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Complex precision components are integral to many sectors, straddling both military and civilian applications. These include aerospace telescopes, infrared thermal imaging systems, artificial intelligence, semiconductor chip lithography, medical imaging apparatus, and avant-garde communication technologies. These intricate precision components have become vital elements of the aforementioned optical systems, characterized by a wide range of extensive requirements totaling in the tens of millions. Within the realm of computer controlled optical surfacing (CCOS), high-efficiency bonnet polishing (BP) and high-precision magnetorheological finishing (MRF) are two compliant polishing methods with distinct advantages, extensively applied to ultra-precision machining of complex curved surface components. However, the bonnet polishing tool is prone to wear, the tool influence function is unstable, and the control process is complicated. The material removal efficiency of MRF is low; it easily introduces mid-spatial frequency (MSF) errors, and improving the performance of the magnetorheological fluid (MR fluid) is challenging. Therefore, summarizing these two techniques is essential to enhance the application of compliant polishing methods. The paper begins by examining the unique strengths of both technologies and then explores the potential for their integrated application. The paper then provides a detailed introduction to the origin, principles, equipment, and applications of BP. Next, the paper outlines the research progress of key technologies, including modeling of the tool influence function (TIF), management of MSF errors, and the wear of the bonnet tool within the realm of BP technology. Following that, the development history, technical principles, equipment, types, and compound methods of MRF are presented. Then, the research progress of several key technologies, such as modeling of TIF, controlling MSF error, and the preparation of MR fluid in the field of MRF technology, are reviewed. Lastly, the paper provides a summary and outlook for the two technologies, such as further in-depth study of the material removal mechanism and the suppression method of the edge effect in BP, a further in-depth study of methods to improve the material removal rate, and MSF error suppression methods in MRF. [ABSTRACT FROM AUTHOR]

Within the context of reducing the environmental impact generated by the current generation, a constant challenge for the automotive industry is to produce vehicles with the lowest possible environmental impact. In this context, in order to reduce vehicle weight and, consequently, reduce fuel consumption and emissions of gases harmful to the environment, the automotive industries have been using advanced high-strength steels. These steels make it possible to reduce thickness without losing mechanical strength and, therefore, without compromising passenger safety. Among these steels, 22MnB5 steel stands out. Among the welding processes used to weld steel sheets, electrical resistance spot welding is the most widely used joining technique in the automotive industry. The main reasons for its wide application are that it is a process in which no material addition is required and it has a high processing speed and low processing costs. In this context, this study proposes a bibliometric and systematic review of electrical resistance spot welding of 22MnB5 steel. The main objective of this study was to identify current research trends and impacts, along with a comprehensive revision. The research was carried out using the Proknow-C method. A bibliographic portfolio of 50 articles was compiled. The bibliometric analysis revealed that articles related to this topic increased substantially between 2016 and 2023 compared to previous years. The systematic evaluation of the papers in the bibliographic portfolio made it possible to identify aspects such as the research problems addressed, the materials and methodologies used, the results evaluated, and the research gaps. It was found that most of the studies focused on the weldability and mechanical performance characteristics of similar two-plate joints with an average thickness of 1.5 mm and Al-Si coatings. Finally, this article provides a comprehensive overview of the research on electric resistance spot welding of 22MnB5 steel and can provide guidance for future studies to improve the process. [ABSTRACT FROM AUTHOR]

Ultrasonic-assisted grinding (UAG) can effectively reduce the grinding force and improve the machining quality of carbon fiber-reinforced ceramic matrix composites (C/SiC) due to its excellent machining performance. Many researches have shown that the machining performance of UAG is closely related to the kinematic trajectory characteristics of the abrasive grains, so the surface morphology of diamond grinding wheels with various process preparations has an important influence on the grinding quality. In this paper, to investigate the performance of UAG of C/SiC composites with diamond grinding wheels prepared by different processes, UAG experiments were carried out on C/SiC composites using diamond grinding wheels prepared by brazing and electroplating processes. The trajectories of the abrasive grains and the maximum undeformed chip thicknesses with different abrasive grain protrusion heights were analyzed and the impact of the two diamond grinding wheels and the grain mesh size on the grinding force, surface roughness, and surface morphology were comparatively investigated. The results indicated that the grinding force and surface roughness obtained by brazed grinding wheels were reduced by 13 ~ 36.05% and 5.95 ~ 19.3% compared with electroplated diamond wheels at 240#, respectively. The brazed grinding wheels could improve the grinding surface morphology to a certain extent. However, the surface roughness value fluctuated with the increase of abrasive grain size. Additionally, the protrusion height of the abrasive grain of the brazed diamond wheels is more favorable for the UAG effect and the grinding wheels are less prone to clogging. [ABSTRACT FROM AUTHOR]

This paper introduces an approximate grinding method (AGM) and tooth flank deviation correction strategies for helical face gears (HFGs) generated by grinding worm, addressing the issue of singularities on the grinding worm thread surface that hinders HFGs grinding properly. Firstly, the tooth flanks of the face gear and grinding worm are derived, and singularities on the grinding worm are determined. Then, based on the grinding generation theory of HFGs, the AGM is proposed to solve the challenge of grinding HFGs with a large helix angle. Next, the tooth flank deviation of HFG generated by the grinding worm with the AGM is investigated; meanwhile, the tooth contact pattern and transmission error analysis are conducted. In addition, the correction method of the HFG tooth flank deviation is researched. Finally, a grinding experiment is performed and demonstrates the validity of the theoretical analysis of the AGM. [ABSTRACT FROM AUTHOR]

Titanium alloy milling is prone to burrs at the edges of the workpiece, which can negatively affect surface integrity and dimensional accuracy, and even lead to part scrap. Ultrasonic vibration–assisted milling technology can effectively inhibit burr generation and improve machining quality. However, the research of ultrasonic vibration–assisted milling on burr inhibition is not clear, so this paper establishes a mathematical model of ultrasonic vibration vertical milling titanium alloy top burr size based on the chip deformation process and specifically analyses the effect of ultrasonic machining parameters on burr through experiments. The experimental results show that the depth of cut has the greatest influence on the burr size, and the ultrasonic vibration has the second greatest influence on the burr. The cutting force and the burr size on both sides of the groove show a trend of "decrease and then increase" with the increase of ultrasonic amplitude. When the ultrasonic amplitude was 3 µm, the cutting forces Fx and Fy were reduced by 34.42% and 31.36%, respectively, and the heights and widths of the burrs on the up milling side and on the down milling side were reduced by 75.49%, 44.33% and 89.16%, 47.82%, respectively, when comparing with no ultrasonic machining. The longitudinal-torsional ultrasonic vibration converted the large piled-up, rolled-up, and serrated burrs into intermittent, small-sized flocculent burrs, which significantly improved the burr morphology and weakened the serrated characteristics of the chips. [ABSTRACT FROM AUTHOR]

Rivet connection is one of the most important connection technologies. The main factors affecting the rivet-forming quality of riveted structures are squeezing force, squeezing velocity, and materials of rivets and plates, which significantly impact the damage and failure of riveted holes in riveted structures. This paper provides a detailed study of the rivet-forming quality of riveted structures under different dynamic loads. A theoretical analysis method for the nonlinear dynamic plastic behavior of riveted structures is proposed to predict and investigate the rivet-forming quality of riveted structures under different squeezing forces, velocities, and materials. The proposed theoretical analysis method for the rivet-forming quality of riveted structures is conducted using the explicit dynamics method. Furthermore, the nonlinear dynamic plasticity theory method and nonlinear explicit dynamics model calculation results of riveted structures are compared with measured and Ultra Plus field scanning electron microscope scanning values. The results confirm the accuracy of the nonlinear dynamic plasticity theory method for riveted structures. In addition, the effects of different squeezing forces, velocities, rivet material, and plate material properties on the rivet-forming quality of riveted structures are also studied. This paper proposes a theoretical analysis method for the rivet-forming quality of riveted structures, providing an optimal squeezing force and velocity for rivet hole damage and rivet failure under different rivet and plate materials. [ABSTRACT FROM AUTHOR]

