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Thin-walled parts are widely used in the aerospace field. They have the characteristics of large material removal during processing and are affected by factors such as processing technology and processing environment, which can easily cause the deformation of parts. Deformation will seriously affect the machining accuracy of parts, which is one of the key factors affecting the installation accuracy and quality of parts. Aiming at the problem that the machining deformation of thin-walled parts cannot be perceived in real-time during the milling process. This paper constructs a digital twin framework for the milling process of thin-walled parts. Unity3D and Visual Studio 2010 software are used to build a digital twin intelligent processing platform to realize the interaction and integration of physical objects and virtual models. The simulation is carried out by ABAQUS finite element analysis software and verified by experiments. At the same time, based on the simulation data and historical processing data, the PSO-LSTM thin-walled part deformation prediction model is constructed, and the prediction model is embedded into the intelligent processing platform. The real-time monitoring of deformation during the machining process of thin-walled parts is realized, and the problem that the deformation of thin-walled parts cannot be perceived in real-time during the machining process is solved. By processing Al-7075-T6 thin-walled parts for experimental analysis, the prediction accuracy reaches 96.1%, which verifies the accuracy and effectiveness of the platform. [ABSTRACT FROM AUTHOR]

As a technology for the interaction and integration of products and simulation models, the digital twin can achieve accurate prediction and evaluation of product performance. However, the accurate model base is computationally complex, has a long iteration time, and is unable to perceive changes in the operating state in time. This leads to poor adaptability of the model and low efficiency of performance evaluation. The surrogate model can simplify the above model and improve computational efficiency. Based on this, this paper proposes a digital twin modelling and updating approach. The surrogate model is applied to the digital twin modelling process, which can accurately describe the physical mechanism and achieve interaction with the physical world. Then, this paper defines the consistency metric function, which achieves the rapid perception of the operation state and follows the physical world. Meanwhile, an improved LHS-Adam model update algorithm is used to adaptively update the model structure, improving the efficiency of the model parameters adjustment. Finally, experiments are conducted on the bogie suspension system to verify the feasibility and effectiveness of the update method in practical applications. The experimental results show that the established digital twin model has good updating performance and more efficient performance evaluation capability. [ABSTRACT FROM AUTHOR]

Paper dusting has recently been recognized as a significant issue in the hygiene tissue industry. This review considers the factors that may contribute to dusting and linting, as well as the challenges of evaluating dusting propensity. Examining both the paper and textile industries, several methods of dusting and linting assessment exist. This review describes the equipment, methodologies, targeted paper grades or materials, advantages, and disadvantages. Standards (if applicable) are also covered for each of the major methods. These existing methods were found to have various drawbacks, suggesting a need for an improved, standardized method and device. In conclusion, and to motivate future research, mechanisms of dust release are reviewed along with existing and possible solutions to combat the tissue-dusting problem. This paper outlines the importance of creating a repeatable, standard, and accurate testing procedure and methodology for dust particle characterization in the hygiene tissue industry. [ABSTRACT FROM AUTHOR]

Manual repair tasks in the industry of maintenance, repair, and overhaul require experience and object-specific information. Today, many of these repair tasks are still performed and documented with inefficient paper documents. Cognitive assistance systems have the potential to reduce costs, errors, and mental workload by providing all required information digitally. In this case study, we present an assistance system for object-specific repair tasks for turbine blades. The assistance system provides digital work instructions and uses augmented reality to display spatial information. In a user study with ten experienced metalworkers performing a familiar repair task, we compare time to task completion, subjective workload, and system usability of the new assistance system to their established paper-based workflow. All participants stated that they preferred the assistance system over the paper documents. The results of the study show that the manual repair task can be completed 21% faster and with a 26% lower perceived workload using the assistance system. [ABSTRACT FROM AUTHOR]

In the workshop scheduling problem, frequent disturbances lead to continuous and frequent rescheduling. This is detrimental to the optimal utilization of production resources, the maximization of production efficiency, and the minimization of operational costs. Therefore, finding an effective method to reduce frequent rescheduling is crucial for stable and efficient workshop operations. This paper introduces digital twin (DT) technology. Serving as a digital replica of a physical system, DT establishes an interactive connection between the physical entity and its digital counterpart. It has been applied in multiple fields. A disturbance evaluation method for scheduling mechanisms based on DT technology is proposed and studied in this paper. Firstly, this method evaluates the impact of disturbances by using a causal factor chart (CFC) and convolutional neural networks (CNN). Then, corresponding scheduling mechanisms are proposed based on the degree of disturbance impact. DT technology is used to provide data and model support throughout the entire process. Through the experimental verification, workshop disturbances were accurately evaluated by this method. Two unnecessary instances of rescheduling were avoided, resulting in a 66.3% reduction in the time to handle disturbances. The experimental results show that the proposed method can enhance the adaptability of scheduling mechanisms and contribute to a more agile response to disturbances. [ABSTRACT FROM AUTHOR]

