneficial in industries where weight savings are essential, such as in the aerospace sector [3]. Furthermore, the optimized supply chain of AM technologies (i.e., the absence of models and the ability to easily realize one-of-a-kind parts) is a notable feature in the oil and gas sector, where very small batches of large components (typically realized by forging or casting) are common and a short lead time is frequently required [4]. Laser metal deposition (LMD) is an additive manufacturing process that uses thermal energy, specifically a laser beam, to melt the metal precursor (in the form of wire or powder)as it is supplied to the deposition area, resulting in a molten pool of liquid metal [5]. The mutual motion of the laser beam and the fed material on a tool path generated by CAM software on the base of a CAD file realizes the solid component. With LMD, high deposition rates are available, and support-free near-net shape components can be realized, making it an excellent option for technological transition in areas such as aerospace, oil and gas, and construction [6]. The ability to manufacture large components is related to the fact that the deposition head is mounted on a motion system that moves it, and it follows the defined tool path to realize the part. This motion system can be a robot or a computer numerical control (CNC) machine with multiple degrees of freedom [7; 8]. The choice between one motion system and the other may be difficult because of the many differences between the two configurations. In general, robots are more flexible than CNC machines because they have more degrees of freedom and may be used for a variety of tasks, but they are less accurate and precise (especially from the point of view of the trajectory between points) [9]. Robots have inferior geometrical accuracy and precision due to their extended cantilever kinematic structure, which must support the motors, brakes, and reduction gears of each axis, whereas the axes of cartesian CNC machines are stiffer and more robust and less influenced by vibrations [10]. Differences in the kinematic architecture of the two explored configurations lead to variations in trajectory and travel speed management. Indeed, due to the complicated kinematic chain of articulated robots, they may struggle to maintain the specified linear path with the given travel speed, resulting in a trajectory approximation or travel speed fluctuation [11]. This fact, when considered in the context of the discussed application, may result in the realization of inaccurate geometries as a result of an incorrect tool path or material shortage or accumulation as a result of speed increments or decrements, respectively [12; 13; 14]. CNC cartesian machine architectures, on the other hand, are isotropic in all reachable points and do not suffer from this issue. Because of this, machine builders typically propose LMD machines with CNC cartesian kinematics instead of articulated robot-based machines [15]. However, one major drawback is the increased cost of such systems, which can be about ten times more expensive than articulated robots [16]. For this reason, it is common to see articulated robot-based LMD machines used for research purposes.