The cutting subsurface plastic deformation layer of titanium alloys has a serious influence on fatigue performance. Hence, it is necessary to establish a predicting model of the depth of subsurface plastic deformation. However, empirical models are difficult to be applied for different cutting methods and are controlled by various cutting parameters. This paper establishes an analytical model for predicting the depth of subsurface plastic deformation based on cutting force. In this case, as long as the cutting force is known, the analytical model can be used to predict the depth of subsurface plastic deformation layer for various cutting conditions. In experiments, the depth of subsurface plastic deformation was measured by using a scanning electron microscope (SEM) and electron back-scatter diffraction (EBSD). The measured and predicted values are closed, and the average prediction error is only 16.01%. Therefore, the analytical model is reliable and useful to predict the depth of subsurface plastic deformation during cutting titanium alloys. This study will have an important application value to control the depth of subsurface plastic deformation to improve fatigue performance. [ABSTRACT FROM AUTHOR]

Laser-based powder bed fusion of metals (PBF-LB/M) is an additive manufacturing process enabling the fabrication of parts with highly complex and customizable geometries, enhanced strength-to-weight properties, and minimized material waste. Despite its unique capabilities, PBF-LB/M needs research and innovation efforts to enhance process dynamics and product quality, as well as to broaden its adoption in high-value industrial sectors, such as aerospace and biomedical. In this context, in-process monitoring solutions and post-process part quality evaluations are fundamental to improving the process towards sustainable, first-time-right, and zero-defect production. This paper describes a novel building plate concept for metal laser powder fusion, whose characteristics were specifically designed to enable and improve the performances of in-process monitoring and high-resolution X-ray computed tomography (CT) measurements. In particular, the plate features markers for perspective correction in off-axis optical monitoring and dismountable inserts with machined geometrical elements to be used for the precise alignment between high-resolution CT reconstructions, in-process gathered data, and building volume geometry. The plate capabilities were demonstrated through examples related to in-process monitoring and post-process X-ray CT measurements. [ABSTRACT FROM AUTHOR]

The cooling process of a hot rolled strip on the run-out table (ROT) mainly determines the microstructure and mechanical properties of the final product; therefore, a method of investigation that helps companies follow the optimum cooling scenario is a profound issue. This paper develops a 2D finite element model based on industrial data that predicts the cooling pattern of hot rolled strips, with the potential to be formulated for steel grades dealing with complex boundary conditions, flexible to be applied for any cooling table. Meanwhile, this model investigates the thermal behavior of strips facing different heat transfer mechanisms in the full-scale ROT of Mobarakeh Steel Company (MSC). Moreover, coiling temperature (CT) and cooling pattern are validated through experimental data obtained from the Evraz hot rolling mill. Regarding the simulation of various header configurations, each four-header bottom bank, upper laminar, and water curtain headers deliver 10 ∘ C / s , 10.66 ∘ C / s , and 7.85 ∘ C / s of cooling rate, respectively. The simulations also predict the heat flux in the impingement, parallel, and air-cooling zones to be in the range of 4000–12,000, 500–2500, and 80–400 (w / m 2 K) on the top surface, and 21,000–5400, 700–4200, and 380–170 (w / m 2 K) on the bottom surface, respectively. According to the temperature-dependent attitude of steel properties, the effect of strip's thermo-physical properties on the heat transfer along ROT was examined, illustrating the significant impact of specific heat on cooling, which leads to the endorsement of the functionality of early cooling compared to delayed and distributed strategies for the investigated HSLA (high-strength low-alloy) steel. [ABSTRACT FROM AUTHOR]

Recent experiments have shown that improper encoding in MR user interfaces exacerbates the individual cognitive symbol effect, leading to issues of excessive cognitive workload and elevated psychological stress levels in individual cognitive task methods. In light of this, this paper proposes a novel MR user interface information encoding method. By assessing the improvement level of object clues and action clues on information encoding quality, it identifies the optimal encoding forms for combining these two types of cues, thereby establishing a more intuitive and natural communication channel for information. The paper presents several human–machine interface usability test results and compares the proposed encoding forms with the MR interface encoding information currently used in significant factories like AVIC (Aviation Industry Corporation of China) to analyze the advantages and disadvantages of the proposed encoding forms. [ABSTRACT FROM AUTHOR]

Gear shafts are commonly manufactured by machining of gear teeth and shaft separately. This kind of approach entails quite some problems, such as long processing time, large die, and low production efficiency. To tackle these problems, this paper innovatively proposes a new process of cross wedge rolling (CWR) that is specifically tailored to the manufacturing of gear shafts, with which the shaft and teeth are formed at one go. The finite element model of CWR forming of gear shaft is established to simulate and analyze the CWR forming process. A three-factor and three-level response surface test is designed to optimize the processing parameters, where the friction coefficient, rolling temperature, and die movement speed are chosen as three factors, and inhomogeneous deformation is set as the response. The optimal parameters are obtained as follows: the rolling temperature is 1240 ℃, the speed of the die movement is 336 mm/s, and the friction coefficient is 0.8. This result is subsequently verified by experiments. Further on, the microstructure evolution of the characteristic points of the CWR forming process of gear shaft is analyzed. It is found that the grains at the gear teeth section are continuously refined and grown from the boundary at the early section of deformation, and the final grains grown are much smaller than the original ones. In addition, the grains appear to grow in a short range of time in the process of deformation, but the overall trend is towards refinement. In the shaft section, the evolutions of the grains in the two stepped shaft segments are almost the same; the grain deformation shows cyclic changes; the degree of grain refinement in the shaft is higher than that in the teeth; and the degree of grain refinement in the shaft center is higher than that in the shaft edge. The results of the study provide a theoretical basis for short-process forming of high-performance gear shafts by cross wedge rolling. [ABSTRACT FROM AUTHOR]

Liquid composite molding (LCM) is a common technology for manufacturing the polymer composites. The LCM process involves a non-isothermal flow of resin which influences the curing stage. The gradient of curing degree generated before gel point in curing stage seriously affects the quality of composites. The optimized design of cure cycle plays a crucial role in reducing gradient of curing degree. In this paper, the influence of non-isothermal flow on curing stage is considered. Based on ANSYS FLUENT software, the 3D non-isothermal resin filling-curing co-simulation is applied. The flow parameters, temperature parameters, and curing reaction parameters are fully considered in the co-simulation simulation, which can realize the multi-field coupling of thermal-flow-chemical field in the LCM process. The effectiveness of the co-simulation is verified by non-isothermal experiment of LCM process. An optimization method of cure cycle which the gradient of curing degree decreases significantly before the gel point is proposed. Through this method, the data obtained from the cyclic co-simulation to determine the temperature and heating rate at different curing times, and finally the optimal cure cycle, is obtained. Furthermore, these results have industrial significance for improving the LCM manufacturing of the key composite parts in aircraft, automobile, and ship technology. [ABSTRACT FROM AUTHOR]

