Selected Topics in Manufacturing

Shape memory polymers (SMPs) has recently gained popularity in the 3D printing field: the possibility to 3D print polymers capable to change their shape when triggered by a certain temperature, can lead to the fabrication of programmable structures. So far, the usage of solutions such as oven and warm water have been used to activate SMP, resulting in a lack of feasibility and difficult to be employed in real-life scenarios. In the present paper the authors propose a method to embed electrical nichrome-wires inside the 3D printed SMP during the fabrication process, in order to make the activation step easier, more feasible and faster. Several motions were reached when the 3D printed SMPs were activated, resulting appealing for the fabrication of soft robots. Moreover, complex structures made up of SMP material and flexible joint were also manufactured, proving that the proposed manufacturing method can be used to fabricate grippers and walking soft robots.

Aerosol Jet^® Printing (AJ^®P) is an additive manufacturing (AM) technique for the deposition of a functionalized jet on free-form substrates. AJ^®P is mainly exploited for 2D printed electronics, nevertheless, is gaining attention in the bioelectronic field. Few emerging studies have also established AJ^®P as a micro-AM 3D printing technique. In this context, the 3D AJ^®P process has not been deeply analysed yet. This work proposes an unique study of novel 3D AJ^® printed gold microstructures, as arrays of micropillars ≥40 µm, with aspect ratios ARs ≤9 and print times ≤10 min. Print parameters were investigated via a full factorial design against shape fidelity and resolution, using a layer-by-layer strategy. Specimens were thermally sintered, without any binding. Optical, electrical, and biocompatibility tests were conducted and a flexible 3D microelectrode array was printed as proof-of-concept. Future applications include in-vitro bioelectronics, thermoelectric, and batteries.

Additive manufacturing technologies can cover the needs for highly customized components characterized by complex shapes in a short lead time. Despite the benefits of AM processes, these techniques are generally characterized by a low-quality surface finish, one of the most important requirements in several industrial fields. Considering this aspect, it is important to define solutions able to improve the surface finish to benefit the low lead times and the elevated level of customization. This study aims to develop surface quality improvement techniques for metal material extrusion (metal-MEX) samples. Specifically, an investigation was carried out to improve the surface finish of AISI630 stainless steel samples fabricated by metal-ME using different approaches (e.g., thermal and mechanical). The techniques were defined avoiding overstressed components that could be damaged and evaluating the processing convenience of processing time.

Wire arc additive manufacturing (WAAM) is an additive technology with several advantages, such as a high deposition rate, the possibility to manufacture metallic materials, a very low incidence of porosity and excellent mechanical properties. However, there are challenges in WAAM, like the uncontrollable grain growth (due to the prolonged exposure to high temperatures) and the accumulation of impurities or decrease in toughness (due to preferred crystallographic orientation and the grain growth mechanism). These issues are relevant for many materials like steel, aluminium, titanium, and nickel alloys. This work aimed to use arc oscillation in steel that could break this unrestrained grain growth, resulting in a more refined grain structure. The components were characterised morphologically, geometrically, and microstructurally, and the oscillation resulted in microstructures that were equally or more refined than the base material.

One of the limitations of fused filament fabrication (FFF) in mass customisation is the long trial and error process required to optimise process parameters under frequent changes of geometries, materials and structural/mechanical requirements. Extrusion parameters may also need to be changed in-process, for example to address different requirements of skin and internal regions within the same part. This work explores the possibility of making a FFF machine capable of autonomous optimisation of extrusion parameters, currently for use in pre-process optimisation, but in future also applicable to in-process adaptive optimisation and control. Through a combination of machine learning and digital twinning, the proposed solution is able to automatically modify a part program optimising extrusion parameters to improve uniformity of widths of the extruded strands. The solution learns how to modify the part program using data from example depositions (tests runs) and simulation models. The proposed approach is demonstrated through the application to a test case.

Additive manufacturing (AM) has the potential to revolutionize the way products are designed and produced in a wide range of industries. However, ensuring the quality and reliability of AM parts remains a challenge, as defects can occur during the building process. In-situ monitoring is a promising approach for detecting and classifying these defects for in-process part qualification. In this paper, we present a novel approach for in-situ monitoring of laser powder bed fusion (LPBF) processes using a recoater-based imaging sensor and machine learning algorithms. The new sensor architecture is a recoater-mounted contact image sensor (CIS) and allows for high-resolution imaging of the build area during the recoating process, enabling the observation of a wide range of part and process-related defects. We demonstrate the effectiveness of using machine learning for image analysis on a series of experiments on a commercial AM system, showing significant improvements in defect detection accuracy compared to existing methods. Our results demonstrate the potential of the recoater-based sensor architecture for unlocking new capabilities for in-situ monitoring and quality control in powder bed-based AM processes.

The present study introduces an electrically assisted direct joining process for hybrid metal-polymer connections. The process consists of the adoption of an electrical current to heat the metal component, which is pressed against a thermoplastic polymer. Titanium grade 2 and Polyetheretherketone were selected for the preliminary testing campaign. An instrumented equipment was developed to control and measure the main process parameters such as the voltage and the current during the joining process. The investigation was carried out to determine the feasibility of the process. To this end, preliminary experimental tests were performed by varying the main process parameters. The metal surface's laser texturing was performed before joining to promote micromechanical interlocking. Quality assessment of the connections was carried out through single lap shear tests and fracture surface analysis.

