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Additive manufacturing (AM) is a rapidly evolving manufacturing process, which refers to a set of technologies that add materials layer-by-layer to create functional components. AM technologies have received an enormous attention from both academia and industry, and they are being successfully used in various applications, such as rapid prototyping, tooling, direct manufacturing and repair, among others. AM does not necessarily imply building parts, as it also refers to innovation in materials, system and part designs, novel combination of properties and interplay between systems and materials. The most exciting features of AM are related to the development of radically new systems and materials that can be used in advanced products with the aim of reducing costs, manufacturing difficulties, weight, waste and energy consumption. It is essential to develop an advanced production system that assists the user through the process, from the computer-aided design model to functional components. The challenges faced in the research and development and operational phase of producing those parts include requiring the capacity to simulate and observe the building process and, more importantly, being able to introduce the production changes in a real-time fashion. This paper aims to review the role of robotics in various AM technologies to underline its importance, followed by an introduction of a novel and intelligent system for directed energy deposition (DED) technology.

AM presents intrinsic advantages when compared to the conventional processes. Nevertheless, its industrial integration remains as a challenge due to equipment and process complexities. DED technologies are among the most sophisticated concepts that have the potential of transforming the current material processing practices.

The objective of this paper is identifying the fundamental features of an intelligent DED platform, capable of handling the science and operational aspects of the advanced AM applications. Consequently, we introduce and discuss a novel robotic AM system, designed for processing metals and alloys such as aluminium alloys, high-strength steels, stainless steels, titanium alloys, magnesium alloys, nickel-based superalloys and other metallic alloys for various applications. A few demonstrators are presented and briefly discussed, to present the usefulness of the introduced system and underlying concept. The main design objective of the presented intelligent robotic AM system is to implement a design-and-produce strategy. This means that the system should allow the user to focus on the knowledge-based tasks, e.g. the tasks of designing the part, material selection, simulating the deposition process and anticipating the metallurgical properties of the final part, as the rest would be handled automatically.

This paper reviews a few AM technologies, where robotics is a central part of the process, such as vat photopolymerization, material jetting, binder jetting, material extrusion, powder bed fusion, DED and sheet lamination. This paper aims to influence the development of robot-based AM systems for industrial applications such as part production, automotive, medical, aerospace and defence sectors.

The presented intelligent system is an original development that is designed and built by the co-authors J. Norberto Pires, Amin S. Azar and Trayana Tankova.

The purpose of this paper is to present a novel methodology to produce a large boat hull with a foam additive manufacturing (FAM) process. To respond to shipping market needs, this new process is being developed. FAM technology is a conventional three-dimensional (3D) printing process whereby layers are deposited onto a high-pressure head mounted on a six-axis robotic arm. Traditionally, molds and masters are made with computer numerical control (CNC) machining or finished by hand. Handcrafting the molds is obviously time-consuming and labor-intensive, but even CNC machining can be challenging for parts with complex geometries and tight deadlines.

The proposed FAM technology focuses on the masters and molds, that are directly produced by 3D printing. This paper describes an additive manufacturing technology through which the operator can create a large part and its tools using the capacities of this new FAM technology.

The study shows a comparison carried out between the traditional manufacturing process and the additive manufacturing process, which is illustrated through an industrial case of application in the manufacturing industry. This work details the application of FAM technology to fabricate a 2.5 m boat hull mold and the results show the time and cost savings of FAM in the fabrication of large molds.

Finally, the advantages and drawbacks of the FAM technology are then discussed and novel features such as monitoring system and control to improve the accuracy of partly printed are highlighted.

This paper aims to investigate the additive manufacturing (AM) approach of a spatial complex curve feature (SCCF, mapped from two-dimensional nonuniform rational B-splines [2D-NURBS] curve) on a complex surface based on a serial robot using plasma built-up welding, and lays a foundation for plasma AM SCCFs on complex surfaces by combining the NURBS theory with the serial robotic kinematics.

Combining serial robotic kinematics and NURBS theory, a SCCF mapped from a square-like 2D-NURBS curve is prepared on a predefined complex NURBS surface using serial robotic plasma AM. The interpolation points C (ui) on the square-like 2D-NURBS curve are obtained using the equi-chord length interpolation method, and mapped on a predefined NURBS surface to get mapped points S (ui, vj). The homogeneous transformation matrix T = [n o a S (ui, vj)] of the plasma torch is calculated using the mapped points S (ui, vj) and the designated posture [n o a]. Using the inverse kinematics of the serial robot, the joint vector θ of the serial robot can be computed. After that, the AM programs are generated and transferred into the serial robotic controller and carried out by the serial robot of Motoman-UP6. The 2D-NURBS curve (square-like) is considered as AM trajectory planning curve, while its corresponding SCCF mapped from the 2D-NURBS curve as AM trajectory.