Laser-based powder bed fusion (LPBF) is a widely utilized technique for additive manufacturing (AM) of metal components. The size of LPBF-produced parts is restricted by machine dimensions. Welding emerges as a feasible solution for connecting smaller parts generated via PBF. Nevertheless, the weldability of PBF parts differs from conventional ones due to the unique thermal history of PBF components. This paper investigated the weldability of stainless steel 316L and tensile behavior of welded samples, comparing samples produced through LPBF and the conventional wrought method. Tensile testing, grain size analysis, microhardness test, and assessment of secondary dendrite arm spacing were conducted on every welded combination of materials (AM-AM, wrought-wrought, and AM-wrought) using gas tungsten arc welding (GTAW). The findings indicate that the wrought material demonstrates a higher maximum strength (577.5 MPa) and a lower yield strength (231.7 MPa) compared to the AM material (with a maximum strength of 548.2 MPa and a yield strength of 399.9 MPa). This difference may be attributed to the annealing process applied to the wrought material, which has not been applied on the AM material. Additionally, welded wrought samples have a significantly lower tensile strength compared to non-welded samples. The wrought samples exhibit a larger average grain size (11.14 to 31.12 μ m ) in the heat affected zone (HAZ) compared to non-heat affected regions (8.13 μ m ). In contrast, it is found that grain coarsening does not occur in PBF samples, which exhibit a similar grain size in the HAZ (15.04 μ m ) vs 13.97 μ m outside of the HAZ. Larger grain sizes within the HAZ correspond to a larger reduction in tensile strength for the wrought samples, compared to PBF samples. Similar secondary dendrite arm spacing has been observed in the weld regions of both PBF and wrought materials. Microhardness test results indicated that the AM base material has the highest microhardness and gradually decreases as transitioning to the HAZ and weld region. In summary, the PBF samples exhibit less reduction of strength and ductility after welding than wrought samples. Therefore, it is determined that additively manufactured 316L stainless steel has a higher weldability than traditionally manufactured wrought 316 stainless steel. [ABSTRACT FROM AUTHOR]

Accurate calibration of a Stewart platform is important for their precise and efficient operation. However, the calibration of these platforms using forward kinematics is a challenge for researchers because forward kinematics normally generates multiple feasible and unfeasible solutions for any pose of the moving platform. The complex kinematic relations among the six actuator paths connecting the fixed base to the moving platform further compound the difficulty in establishing a straightforward and efficient calibration method. The authors developed a new forward kinematics-based calibration method using Denavit-Hartenberg (DH) convention and used the Stewart platform "Tiger 66.1" developed in their lab for experimenting with the photogrammetry-based calibration strategies described in this paper. This system became operational upon completion of construction, marking its inaugural use. The authors used their calibration model for estimating the errors in the system and adopted three compensation options or strategies as per least-square method to improve the accuracy of the system. These strategies leveraged a high-resolution digital camera and off-the-shelf software to capture the poses of the moving platform's center. This process is non-invasive and does not need any additional equipment to be attached to the hexapod or any alteration of the hexapod hardware. This photogrammetry-based calibration process involves multiple high-resolution images from different angles to measure the position and orientation of the platform center in the three-dimensional space. The target poses and actual poses are then compared, and the error compensations are estimated using the least-square methods to calculate the predicted poses. Results from each of the three compensation approaches demonstrated noticeable enhancements in platform pose accuracies, suggesting room for further improvements. Given that "Tiger 66.1" is based on the general Stewart platform structure, the proposed calibration method holds promise for extension to machines operating on similar principles where non-invasive calibration is desirable. This study contributes to advancing the field of Stewart platform calibration, paving the way for more precise and efficient applications in various domains. [ABSTRACT FROM AUTHOR]

Energy efficiency is a challenging and relevant research field in modern manufacturing industries, where robotic systems play an essential role in the automation of several industrial operations. In this paper, we present an approach for the energy-efficiency optimization of a 3-DOF parallel robot. The proposed strategy leverages the task placement, the execution time, and the length of the robot lower arms to minimize the energy consumption for the execution of a predefined high-speed pick-and-place operation. To evaluate the actuators energy consumption, the kinematic, dynamic and electro-mechanic mathematical models, as well as an equivalent multibody model, of the parallel robot are implemented. The results of extensive numerical simulations show that the proposed strategy provides notable improvements in the energy efficiency of the parallel robot, with respect to alternative approaches. Starting from a pick-and-place task with optimal task placement with a consumption of 38.2 J (with a cycle time of 0.4 s), the energy expenditure can be reduced to 3.75 J (with a cycle time of 1.86 s), with a reduction percentage of 90.2%, by additionally optimizing the execution time, and the length of the robot lower arms. These results lead to a reduction from 5733 J/min (for 150 cycles/min) to 121 J/min (for 32 cycles/min), allowing to choose the best trade-off between robot productivity and consumed energy. [ABSTRACT FROM AUTHOR]

Human errors are prevalent in manual assembly line statistics, but humans are still a necessary and numerous working force for assembly tasks. Since faster and shorter production cycles lead to higher mental efforts, an alternative to decrease the cognitive load and errors of manual assembly lines is using augmented reality (AR). AR increases system interaction and assists operators in the step-by-step of any tasks performed. Its use allows granular production data, enabling an increase in quality control and timely detection of assembly problems. However, AR alone is not enough to avoid demotivation and lack of engagement in the task, which is repetitive. Gamification can become an auxiliary resource to increase operators' motivation and engagement. This paper presents a system model to integrate AR and gamification for a manual assembly line of printed circuit boards (PCBs) called GRAAL, used to develop an actual system for PCB assembly, which can guide operators using AR but also tracks down their efficiency and efficacy which is then used for gamifying their performance. A prototype system was implemented and assessed by 34 specialist respondents. TAM 3 (Technology Acceptance Model 3) Questionnaire was used to assess the system, which allowed us to find that GRAAL was well accepted (all scores were above the center of a Likert scale from 1 to 7 values), suggesting that GRAAL may be useful as an auxiliary resource to manual assembly lines. We conclude that modeling a system that merges AR and gamification is feasible but a non-trivial task in industry. The system's features are dependent on conditioning factors such as Application Environment, Application Context, Application Audience, AR hardware, and gamification elements. [ABSTRACT FROM AUTHOR]

Bearings represent crucial components within rotating machinery, and unexpected failures can lead to significant damage and unplanned breakdowns. This paper introduces a novel approach to diagnose bearing faults under variable working conditions, leveraging the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and sequential backward selection (SBS). CEEMDAN automatically selects intrinsic mode functions (IMFs) from vibration and current signals to establish a comprehensive set of health indicators. Subsequently, the SBS algorithm identifies the most pertinent indicators for different bearing failure modes. The accuracy of the proposed method is evaluated on both vibration and electrical signals using data from a dedicated test bench at the Signal and Industrial Process Analysis Laboratory (LASPI). Results demonstrate the effectiveness of the proposed method in accurately identifying and classifying bearing faults across various working conditions, utilizing both types of signals. This approach holds promise for real-world industrial applications, offering a reliable method for condition monitoring and diagnostics in bearing systems. [ABSTRACT FROM AUTHOR]