Traditional geometry optimization of elevator fairings is only based on computational fluid dynamics simulations to find optimal structure parameters, and a large volume of data generated during the elevator operation is not utilized to optimize elevator fairings collaboratively. This paper proposes a digital twin-driven design framework to design the elevator fairing of the next generation. A digital twin model corresponding to the real elevator is first established via a computing platform, and a multi-objective optimization method like neighborhood cultivation genetic algorithms is employed to optimize the elevator fairing design. The effectiveness of the digital twin-driven design framework is demonstrated by the elevator fairing design, and the results show that compared with the unoptimized elevator fairing, the air drag and the lateral force are lowered by 18.1% and 11.2%, respectively, and the turbulence coefficient decreases from 0.478 to 0.451 after optimizing the elevator fairing. [ABSTRACT FROM AUTHOR]

Origami techniques derived from antique paper folding arts have been applied to solve engineering problems such as weight/space-saving structures and their rapid deployment for foldability. Recently, origami techniques' potential in mechanical reinforcement for structural designs has also been discussed. For example, the mechanical performance of origami tubular structures can be significantly improved compared with the circular and hexagonal tubes under lateral loading. In this paper, an origami-inspired tubular structure was applied as the infill pattern for additive manufacturing, and energy absorption performance under dynamic and static loadings was investigated. Fused filament fabrication was selected as the testbed for the origami-inspired infill pattern investigation. The samples with the origami infill pattern presented higher dynamic and quasi-static energy absorption performance than samples with grid or honeycomb infill patterns. The proposed structural reinforcement method can be expanded to crash-worthy structures, thin-wall structures, functional structures, and the design of lightweight, high-strength parts. [ABSTRACT FROM AUTHOR]

The vibration of the rolling mill has been a persistent issue affecting its safe and stable operation. To address the vibration problem in the F2 stand of a continuous rolling mill, this paper establishes a digital twin model of the rolling mill. Based on the digital twin model, a rolling mill virtual commissioning framework has been proposed to enhance the accuracy of real-time data and improve the utilization of production data, laying the foundation for reducing vibration during the operation of the rolling mill. In this process, we first construct a digital twin framework for the rolling mill, consisting of four levels: physical rolling mill, virtual rolling mill, twin data, and services. Next, an online data acquisition and virtual commissioning framework is established to achieve a state mapping from the physical rolling mill to the virtual rolling mill. Finally, using the digital twin model, the effects of real-time process parameter optimization are analyzed. The impact of process parameter optimization on the dynamic response of the rolling mill system is examined. The optimized rolling process parameters effectively reduce the vertical vibration of the rolling mill system. [ABSTRACT FROM AUTHOR]

In the present analysis, a new experimental pilot plant system for exploring resin-impregnated paper (RIP) bushing technology was conducted. Experimental and numerical studies were carried out on the resin infusion and impregnation processes in the paper condenser core of a RIP bushing. An innovative approach for the molding process (named molding method B) of a commercial RIP bushing was implemented. For this method, the homogeneity of the paper winding process was controlled precisely. The filling process was conducted by gravity due to the difference of heights between two vacuumed chambers and from bottom to top in the mold. The flow front position and infusion time were measured experimentally and used to obtain the axial permeability of the paper condenser core analytically and numerically. The results indicate that the molding methods have a significant effect on the RIP bushing quality, homogeneous filling, and impregnating process time. Also, it was found that homogeneity of the paper winding process and, consequently, uniform axial velocity of resin flow in the radial direction is the most effective factor to eject the air. Finally, it was recognized that the determination of axial permeability in the case of transient flow is novel in comparison with conventional procedures such as Darcy relation of steady flows. By decreasing the paper thickness from 0.3 to 0.2 mm, the permeability decreased from 8.84 × 10−10 to 4.52 × 10−10 m2. The microstructure of the core illustrates that the axial permeability of the crepe paper condenser core is considerably affected by the variation of the paper thickness. [ABSTRACT FROM AUTHOR]