Simulation and experiments show that the preparation of SCCF (mapped from 2D-NURBS curve) on complex NURBS surface using robotic plasma AM is feasible and effective.

A SCCF mapped from a 2D-NURBS curve is prepared on a complex NURBS surface using the serial robotic plasma AM for the first time. It provides a theoretical and technical basis for plasma AM to produce SCCFs on complex surfaces. With the increasing demand for surface remanufacturing of complex parts, the serial robotic plasma AM of SCCFs on complex NURBS surfaces has a broad application prospect in aero-engine components, high-speed rail power components, nuclear industry components and complex molds.

3D printing technology has the characteristics of fast forming and low cost and can manufacture parts with complex structures. At present, it has been widely used in various manufacturing fields. However, traditional 3-axis printing has limitations of the support structure and step effect due to its low degree of freedom. The purpose of this paper is to propose a robotic 3D printing system that can realize support-free printing of parts with complex structures.

A robotic 3D printing system consisting of a 6-degrees of freedom robotic manipulator with a material extrusion system is proposed for multi-axis additive manufacturing applications. And the authors propose an approximation method for the extrusion value E based on the accumulated arc length of the already printed points, which is used to realize the synchronous movement between multiple systems. Compared with the traditional 3-axis printing system, the proposed robotic 3D printing system can provide greater flexibility when printing complex structures and even realize curved layer printing.

Two printing experiments show that compared with traditional 3D printing, a multi-axis 3D printing system saves 47% and 79% of materials, respectively, and the mechanical properties of curved layer printing using a multi-axis 3D printing system are also better than that of 3-axis printing.

This paper shows a simple and effective method to realize the synchronous movement between multiple systems so as to develop a robotic 3D printing system that can realize support-free printing and verifies the feasibility of the system through experiments.

Most of the 3D printing machines do not comply with the requirements of on-site, large-scale multi-story building construction. This paper aims to propose the conceptualization of a tower crane (TC)-based 3D printing controlled by artificial intelligence (AI) as the first step towards a large 3D printing development for multi-story buildings. It also aims to overcome the most important limitation of additive manufacturing in the construction industry (the build volume) by exploiting the most important machine used in the field: TCs. It assesses the technology feasibility by investigating the accuracy reached in the printing process.

The research is composed of three main steps: firstly, the TC-based 3D printing concept is defined by proposing an aero-pendulum extruder stabilized by propellers to control the trajectory during the extrusion process; secondly, an AI-based system is defined to control both the crane and the extruder toolpath by exploiting deep reinforcement learning (DRL) control approach; thirdly the proposed framework is validated by simulating the dynamical system and analysing its performance.

The TC-based 3D printer can be effectively used for additive manufacturing in the construction industry. Both the TC and its extruder can be properly controlled by an AI-based control system. The paper shows the effectiveness of the aero-pendulum extruder controlled by AI demonstrated by simulations and validation. The AI-based control system allows for reaching an acceptable tolerance with respect to the ideal trajectory compared with the system tolerance without stabilization.

In related literature, scientific investigations concerning the use of crane systems for 3D printing and AI-based systems for control are completely missing. To the best of the authors’ knowledge, the proposed research demonstrates for the first time the effectiveness of this technology conceptualized and controlled with an intelligent DRL agent.

The results provide the first step towards the development of a new additive manufacturing system for multi-storey constructions exploiting the TC-based 3D printing. The demonstration of the conceptualization feasibility and the control system opens up new possibilities to activate experimental research for companies and research centres.

Additive manufacturing (AM) technologies have recently turned into a mainstream production method in many industries. The adoption of new manufacturing scenarios led to the necessity of cross-disciplinary developments by combining several fields such as materials, robotics and computer programming. This paper aims to describe an innovative solution for implementing robotic simulation for AM experiments using a robot cell, which is controlled through a system control application (SCA).

For this purpose, the emulation of the AM tasks was executed by creating a robot working station in RoboDK software, which is responsible for the automatic administration of additive tasks. This is done by interpreting gcode from the Slic3r software environment. Posteriorly, all the SCA and relevant graphical user interface (GUI) were developed in Python to control the AM tasks from the RoboDK software environment. As an extra feature, Slic3r was embedded in the SCA to enable the generation of gcode automatically, without using the original user interface of the software. To sum up, this paper adds a new insight in the field of AM as it demonstrates the possibility of simulating and controlling AM tasks into a robot station.