Polyetheretherketone is a thermoelastic biopolymer that has good properties for use in medical implants. The paper presents the results of experimental research on the influence of some machining conditions (feed per tooth and cutting strategy) on the size of the temperature in the milling area, the size of the components of the cutting force, the roughness of the machined surface, the hardness of the surface layer resulting from the milling application. The working feeds had values in two ranges (0.0167–0.025 mm/tooth and, respectively, 0.05–0.15 mm/tooth). Different zig, zig-zag, and follow periphery machining strategies were applied to evaluate their effects on the values of some milling parameters of interest and, respectively, on the quality and integrity of the surface resulting from milling. The experimental research was carried out using modern research equipment, such as the confocal microscope and an interferometer, for the observation and analysis of the surface texture. It was found that a movement of the tool along a zig-zag type strategy leads to smoother surfaces compared to those obtained by zig-zag and follow periphery strategies. Higher cutting feeds (0.05–0.15 mm/tooth) determine lower values of the roughness parameter Sa. When feed values are in the range of 0.05–0.15 mm/tooth, the cutting temperature reaches values of 160–183 °C. In accordance with the higher temperature values, an increase in the hardness of the superficial layer resulting from milling is also observed. A consequence of the temperature increase in the cutting zone was a reduction in the sizes of the components of the cutting force, the material becoming more ductile and easier to cut. [ABSTRACT FROM AUTHOR]

A suitable texture location is a significant factor in avoiding derivative cutting and improving friction conditions. This paper aims to explore the impact of texture in the sticking and sliding friction regions on cutting performance. The chip distribution model was established and validated to assess the distribution of friction regions. Turning experiments with and without MoS2 solid lubricants were conducted on AISI 304 using textured tools with various texture locations determined by the chip distribution model. The results derived from the prediction model aligned favorably with the experimental results, and the location near the boundary of the sticking and sliding friction regions was the suitable initial location of tool surface textures. Under dry cutting conditions, the texture at the termination of the sticking region increased the cutting force and temperature by only 0.5% and 4.8%, while the presence of MoS2 caused a decrease in cutting force and temperature by 2.9% and 3.5%, respectively. [ABSTRACT FROM AUTHOR]

The mitigation of undesired welding deformation during laser welding of metal bipolar plates (BPs), which are crucial components in proton exchange membrane fuel cells (PEMFCs), represents a significant challenge that has yet to be effectively addressed. The low weight requirements of PEMFC endow the BP with ultra-low thickness and sensitivity to processing technology. This paper introduces a study that reduces the deformation of BPs from 4 to 1 mm by implementing a novel multi-path welding process as an alternative to traditional single path welding. The research primarily investigates the weld seam space (WSS) and seven series of experiments with dissimilar WSS are conducted with the objective of minimizing deformation using specially designed welding fixtures. Following this, the weld seam stiffness and residual stress distribution are analyzed in further detail to elucidate the effects of WSS on welding deformation. Furthermore, a stress distribution indicator is proposed in this study to characterize the stress distribution. The conclusion of this study is that multi-pass welding techniques are highly effective in reducing welding deformation, particularly when the WSS is set to 0.75 mm. In principle, the stiffness of the weld seam and the distribution of residual welding stress jointly determine the welding deformation. [ABSTRACT FROM AUTHOR]

Wire arc additive manufacturing (WAAM) is one of the most productive metal additive manufacturing methods. One of its most promising applications holds in the manufacturing of difficult-to-cut materials where production costs can be reduced with minimizing the time of machining and total tool costs. To develop a correct WAAM, technological processes for manufacturing complex-shaped components welding torch path corrections and welding power corrections have to be made especially in critical sections such as corners and sharp edges. A predictive mathematical model of the material cladding during the WAAM process has been developed for the purposes of generating an optimal toolpath of the WAAM clads. This predictive mathematical model is simplified to reflect the important physical phenomena in the weld pool but also to optimize computing time. In this paper, the principle of the mathematical model is described, and its functionality is verified by the welding experiments with five different welding power settings. For the initial calibration of the model parameters single straight-line weld clads with 5 different welding power settings (wire feeds) ranging from 5.0 to 8.6 m/min were investigated. 3D scans of these welded samples are used for the verification. With the calibrated simulation model, it was possible to predict the precise shape with a maximum deviation circa 0.20 mm. The start portions of the weld clads seem more complex having the deviation circa 0.30 mm. These are valuable results as the WAAM technology is generally considered to be reasonably rough. [ABSTRACT FROM AUTHOR]

With the advent of Industry 4.0 and the impending shift towards Industry 5.0, the integration of human–robot collaboration (HRC) into production systems has become increasingly widespread. This paradigm shift leverages collaborative robots, or cobots, to mitigate physical and mental strain on human workers, thereby increasing productivity and improving overall quality performance. This paper investigates the interplay of productivity and quality factors with assembly complexity in both manual and collaborative assembly systems. The focus is placed on a product family of electronic boards, with varying levels of assembly complexity, to provide a comprehensive comparison between manual assembly and two different collaborative assembly scenarios. Key performance metrics such as assembly time and total defects are evaluated. This case study, rooted in the electronics industry, seeks to provide a valuable perspective on how assembly complexity influences productivity and quality in product family assembly systems. The results of this study aim to contribute to the growing body of knowledge on the implementation of HRC in manufacturing, facilitate informed decision-making and encourage further advances in this rapidly evolving field. [ABSTRACT FROM AUTHOR]

This work focuses on porosity formation during the welding of dissimilar aluminium alloys (cast and sheet) by pulsed gas metal arc welding (GMAW) with different travel speeds (12–14 mm/s) and by friction stir welding (FSW). The case study concerns the assembling of a battery-pack enclosure prototype. The welded specimens were scanned by 3D X-ray computed tomography. The cast base material (BM) shows a porosity percentage of 1.45%, and it is characterized by pores with a strong hyperbolic relationship between equivalent diameter and sphericity. Considering the GMAW beads, porosity rises with the travel speed (from 1.80 to 5.12%), due to the reduction of the opening window in which pores can escape. Pores with volume higher than 0.10 mm3 rise with the travel speed, representing from 9.75 to 32.98% of the total porosity. These pores are responsible for the weaker hyperbolic connection for sphericity found for the GMAW beads. On the other hand, FSW mixes and homogenizes the pores in the cast BM. The novelty of the paper lays in proving the strong potentialities of FSW for weld porosity reduction. A re-designing of the battery-pack enclosures is necessary to limit arc welding in marginal areas, which are not crucial for sealing but necessary to create a stable platform to be subsequently sealed with FSW. [ABSTRACT FROM AUTHOR]

In comparison to coordinate measuring machine (CMM), on-machine measurement (OMM) offers the benefit of avoiding re-clamping of workpieces and has become a crucial technology for adaptive machining. In OMM, the positioning errors of machine tool shift the ideal position and orientation between the probe and the workpiece. This introduces an error in the measurement result, causing workers to question OMM's precision. Therefore, the clarification of the relationship between positioning error and OMM error is helpful to make this technique more reliable. For this purpose, a five-axis OMM error model considering positioning errors is proposed. First, this paper gives the definition of feasible measurement region (FMR) about five-axis machine tool and obtains the FMR under specified measurement feature. Then, in the interest of identifying the influence of machine tool positioning error on OMM accuracy, an OMM error prediction model considering positioning error is established, which can be used to predict the error distribution in FMR. Next, the validity of the prediction model is verified by OMM experiments on the standard block. Finally, several applications of the OMM error prediction model are proposed. [ABSTRACT FROM AUTHOR]