The process of complex product assembly-commissioning has the characteristics of high flexibility and firm dynamics. To overcome the drawbacks of manual assembly, deploying automated and intelligent techniques can greatly boost efficiency, improve flexibility, and enhance the quality control. The human–robot collaborative (HRC) technology combines the advantages of human capabilities and the efficiency and precision of robots. However, current HRC technology lacks of perception and cognitive ability, especially in dynamic environments. Therefore, this paper proposed a digital twin-driven HRC assembly-commissioning framework. In this framework, a virtual-physical mapping environment for HRC is constructed. In order to improve the cognitive ability of robot units to tasks, a motion intention recognition approach is proposed which integrates the feature of part into human joint sequences. To improve the adaptability of the robot unit to tasks, the assembly-commissioning task knowledge graph is developed to extract the action sequence of the robot unit in a timely manner. Moreover, the deep deterministic policy gradient (DDPG) is used to adaptively adjust the robot unit movement path in the process of assembly-commissioning. Finally, the effectiveness of the proposed method is verified by taking a particular type of automobile generator as a case study product. [ABSTRACT FROM AUTHOR]

For large flexible parts with initial deformation, the springback deviation of a product often occurs with the release of the fixture constraints after assembly. Different final constraint states of product leads to different springback deformation. In order to solve the problem that the classical method of influence coefficient (CMIC) is single to the final constraint states of the product in the assembly deviation modeling of flexible parts, an improved method of influence coefficient (IMIC) based on unit displacement response is proposed in this paper, which can meet the assembly springback deviation analysis of the product under any final constraint states. On this basis, a modeling method of assembly deviation of large flexible parts is proposed, which can accurately and efficiently predict the assembly deviation of flexible parts with initial deformation. Through case comparison and analysis, the IMIC has the same calculation accuracy as the CMIC, and the analysis steps of deviation model based on the IMIC are reduced by 66.67% and the analysis time is shortened by 54.17%, which proves the efficiency of the method proposed in this paper. Compared with the CMIC, the method proposed in this paper is more applicable and universal. [ABSTRACT FROM AUTHOR]

Risk management has always been a trend in manufacturing related literature in the era of zero-defect manufacturing (ZDM). However, a gap still exists to present a holistic viewpoint of the integration for a product and its related processes involved during decision-making in manufacturing industry. The (knowledge-driven) integrated-decision support system indicates the opportunity by integrating the product design and manufacturing processes related risks in a manufacturing industry to make better decisions at the shop floor. It further proposes a direction towards development of a decision support system framework for their respective risks' identification as well as mitigation to enhance the quality, while minimizing time and cost. Over the years, risk identification has been considered well but risk mitigation has mostly been overlooked in the published literature. This paper scanned over a thousand papers from renowned journals published between 2005 and 2024. Currently, the evolution involved in the advancement of decision support tools for risk management has been reviewed by utilizing systematic literature review methodology. The study also provides a design overview, highlighting its features, pros, and cons of the existing methods which can be used for risk identification, prioritization, and mitigation in the development of a dynamic decision support system to aim (data-driven) zero-defect manufacturing (ZDM). Lastly, the paper discusses the current challenges and opportunities to lessen the manufacturing recalls in the industry, followed by phases of the proposed model. [ABSTRACT FROM AUTHOR]

The machining of monolithic components is prone to deformation, which causes a large amount of production resources to be wasted. Therefore, studying the process of initial configuration optimization method to reduce machining deformation is of great significance for the precision machining of monolithic components. In this paper, the concept and mathematical expression of the initial process configuration are proposed for aluminum alloy U-shaped cross-section stringer structural components. The initial configuration optimization problem is formulated with the initial process configuration as the variable and the objective of minimizing machining deformation. An iterative method is used to optimize the initial process configuration. The machining deformation after the optimized configuration was analyzed by finite element simulation and theoretical calculation, and the deformation data error of the two was less than 20%, which verified the correctness of the method proposed in this paper. Machining tests were carried out, and the results show that the proposed initial configuration optimization method can control the deformation of the U-shaped long truss parts within ± 0.06 mm/m, which is 80–90% less than that before optimization. This initial configuration optimization method has a positive effect on controlling machining deformation. [ABSTRACT FROM AUTHOR]