The purpose of this paper is to contribute to the AM field by introducing and implementing an SCA capable of executing/simulating robotic AM tasks. It also shows how an advanced user can integrate advanced simulation technologies with a real AM system, creating in this way a powerful system for R&D and operational manufacturing tasks. As demonstrated, the creation of the AM environment was only possible by using the RoboDk software that allows the creation of a robot working station and its main operations.

Although the AM simulation was satisfactory, it was necessary to develop an SCA capable of controlling the whole simulation through simple commands instructed by users. As described in this work, the development of SCA was entirely implemented in Python by using official libraries. The solution was presented in the form of an application capable of controlling the AM operation through a server/client socket connection. In summary, a system architecture that is capable of controlling an AM simulation was presented. Moreover, implementation of commands in a simple GUI was shown as a step forward in implementation of modern AM process controls.

Robotic wire and arc additive manufacturing (RWAAM) is becoming more and more popular for its capability of fabricating metallic parts with complicated structure. To unlock the potential of 6-DOF industrial robots and improve the power of additive manufacturing, this paper aims to present a method to fabricate curved overhanging thin-walled parts free from turn table and support structures.

Five groups of straight inclined thin-walled parts with different angles were fabricated with the torch aligned with the inclination angle using RWAAM, and the angle precision was verified by recording the growth of each layer in both horizontal and vertical directions; furthermore, the experimental phenomena was explained with the force model of the molten pool and the forming characteristics was investigated. Based on the results above, an algorithm for fabricating curved overhanging thin-walled part was presented and validated.

The force model and forming characteristics during the RWAAM process were investigated. Based on the result, the influence of the torch orientation on the weld pool flow was used to control the pool flow, then a practical algorithm for fabricating curved overhanging thin-walled part was proposed and validated.

Regarding the fabrication of curved overhanging thin-walled parts, given the influences of the torch angles on the deposited morphology, porosity formation rate and weld pool flow, the flexibility of 6-DOF industrial robot was fully used to realize instant adjustment of the torch angle. In this paper, the deposition point and torch orientation of each layer of a robotic fabrication path was determined by the contour equation of the curve surface. By adjusting the torch angle, the pool flow was controlled and better forming quality was acquired.

With the development of 3D printing or additive manufacturing (AM), curved layer fused deposition modeling (CLFDM) has been researched to cope with the flat layer AM inherited problems, such as stair-step error, anisotropy and the time-cost and material-cost problems from the supporting structures. As one type of CLFDM, cylindrical slicing has obtained some research attention. However, it can only deal with rotationally symmetrical parts with a circular slicing layer, limiting its application. This paper aims to propose a ray-based slicing method to increase the inter-layer strength of flat layer-based AM parts to deal with more general revolving parts.

Specifically, the detailed algorithm and implementation steps are given with several examples to enable readers to understand it better. The combination of ray-based slicing and helical path planning has been proposed to consider the nonuniform path spacing between the adjacent paths in the same curved layer. A brief introduction of the printing system is given, mainly including a 3D printer and the graphical user interface.

The preliminary experiments are successfully conducted to verify the feasibility and versatility of the proposed and improved slicing method for the revolving thin-wall parts based on a rotary 3D printer.

This research is early-stage work, and the authors are intended to explore the process and show the initial feasibility of ray-based slicing for revolving thin-wall parts using a rotary 3D printer. In general, this research provides a novel and feasible slicing method for multiaxis rotary 3D printers, making manufacturing revolving thin-wall and complex parts possible.

This paper aims to present a multi-axis additive robot manufacturing system (ARMS) and demonstrate its beneficial capabilities.

ARMS was constructed around two robot arms and a fused filament fabrication (FFF) extruder. Quantitative experiments are conducted to investigate the effect of printing at different orientations with respect to gravity, the effect of dynamically changing build orientation with respect to the build tray when printing overhanging features, the effect of printing curved parts using curved, conformal layers. These capabilities are combined to print an integrated demonstrator showing potential practical benefits of the system.

Orientation with respect to gravity has no effect on print quality; dynamically changing build orientation allows overhangs up to 90° to be cleanly printed without support structures; printing an arch with conformal layers significantly increases its strength compared to conventional printing.

The challenge of automatic slicing algorithms has not been addressed for multi-axis printing. It is shown that ARMS could eventually enable printing of fully-functional prototypes with embedded components.

This work is the first to prove that the surface roughness of an FFF part is independent of print orientation with respect to gravity. The use of two arms creates a novel system with more degrees of freedom than existing multi-axis printers, enabling studies on printing orientation relationships and printing around inserts. It also adds to the emerging body of multi-axis literature by verifying that curved layers improve the strength of an arch which is steeply curved and printed with the nozzle remaining normal to the curvature.