With the continuous evolution of additive manufacturing technology, the production of spherical powders has become increasingly vital. Various studies suggest that factors such as the preparation process, powder materials, and sphericity are crucial in determining product performance. This paper provides a comprehensive review of the principles, advantages, and disadvantages of three widely used preparation technologies for spherical powders: gas atomization (GA), plasma rotating electrode process (PREP), and radio frequency plasma (RFP). Next, we identify the current research gaps in the preparation process for spherical powders and analyze the techniques for controlling particle size, sphericity, and purity during powder production. Finally, we proposed the development trend of spherical powder preparation technology, which provides crucial insights for optimizing the preparation process. [ABSTRACT FROM AUTHOR]

Collaborative robots, also known as cobots, are designed to work alongside humans in a shared workspace and provide assistance to them. With the rapid development of robotics and artificial intelligence in recent years, cobots have become faster, smarter, more accurate, and more dependable. They have found applications in a broad range of scenarios where humans require assistance, such as in the home, healthcare, and manufacturing. In manufacturing, in particular, collaborative robots combine the precision and strength of robots with the flexibility of human dexterity to replace or aid humans in highly repetitive or hazardous manufacturing tasks. However, human–robot interaction still needs improvement in terms of adaptability, decision making, and robustness to changing scenarios and uncertainty, especially in the context of continuous interaction with human operators. Collaborative robots and humans must establish an intuitive and understanding rapport to build a cooperative working relationship. Therefore, human–robot interaction is a crucial research problem in robotics. This paper provides a summary of the research on human–robot interaction over the past decade, with a focus on interaction methods in human–robot collaboration, environment perception, task allocation strategies, and scenarios for human–robot collaboration in manufacturing. Finally, the paper presents the primary research directions and challenges for the future development of collaborative robots. [ABSTRACT FROM AUTHOR]

During the pulsed laser cladding process, complex thermal accumulation occurs between powder and beam due to the pulsed laser periodic change. The selection of process parameters affects the cladding layer quality, and the correlation between the parameters is high. It is of great significance to obtain high quality cladding layer to determine the influence of the powder-carrying gas nitrogen velocity, powder feeding port diameter, and powder feeding angle on the powder flow, as well as the optimal powder shading rate and the mechanism of powder interaction with pulsed laser beam. In this paper, a gas–solid coupling model during the pulsed laser cladding process of three-beam coaxial powder feeder was established, and the rotating Gaussian heat source function of pulsed laser was written to calculate the temperature, flow velocity, and concentration distribution considering the interaction between laser and powder. The orthogonal test method was used to optimize the process parameters in order to reduce the shading rate of powder and improve the laser energy utilization. On this basis, a full cycle three-dimensional multi-field coupling numerical model for pulsed laser cladding process was established, and the temperature, flow, stress fields, and multi-component heat and mass transfer behaviors were calculated under different powder shading rates. The flow temperature of powder was collected by infrared thermometer and compared with the numerical results, the reliability of the model was verified. This study provides a significant theoretical basis for the full-cycle optimization of process parameters and the improvement of cladding layer quality during pulsed laser cladding. [ABSTRACT FROM AUTHOR]

The concepts of digital twins (DTs) have been widely studied to predict system performance, shorten design cycles, and implement preventive maintenance, but mainly, in large-scale enterprises. It is extremely beneficial to the whole manufacturing sector, since DTs can be readily implemented in small and medium-sized enterprises (SMEs) with basic computer aided engineering (CAE) tools; over 95% enterprises are SMEs. This paper aims to prove the feasibility of using commercial CAE tools, such as SolidWorks Simulation, to design air-quenching processes for SMEs. SMEs can benefit to explore new business opportunities, reduce system design cycle, and improve existing air-quenching processes. To our knowledge, it will be the first work of adopting DTs in conceptual design of an air-quenching process in sense that (1) the need of simulating an air-quenching process before physical implementation is discussed thoroughly; (2) heat transfer processes are classified, governing mathematical models for various heat transfer behaviors are introduced to present an evaluation model of a heat transfer process; (3) main process variables of air-quenching are identified; (4) a DT of an air-quenching process is developed and simulated to verify the capabilities of commercial SolidWorks Simulation; (5) case studies are developed to show how a CAE tool can be used in DTs. The findings from the reported work are summarized with a debrief of our future work. [ABSTRACT FROM AUTHOR]

Ball-end milling cutters are commonly used in the finishing processes of curved-side milling for titanium alloys; however, several issues arise during machining, such as poor cutting conditions at the bottom of the end teeth, low cutting speeds, and limited chip space. Given the above issues, the research on the design and manufacture of conical arc side-edge milling cutter for titanium alloy processing was carried out in this paper; the mathematical model of the vital structure of conical arc side-edge milling cutter was established; the grinding trajectory equations of tool front and flank were deduced; the tool-workpiece kinematics of ultrasonic vibration applied to conical arc side edge was studied; and the comparative experimental study of the conical arc side-edge milling cutter cutting titanium alloy with and without ultrasonic vibration was carried out. The experiment results indicate that in comparison to conventional milling techniques, ultrasonic vibration cutting significantly decreases cutting force, plastic deformation of the chip, and wear rate of the flank face. The tool wear band is both longer and more uniform, bonding phenomena in titanium alloys are distinctly reduced, and tool performance is improved. [ABSTRACT FROM AUTHOR]

The inclusion of additive manufacturing (AM) as an automated repair method leads to a sustainable remanufacturing process, which is known as additive repair. Despite its potential in improving the efficiency of repair and restoration, additive repair remains in its infancy and requires a thorough investigation on part design and process parameters. The major concern raised in additive repair is the capability to create perfect bonding between two metals, which will affect the mechanical properties of the complete repaired part. Hence, performing evaluation from the beginning is crucial to validate the feasibility of the process through appropriate structural analysis and to obtain deformation and stress results. Brake caliper housing is selected as a remanufacturable component for case exemplary purposes. Prior to analysis, the potential damages and failures of the brake caliper component were initially evaluated through literature surveys and direct interviews with industry experts where two types of damages were identified, namely, cracks and broken or fractured parts. Then, the validation focuses on comparative analysis of two different conditions of the brake caliper housing: original, and repaired caliper model using finite element analysis in ANSYS. Results indicate that the strength of the repaired caliper model shows equal and higher strength compared with the original model. This result confirms that the repair process through AM can retain or improve the quality of the remanufactured brake caliper housing. Therefore, this paper provides a systematic framework for the evaluation of mechanical properties in multi-metal additive repair with the integration of failure analysis techniques. [ABSTRACT FROM AUTHOR]

Due to the inevitable deviation of the casting process, the dimensional error of the turbine blade is introduced. As a result, the location datum of the film cooling holes is changed, which has an impact on the machining accuracy. The majority of pertinent studies concentrate on the rigid location approach for the entire blade, which results in a modest relative position error of the blade surface but still fails to give the exact position and axial direction of the film cooling holes of the deformed blade. In this paper, the entire deformation of the blade cross-section curve is divided into a number of deformation combinations of the mean line curve based on the construction method of the blade design intent. The exact location of the film cooling holes in the turbine blade with deviation is therefore efficiently solved by a flexible deformation of the blade that optimises the position and axial direction of the holes. The verification demonstrates that the novel method can significantly reduce both the contour deviation of the blade surface and the location issue of the film cooling holes. After machining experiments, the maximum position deviation of the holes is reduced by approximately 80% compared to the rigid location method of the entire blade, and the average value and standard deviation are also decreased by about 70%. [ABSTRACT FROM AUTHOR]