Tool radial runout is an inevitable phenomenon which significantly affects the cutting conditions in a milling operation. Indeed, tool runout causes irregular spacing between cutter teeth creating uneven engagement conditions. This aspect may limit the accuracy and reliability of the predictive approaches dealing with important phenomena in milling such as chatter, surface errors and tool wear. For these predictions, a cutting force model, which includes tool runout, is essential, but it requires complex formulations which limit its application. This paper presents a simplified cutting force model for an endmill with generic geometry then adapts it to represent the effect of radial runout on a regular endmill. The model thus obtained expresses the cutting forces as a Fourier series considering the effect of tool runout on the cutting force frequency components, and it is easy to apply to other predictive models. The proposed formulations are validated, and an application is presented.

Shape memory (SM) polymer composite (PC) actuators have been manufactured by using carbon fibre reinforced (CFR) prepregs and by integrating flexible heaters. The smart device has the structure of a composite sandwich with CFR plies as external skins, an embedded heater and SMP layers in between. Small epoxy foam tablets were also inserted in the laminate centre to increase the maximum attainable deformation during the memory step. These foams were produced by a solid-state process. The sandwich consolidation was obtained in one moulding step. For comparison, a second CFR-SMPC actuator was manufactured without the SMPC foams, thus reducing the final laminate thickness. SM performances of the SMPC devices were evaluated by thermo-mechanical cycling in bending configuration. Memory, constrained-recovery and free-recovery tests were carried out. Shape fixity and shape recovery were extracted as well as recovery loads. Results show the optimal SM behaviour of the new sandwich architecture.

Reducing scrap is one of the key objectives of manufacturing companies to increase production efficiency and sustainability. Although many causes of scrap can be attributed to deviations at level of single processes, there are other causes inevitably related to dynamics at system level, as in presence of perishable material. In such situations the amount of time material waits in buffers, and therefore its level of degradation, is a consequence of the interaction among dynamics of the different production resources. This work presents an analytical model of a two-stage production system with perishable work in process. The model includes a control policy that modulates production capacity of parallel machines based on buffer and machines state, to reduce average waiting time and therefore scrap. Results from an industrial case in the semiconductor manufacturing sector show the usefulness of the policy in reducing scrap when the maximum waiting time of work in process is constrained.

Advances in Manufacturing of metal implants may offer solutions to several challenges. Considering the current state of bespoke manufactured implants alongside clinical and industrial perspectives, this review seeks to illuminate where key advances are being made in a laboratory setting and what is being done to translate them to use in future implants. Especially, additive manufacturing is a core business in producing customized implants but its application in industrial field is yet to be fully exploited. On the other side, sheet forming and laser processing are two main techniques for the fabrication of bespoke metal parts with high dimensional accuracy and surface finishing that can be integrated within a functional chain leading to clinical applications. The exploited processes are here presented, together with a focus on implant customization strategies and standardization processes, key factors for the industrialization of custom-built rather than mass-produced devices.

The ever-growing demand for electric vehicles in the world and Europe will result in a significant socio-economical change. The electrification changes the material types, usage, manufacturing, and vehicle design. The contemporary electric drives are being used in various vehicles, such as automobiles, drones, trains, airplanes, and ships. These vehicles will require a lower weight, an extended maximum range, and faster recharging as the number of vehicles in use increases. Compared to vehicles powered with combustion engines, fewer components will be placed with increased demand in flexible welding, heat treatment, cutting, trimming, and texturing applications. The need for rapid changes in the vehicle models and the variety of components will be resolved through highly digitalized, flexible, adaptable, and reliable manufacturing processes. From this point of view, laser-based manufacturing is an essential solution, placing this family of processes as the conventional method in electric vehicle manufacturing. Today, lasers are used in various applications, such as hairpin stripping and welding, cutting and texturing of Lithium-ion electrodes, welding of battery busbars, and cutting of composite materials. The rapid reduction of the costs of laser sources, optics, and components in the last decade facilitated the adoption of laser systems in electric vehicle manufacturing. Although laser technology has reached the required maturity, the system developers and the end-users still need to catch up with the pace of the growing demand in electric vehicle manufacturing. This white paper highlights the challenges and opportunities regarding the main laser-based manufacturing processes for electric vehicle production.

The widespread adoption of digital technologies in factories has resulted in the generation of a vast amount of data, which has the potential to enhance efficiency and effectiveness in the manufacturing industry. However, collecting and analyzing these data require approaches and tools to design and operate complex digital models and infrastructures, also requiring transversal competencies. The Digital Twin approach can be exploited to couple assets with their digital counterparts to support analyses and decisions. In particular, a Digital Twin can be associated with a product, a specific machine tool or process, a production system, or an entire factory. This paper focuses on the application of Digital Twins in factories, proposing a framework to identify data flows and relevant digital tools for applications throughout the different phases of the factory lifecycle. Despite the great potential, Digital Twin in manufacturing is still hindered by certain limitations. Therefore, by drawing upon relevant literature, we define and highlight the key challenges that need to be addressed. Finally, the framework and the challenges are exploited to characterize three case studies, which demonstrate the application of Digital Twins during the design and execution phases.

This document wants to provide an in-depth framework on the use of innovative joining technologies in the shipbuilding industry that must innovate both its own ship product and production process to maintain high levels of competitiveness, however, it wants also to attract the attention of the shipbuilders, because they often are reluctant to change, to stimulate them to innovation. After an introduction focused on both the impact and the evolution of the industry of European shipbuilding into the contest of the Blue Economy, a state-of-art is developed highlighting the progress in terms not only scientific but also in terms of design and application. Then, the document aims to identify the technological needs and the possible solutions also with the aid of the information provided by some companies such as Intermarine, Fincantieri and Caronte and Tourist.

Surface functionalization is emerging as one of the most promising methodologies for properly improving surfaces, especially for biomedical applications. The possibility to tune surface properties improving the prosthesis performance and their interaction with the human environment represents a challenging research area. The paper reports the most used surface functionalization for metallic biomaterials highlighting limitations and advantages of such technologies on the actual industrial panorama.