Advances in Additive Manufacturing (AM) technologies have made it possible to reduce the design and prototyping costs to a minimum especially for a low-productivity material like titanium. Titanium alloys are commonly and widely used alloys in the aerospace and biomedical sector due to their advantageous material properties. This paper is an evaluation study of factors affecting the productivity characteristics of Laser Engineered Net Shaping (LENS) titanium alloy (Ti-6Al-4 V) using face milling. Some of the productivity challenges associated with titanium such as rapid tool wear, poor surface finish, and high-power consumption are explored in this paper. All materials processed using AM face the same critical problem that the manufactured part requires a post machining since AM produces relatively poor surface finish. Machining trials are conducted using the combinations of machining parameters such as spindle speed of 800 and 1600 rev/min; feed rate of 50 and 100 mm/min; and a constant depth of cut of 1 mm, respectively. Titanium being a poor thermal conductivity material, the effect of coolant was investigated using wet/dry machining. Data related to the productivity factors and material behavior under a milling trial was recorded and analyzed. The obtained data from the trials include productivity factors such as Metal Removal Rate (MRR), power consumed, and the surface finish for each plate/trial. The power consumed in dry milling was observed to be lower than that in wet milling which is contrary to the observations from conventional wet milling. The paper concludes the trends observed for LENS titanium are opposed to the trends in conventional machining such as increasing cutting speed will result in lower cutting force and power consumed. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is a wide set of technologies that can be used for many different scopes. AM is now a well-integrated prototyping and development tool in most industrial endeavours, while proper end-product manufacturing has only seen very specific niche successes. Given the complexity of AM's matrix, which is full of discontinuities and non-trivial intercorrelations that play a relevant role in product design and development, it should not come as a surprise that not many end-product applications have succeeded in making use of it. This paper argues that understanding AM's complex matrix and correctly identifying suitable production niches for it are key elements of this issue, a topic for which existing literature and tools are scarce. The analysis of AM's status quo for end-product manufacturing and the review of existing approaches to integrate these technologies with product development are the basis used in this paper to propose a suitability assessment tool to fill this knowledge gap. [ABSTRACT FROM AUTHOR]

Various generations of scholars have proposed many material removal models for grinding processing. However, the stress conditions of the free surface and regular surface are different. The free-form models will encounter problems in practical application. To refine the stress distribution in the contact area during grinding, it is necessary to construct the elastic contact model for the workpiece profile. This paper uses dimensional reduction to introduce the double curvatures to approximate the varying curvatures of the free surface. So, the conclusions of classical elastic Hertz contacting theory can be applied to the model. We use differential thought to deduce the relation between the normal force and the maximum deformation depth of the contact region. Then, we obtain the boundary of the contact region. After dimensional reduction by Winkler theory, we propose the normal equivalent spring potential energy correction error terms. They compensate for the local stress based on the relationship between stress and deformation of continuous media. According to the boundary of the contact region obtained above, we carry out the differential stress distribution. This accounts for the dispersion effect of the convex surface on the force. Using stress-indicating film to show the local stress distribution, the results revealed that the stress distribution was consistent with that of the simulated contact stress distribution. The error was controlled within 0.078MPa. To verify the practicality of the contact model in grinding experiments, we derived the theoretical grinding depth by combining the Hammann linear grinding model. This paper compares the experimental results with the model results. It demonstrates the proposed algorithm's superior adaptability and practical application ability to the free surface. [ABSTRACT FROM AUTHOR]

The application of single-point incremental forming has been hampered by poor geometric accuracy due to problems such as suspending sheet back and difficult forming. In this paper, hydrostatic support and ultrasonic vibration-assisted single-point incremental forming is introduced to evaluate and optimize the formability of the proposed assisted process using the geometrical accuracy of the formed sheet as a criterion for process feasibility. According to the Box-Behnken Design experimental program, experiments on hydrostatic pressure, amplitude, frequency, and tool head diameter in relation to maximum errors are conducted, and the experimental results are analyzed by ANOVA and empirical modeling. The results show that frequency and tool head diameter have significant effects on the maximum error, and the coupling effect of static pressure and tool head diameter has a significant effect on the maximum error. Using the satisfaction function to optimize the process parameters, the maximum error is smaller when the value of static pressure is 0.058 MPa, the amplitude is 0.019 mm, the frequency is 25 kHz, and the tool head diameter is 15.7 mm. The optimum parameter combination has proven to be effective through five sets of validation experiments. The methods and conclusions presented in this paper can be useful for the study of hydrostatic support and ultrasonic vibration-assisted single-point incremental forming. [ABSTRACT FROM AUTHOR]

This paper presents a generalized approach for rapid prediction of scallop height distributions. This methodology introduces the theory of mesh surface conformal mapping, effectively reducing the complexity of scallop height distributions prediction through dimension reduction from 3D space to a 2D parameter domain. It can predict scallop height distributions consistent with the order of cutter contact (CC) points, making it suitable for any type of toolpaths. Building upon this foundation, a novel method for generating supplemental machining toolpaths on intricate surfaces is further elaborated. This innovative method proficiently eliminates uncut regions that are often overlooked during toolpath generation, enhancing machining accuracy and efficiency without compromising on toolpath intervals. Finally, the validity and practicality of the proposed methods are rigorously verified through a combination of simulation and actual machining experiments. The experimental outcomes reveal that, when compared to prevalent commercial machining simulation software, the rapid prediction method introduced in this paper achieves a noteworthy improvement in calculation efficiency by approximately 50%. Furthermore, in contrast to the conventional strategy of enhancing toolpath accuracy by narrowing intervals, the supplementary toolpath generation method presented herein achieves a significant reduction in toolpath length by over 25%. This approach significantly augments the applicability and flexibility of toolpath optimization; it has important potential and value for improving the efficiency and accuracy of milling intricate surfaces. [ABSTRACT FROM AUTHOR]