Accurate tool wear prediction is of great significance to improve production efficiency, ensure product quality and reduce machining cost. This paper proposes a hybrid physics data-driven model-based fusion framework for tool wear prediction to improve low prediction accuracy of physical model and poor interpretation of data-driven model. In this framework, physical information and local features of sensor measurement signals are used as inputs to build a hybrid physics data-driven (HPDD) model. And data mining and physics principles are effectively integrated by using unlabeled samples for data expansion. Piecewise prediction is introduced to reduce difficulty in parameter estimation. Then, in order to manage prediction uncertainty of physical information and HPDD method, two prediction results are gradually combined based on Bayesian fusion mechanism to eliminate prediction error. Finally, the effectiveness of the proposed method is verified by experiment. Compared with existing methods, this method significantly improves prediction. The mean values of root mean square error (RMSE) and mean relative error (MARE) for tool wear prediction results are respectively 2.28 and 1.85. [ABSTRACT FROM AUTHOR]

Ensuring first-time-right on-site repair of critical structures is a key challenge for additive manufacturing (AM)–based repair solutions. Fast thermal simulations are thus needed to plan efficient and error-free AM processes. This paper addresses a fast thermal simulation method for a novel subsea wire arc additive manufacturing (SWAAM) repair procedure. Current commercial finite element (FE) codes for typical welding and AM are computationally expensive and slow. The presented 2D finite difference approach can be used to simulate SWAAM on a damaged plate with around 70 times acceleration compared to real welding times, without the use of parallelization. Although not being able to accurately represent the temperature in close vicinity of the welding torch, the approach shows excellent correspondence with FE simulations and experiments in regions of the plate where the temperature has assumed a distribution that is largely two-dimensional. Compared with FE simulations, the approach is experimentally verified to be accurate to 10 °C within 7 s after the welding torch has passed a point on the plate. Thus, the approach can provide a measure of the global temperature field in a thin-walled structure during repair. The thermal simulation is preceded by a welding path planner, which generates appropriate paths based on slicing of a 3D surface scan of the damage that is to be repaired. Damages to equipment or non-ideal welding conditions are prevented by automatically pausing the welding if the calculated temperature in the path ahead of the welding torch exceeds a predefined interpass temperature limit. [ABSTRACT FROM AUTHOR]

Tools for implementing a systematic quality management are necessary for the use of material extrusion as an additive manufacturing process for products with high quality requirements. Well-defined quality classes are crucial for ensuring that the requirements for a product can be communicated transparently and that the existing properties can be evaluated. Furthermore, there is a lack of capable measurement equipment for the acquisition of process data during the production process. To address these challenges, the present paper introduces an image processing system that determines quality indicators for individual layers in terms of imperfect surface percentages and the number of imperfections. The central element of the hardware is an adaptive darkfield illumination, which leads to high-contrast images. In addition, five types of layer subareas are identified in a segmentation step. Unsupervised machine learning methods are then used to detect imperfections in each layer subarea. In the segmentation, the current layer can be distinguished from irrelevant image background regions with an F-measure of 0.981. For the layer-wise measurement of the quality indicators, relative measurement errors with standard deviations of 25 to 76.1% are found. After evaluating the capabilities of the image processing system, a proposal for limits of quality classes is derived by monitoring several material extrusion processes. For this purpose, three quality classes for each of the five layer subareas are deduced from the process scatter measured by the image processing system. The results are an important contribution to the industrialization of material extrusion in safety–critical areas such as medical technology or the aerospace industry. [ABSTRACT FROM AUTHOR]

The direction in which wire and powder feedstock are fed influences deposit quality of as-built parts produced using laser-direct energy deposition (L-DED). While lateral wire feed has been explored in existing L-DED investigations, limitations like process instability persist, especially in achieving the required connection between the wire and the melt pool. Co-axial feedstock deposition offers a potential solution, enabling higher manufacturing flexibility and efficiency by co-axially feeding wire or powder. However, the full potential of L-DED using co-axial feeding for metal components remains underexplored due to equipment limitations. This study systematically evaluates the printability of stainless steel (SS) 316L and compares the microstructures and microhardness properties between co-axial powder-fed and wire-fed L-DED specimens. Utilizing the MELTIO M450 L-DED system in an argon environment, single-layer three-track specimens are produced with different combinations of process parameters. Comprehensive characterization, employing optical and scanning electron microscopy alongside microhardness testing, reveals powder-fed specimens exhibit greater melt pool depth and cooling rates, while wire-fed counterparts display fewer oxide inclusions and smoother surfaces. Microstructural differences include higher δ-ferrite content in wire-fed specimens. Microhardness values between powder-fed and wire-fed specimens are comparable. These findings hold implications for sequential powder and wire deposition, enabling the production of diverse mechanical structures with distinct characteristics. Overall, this paper provides an insight into feedstock selection for efficient metallic part production via co-axial feedstock deposition and recommends a range of process parameters suitable for fabricating SS316L parts using co-axial deposition in L-DED. [ABSTRACT FROM AUTHOR]

The forming grinding process is a crucial method for helical flute grinding of the end mill and screw tap, and the grinding wheel profile is the key to ensure the precision of the helical flute, which is constrained by the grinding wheel posture. However, the existing methods have some deficiencies such as the invalidity or uneven wear problems. In this paper, an optimized calculation method of the grinding wheel profile for the forming grinding of the helical flute is proposed, including the suitable grinding posture correspondingly. Firstly, the parametric models of the helical cutting edge and the helical flute surface are established. Secondly, the contact condition between the grinding wheel and the flute is deduced to calculate the grinding wheel profile by the envelop theory. Thirdly, an optimization method for grinding wheel profile is proposed, which could predict of the solution interval, avoid the profile intersection, and improve wear resistance. Finally, the method was verified by a series of simulations and experiments, and the results show that the method could meet the grinding precision requirements and expand the application range of forming grinding technology in helical flute. [ABSTRACT FROM AUTHOR]

Robotic force control is crucial for precise polishing and has a significant influence on the final effects. The blade has a free-form surface in space, and the curvature changes drastically, making traditional impedance control feedback untimely. To solve this problem, this paper proposes an adaptive impedance control method for blade polishing based on Kalman filter. The force data is denoised by Kalman filtering to obtain the real force data, then the data is gravity compensated to obtain the real polishing force. The method analyzes the influences of stiffness change and displacement change on the polishing force, and establishes a stiffness and displacement coupling compensation model. The method achieves timely feedback when the robot copes with unknown environmental stiffness changes. In addition, the Lyapunov function is applied to verify the stability of the method during implementation. Four processing conditions are simulated by using Matlab Simulink. The results indicate that the proposed method can provide faster response and higher force tracking accuracy by adjusting the reference position when the environment changes. In the experiment of polishing blade, the roughness is reduced to below Ra0.32 μm and fluctuation range of polishing force is within ±1 N. The force control method performance is significantly improved and the blade surface quality is effectively improved. [ABSTRACT FROM AUTHOR]

Energy coupling efficiency has an important effect on welding quality in pulsed laser spot welding. In this paper, laser spot welding experiments are conducted on 3 mm AZ31 magnesium alloy using an AC-500 W Nd:YAG pulsed laser welder. Results show that the rectangular pulse (R) energy coupling is the most efficient when peak power is less than or equal to 3 kW, but the energy coupling of ramp-up pulse (R-U) is the most efficient when peak power is greater than 3 kW. When the peak power is 4 kW, the energy coupling efficiency of laser spot welding under R-U pulse is the highest. At this time, the cross-sectional area of welding spot reaches 1.3 mm2, peak temperature is 1550 ℃, the metal loss of melting pool is 4.4 mg, the depth-to-width ratio of keyhole is 1.06, and the laser absorptance is 0.9. In addition, a numerical model of velocity field of transient keyhole laser spot welding is established by using ANSYS, and the shape and size of keyhole are calculated during laser spot welding. The mechanism of pulse shaping to improve the energy coupling efficiency of deep-melt laser welding of magnesium alloys is revealed. [ABSTRACT FROM AUTHOR]

Sintered gears manufactured through powder metallurgy technology contain residual porosity that can make them inadequate for high power supply. Crack propagation is significantly enhanced by both residual porosity and cyclical stresses involving the teeth. The use of densification processes can highly improve their performances, permitting the reduction of the residual porosity. Among the densification processes, the rolling assumes a key-role. The process permits the densification of the tooth flanks, the most stressed parts of the wheel. However, the performances of the rolled wheel depend on several process parameters, whose setup phase requires several efforts and many experiments. Finite element (FE) model can be a helpful tool, allowing a faster estimation of the process parameters, reducing waste and costs linked to the experimental tests. In this sense, FE modelling techniques discussed in literature only cover the simulation of spur gears densification process, since they consist of in-plane 2D finite elements. In this paper, different numerical modelling techniques, based on 2D finite elements, are proposed to simulate the densification process of spur gears and used to perform a tendency analysis to explore the effects of wheelbase reduction between the forming rollers on the material densification. Material densification appeared higher for reduced wheelbases, but an increasing cavity was observed at the tooth root as the wheelbases decreases. Moreover, a FE model based on 3D finite elements is proposed to reproduce numerically the rolling process of a helical gear. The accuracy of the 3D FE model was measured against the results provided by some experimental tests, herein discussed too. A good agreement between numerical and experimental results was observed. [ABSTRACT FROM AUTHOR]

This paper presents constitutive equations that describe the hot flow behaviour of Virgin (VG) X20 and rejuvenated heat-treated creep exhaust (CE) X20 steels. The study provides a foundation for determining the effect of rejuvenation heat treatment on CE steels by making comparisons to the VG steel. Hot compression tests were conducted in the temperature range of 900 °C to 1050 °C, at strain rates of 0.1–10 s−1 to a total strain of 0.6, and stress–strain curves were obtained. The flow stress curves of both steels exhibited dynamic recovery (DRV) characteristics as the main softening mechanism. Constitutive constants of steady-state stresses were determined. The stress exponents, n, were 6.62 (VG) and 5.58 (CE), and the apparent activation energy values were 380.36 kJmol−1(VG) and 435.70 kJmol−1 (CE). Analysis of the activation energies showed that VG steel had better workability properties than CE steel and was easier to deform at high temperatures. Constitutive equations for predicting the flow stress in the two steels were established. This were verified by statistical tools: Pearson's correlation coefficient (R) and Absolute Average Relative Error (AARE). The results showed R-values were, 0.98 (VG) and 0.99 (CE), and the AARE values for VG were 4.17% and 9.01% for CE. The statistical parameters indicated a good correlation between the experimental and predicted values. The constitutive equations therefore adequately described the flow stress behaviour of both steels and can therefore efficiently analyse industrial metal forming schedules. [ABSTRACT FROM AUTHOR]

This paper describes a novel end-to-end approach for automatic welding-robot programming based on a product-process-resource (PPR) model, for one-of-a-kind manufacturing systems. Traditionally, the information needed to program a welding robot is processed and transferred along the manufacturing organisation's value chain by using several stand-alone digital systems which require extensive human input and high skill to operate. A PPR model is proposed through this research as a platform for storing and processing the necessary information along the value chain seamlessly. Unlike existing approaches which make use of complex algorithms to automatically identify the weldment seams, the approach suggested in this research makes use of information already digitalised by design engineers under the form of ISO 2553:2019 compliant weldment annotations. Hence, the PPR model contains the weldment annotations; it enables the automatic programming of welding robots and reduces human input down to a few minutes only. The applicability in manufacturing of the theoretical concept is demonstrated through technical implementations tested in the laboratory and on the value chain of an engineering-to-order (ETO) industrial partner involved in the metal fabrication industry. The experiments were conducted by creating several products using the proposed artefact. Experiments show that automatic programming of welding robots can be achieved using PPR models. The conducted experiments showed a reduction of about 80% in human input measured in terms of time, when using the proposed solution. The reduction of the human input can free up skilled labour resource which ETO SMEs can reallocate to other tasks. [ABSTRACT FROM AUTHOR]

The thermal characteristics of the motorized spindle significantly affect the machining accuracy and efficiency, and many thermal models have been developed to investigate the factors that affect the spindle thermal characteristics. However, the thermomechanical coupling of the bearings with constant pressure preload is rarely considered in the present works. Thus, this paper developed a transient temperature model of motorized spindle to study the influence of the radial thermal stress on the heat generation of the constant pressure preloaded bearings. In this research, an analytical thermal stress model was established first by simplifying the components of the bearings into a rotating ring geometry to calculate the thermal stress loaded on the bearings. Meanwhile, a transient temperature model of the motorized spindle was established based on the finite element method (FEM). Then, the analytical model was integrated into the spindle transient thermal model, so that the heat generated by bearings and the motorized spindle temperature can be revised constantly, through the iterative calculation between these two models. Finally, verification experiments with different work conditions clarify that the proposed transient thermal characteristic model of the motorized spindle is valid, and the study shows that it is necessary to consider the bearing heat generation induced by the radial thermal stress when the spindle runs at a high speed. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the contribution of tool wear and process parameters to the shape defects induced by the micro-machining of glassy polymers such as polycarbonate. An experimental approach is proposed in this study using an instrumented orthogonal cutting configuration. Diamond inserts have been considered as a cutting tool and have been subjected to different levels of accelerated wear. The worn tools were first characterized to identify the wear mechanisms that occurred on the active cutting zone and were then used to perform orthogonal cutting experiments on polycarbonate. Micro-cutting depth values (3–20 µm) were considered to respect the micro-machining configuration. Chip morphology, cutting forces, and machined surfaces' topography have been acquired to analyze and assess the effectively removed material depth regarding the theoretical cutting depth for each worn tool. Results show that the increase of the cutting edge radius is the main wear mechanism that occurred in the diamond inserts. This tool wear evolution was found to be the most influential factor on the induced shape defect by increasing the elastic deformation of polycarbonate rather than its shear when using micro-cutting depths, which induces a spring-back of polycarbonate after cutting. [ABSTRACT FROM AUTHOR]

High-resolution 3D printing technologies can print thin films; however, they are not commonly available because of their high initial cost, and the majority of them employ a pneumatic-driven printing technique that hinders retraction, which is crucial for printing complex geometries. The main objective of this paper is to modify an extrusion-based 3D printing technology and investigate its potential for thin-film printing for electronic device applications like perovskite solar cells (PSCs). The modification is done by replacing the filament extrusion system with a liquid extrusion system using a syringe pump. CAD software, CATIA V5R20, is used to model the parts of the syringe pump, which are then 3D printed from polylactic acid (PLA) filaments. To validate the functionality of the modified 3D printer for thin-film printing, a physical experiment is conducted to print a poly 3,4-ethylenedioxythiophene:polystyrene sulfonate (PEDOT:PSS) solution, a widely used conductive polymer, by varying the 3D printing parameters, namely; print speed, bed temperature, nozzle diameter, and x-distance offset. Based on the experiment, a thin PEDOT:PSS film was successfully printed with a thickness of 142 nm and a notable level of surface uniformity when compared to the spin coating. Further, the modified 3D printer is utilized to print a PEDOT:PSS and a perovskite methylammonium leadtriiodide-chloride (CH3NH3PbI3 − xClx) solution in a layer-by-layer fashion sequentially and tested for validity for perovskite solar cell (PSC) application by printing other layers of PSC on top of the perovskite layer using the spin coating method. Based on the test conducted, a competitive open-circuit voltage of 740 mV was successfully generated from the printed PSC. Finally, it has been observed that extrusion-based 3D printing technology can be modified and optimized to print thin films for PSC applications. This has tremendous advantages for rapidly printing and testing electronic devices in general, and PSCs in particular. [ABSTRACT FROM AUTHOR]

Modern manufacturing machinery is often pushed beyond its operational limits, leading to the degradation and failure of critical subsystems, including the linear axis. This paper presents a comprehensive health assessment study that evaluates the root cause failure faults (FFs) of linear axis components against an established system baseline. The study further enhances the health assessment by comparing the system’s repaired state to the baseline data. Each FF was artificially introduced into its respective component in the linear axis. After evaluation, the FFs were carefully repaired by following industrial practices related to the maintenance of the affected component. Our findings reveal that the most frequently occurring FF can be readily detected via the system’s internal data, and the repaired state of the evaluated FFs exhibited a percentage error of less than 10% when compared to the healthy state. This study highlights the importance of understanding how root cause FFs impact the system operation and provides valuable insights for maintaining nominal machine performance after repair. [ABSTRACT FROM AUTHOR]

As an all-in-one process that blended design, materials, and manufacturing, additive manufacturing (AM) adopted a bottom-up stacking approach, thereby avoiding excessive infrastructure and complex production steps. However, the different process stages of AM were influenced by multi-scale factors such as material characteristics, parameter settings, and process stability, resulting in uncertainty. Therefore, the effective containment and accurate evaluation of automated production processes were crucial. With the rapid development and widespread application of artificial intelligence (AI) technologies in the Industry 4.0 era, computer vision (CV) techniques, as an important component, could achieve multi-level understanding of the real world through traditional machine learning (ML) and efficient deep learning (DL) approaches based on information-dense cross-media data such as images, videos, and three-dimensional models. Hence, the organic integration of CV and AM was of great significance for the virtual simulation, global perception, real-time monitoring, and quality measurement of the machining processes. According to the chronological order and logical relationship of manufacturing engineering, this paper organized and summarized the application of CV techniques in material characteristics perception and stacking process simulation before the implementation of projects, in situ inspection, and law exploration during the manufacturing processes, as well as product evaluation and defect detection after processing, which demonstrated its powerful performance and great potential in the intelligence and integration of AM. [ABSTRACT FROM AUTHOR]

Geometric deviations and assembly deformations are inevitable in compliant assembly processes and have a significant impact on assembly quality. This paper proposes a variation propagation model based on isogeometric analysis (IGA), which unifies geometric deviations and compliant deformations in one framework by embedding exact geometry into assembly analysis. First, geometric deviations are modeled via offsets along control points using non-uniform rational basis spline (NURBS). Then, the elastic force induced by geometric deviation is calculated using Kirchhoff–Love shell elements. Further, clamping constraints, such as fixture positioning deviation and connection matching deviation, are transformed into displacement boundary conditions using the Lagrange multiplier method. Finally, several examples including the practical project cases are provided to demonstrate the accuracy and efficiency of the developed method in obtaining assembly deviation distributions. [ABSTRACT FROM AUTHOR]

The paper investigates the characteristics of the laser beam percussion micro-drilling (LBPMD) process in aerospace nickel-based superalloy Hastelloy X using microsecond pulses. The quality of the drilled hole is crucial in laser beam micromachining, and selecting appropriate process parameters significantly impacts the hole's quality. The objective is to achieve predefined hole dimensions with minimal taper angles. Additionally, the study focuses on the alteration of pulse width, which is a combination of laser pulse frequency and duty cycle. Laser power (P), duty cycle % (D), focal plane position (FPP), and laser frequency (f) are considered input parameters, while geometric features such as inlet and outlet diameters, hole taper angle, and inlet circularity are examined as process responses. ANOVA is employed to establish significant relationships between process parameters and response variations based on experimental tests. Creating a precise simulation model that accurately accounts for the moving boundary of the target material's receding surface is a crucial and challenging task in formulating the laser heat conduction problem. It is necessary to simultaneously capture the material's dynamic front movement and update the boundary conditions of the laser source. To model the micro-drilled hole with LBPMD, the UMESHMOTION and DFLUX subroutines, along with the arbitrary Lagrangian-Eulerian (ALE) adaptive remesh algorithm in the Abaqus™ software, are utilized. Notably, no previous numerical study has predicted the geometry of micro-drilled holes using this technique. The proposed procedure is validated through the predictions of inlet and outlet hole diameters. Special emphasis is placed on the validation of models. Consequently, the numerical model and statistical model are compared as well as the need to define model applicability. The study demonstrates that all input parameters significantly influence the inlet hole diameter, while the pulse width notably affects the taper angle and circularity. The interaction between high laser frequency and low duty cycle results in reduced pulse duration. Multi-objective optimization is performed to determine the optimal process parameter settings for desired quality characteristics, considering minimum hole taper angle, precise inlet diameter, and maximum inlet circularity of the hole as optimization criteria. The findings show that with the optimized predicted results obtained from the optimal input variables, a composite desirability of 92% can be achieved. [ABSTRACT FROM AUTHOR]

The final machining process, high-precision boring, can significantly affect the geometric error index of deep holes in gearboxes with thin-walled features. However, traditional mirror and mean compensation strategies are inadequate in compensating for the complex spatial and vector geometric errors, resulting in machining problems when boring deep holes in thin-walled boxes. This paper proposed a gradient compensation method that considered the geometric error and boring process characteristics to improve the current machining accuracy. The disadvantages of the classical compensation methods were analyzed in detail based on the error characteristics in boring deep holes. A gradient compensation was proposed and derived to improve the machining precision for boring deep holes on thin-walled boxes. On the other hand, a cutting test was designed and implemented using a control variable method in industrial cutting environment. Two different codes were programmed for boring process to validate the advantages of the proposed compensation method than the common. With the proposed compensation method, the geometric accuracy was improved by 86.12%, indicating that the proposed model was efficient for boring deep holes in thin-walled boxes. As a result, the proposed gradient compensation method successfully reduces the machining error of actual boring deep holes in thin-walled boxes. [ABSTRACT FROM AUTHOR]

Laser cladding has significant advantages in the forming process of Invar alloy. Nevertheless, the coefficient of thermal expansion, microstructure and mechanical properties still need to be further investigated. In this paper, the Invar alloy powder was used to prepare cladding samples, and the performance and microstructure of the cladding layer were investigated. The mechanical and thermal expansion performances of the cladding layer were analysed using a universal material testing machine and a thermal expansion instrument, and the microscopic structure and micro zone composition of the tensile fracture of the cladding layer were investigated using an SEM scanning electron microscope and an EDS energy spectrum analyser. The results show that the mechanical properties of the Invar alloy transverse cladding layer are better than those of longitudinal cladding layer; the thermal expansion performance of the cladding layer is good, and it keeps the same with the base material in the range of 25–200 °C; the fracture analysis reveals more dimples in the transverse cladding layer fracture with better plastic tenacity, and intergranular fracture and quasi-cleavage fracture in the longitudinal cladding layer fracture with slightly poor plastic tenacity. [ABSTRACT FROM AUTHOR]