The process of high-speed and high-precision machining is highly dependent on the wear process of the tool, so it is necessary to obtain the accurate identification of the wear state of the tool and the timely prediction of the degradation trend through effective detection methods. However, the influencing factors of the real cutting process are complex and variable. The milling process is a complex spatial deformation process, accompanied by very high cutting accuracy requirements, and it is hard to use VB value, the currently popular singular linear indicator of wear state evaluation, to describe the current wear state of end mills precisely and difficult to make a valid decision proof for subsequent dynamic degradation trends. For these issues, a three-dimensional wear region reconstruction and calculation method for end milling cutters based on bi-sensor monitoring information is proposed in this paper, which can be accurately used to estimate the volume of current wear areas and give more reasonable predictions of future wear trends. Firstly, an in situ wear detection device with a bi-sensor based on an industrial camera and line laser scanner is designed, which can obtain the wear shape and depth information synchronously with high precision. Secondly, aiming at the problem of missing wear information due to uneven furring wear on the rear tool face of the end milling tool, this paper proposes a combined threshold segmentation method to extract the complete tool wear region, which improves the calculation precision of the wear region. Thirdly, the SFS algorithm, which integrates high-precision scale information from line laser data, is utilized to reconstruct the rear tool surface topography. This reconstruction allows for accurate estimation of the wear volume. Finally, the experiment results have shown that the wear volume can reflect the wear state of the tool more quickly and comprehensively compared with the traditional tool wear width standard, and it can provide early warning before the tool enters severe wear condition. [ABSTRACT FROM AUTHOR]

The heat transfer coefficient, including interfacial heat transfer coefficient (IHTC) and convective heat transfer coefficient (CHTC), plays a pivotal role in the thermal dynamics of hot gas forming processes. This parameter can determine the temperature field, thereby affecting the deformation and mechanical properties of the material to improve productivity. In this paper, we present an innovative experimental apparatus designed to measure the temperature evolutions of the aluminum specimen and the die during the hot gas forming processes. This apparatus is capable of simultaneously measuring IHTC and CHTC. Using the inverse finite element method, the simulated temperature histories are matched with empirical data and the best-fit values are adopted as indicative of IHTC and CHTC. This study identified the effects of contact pressure and die temperature on IHTC, as well as the impact of gas pressure on CHTC. In addition, a predictive model was developed to forecast the IHTC and CHTC at varying contact pressures and die temperatures with a prediction accuracy surpassing 0.95. By leveraging the predictive model presented in this paper, users can modulate contact pressure and die temperature based on specific production needs to achieve a targeted temperature profile. This method offers enhanced precision in managing the temperature field of the workpiece during hot gas forming experiments, thereby refining the temperature distribution. Moreover, it optimizes the formability and microstructural attributes of the material, ultimately leading to improved mechanical characteristics. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) enables the production of complex geometries that are not accessible by conventional processes. Fused deposition modeling (FDM) 3D printing is an important choice for many industries, particularly for additive manufacturing of microelectronic systems. The various physical properties of printing polymer materials, such as geometry, rheological behavior, and others, need to be taken into account in the printing process. In our study, a semi-crystalline polypropylene polymer PP is used in the FDM process, as it is characterized by deformability due to crystallization. We investigate the thermomechanical behavior of a semi-crystalline polymer PP (polypropylene) with different material deposition geometries ranging from a parallelepiped filament to a cylindrical filament in a numerical model developed. A coupling (to temperature vs. time evolution during printing) of solid mechanics, heat transfer, and crystallization kinetics equations was considered to build the Multiphysics numerical model capable of predicting temperature profiles, residual stresses, and degree of crystallization during the FDM process. The results obtained with the numerical model provide a reliable approach to predicting and adjusting the actual thermomechanical behavior of a printed electronics package. The values are calculated and compared to the six points in the two samples. The results show that the change in deposit shape resulted in a maximum deviation of 3.3 MPa for residual stress and 0.376 for the degree of crystallization, while a decrease was observed in the selected points with an average deviation of 1.81 MPa and 0.193 for residual stress and the degree of crystallization, respectively. This is due to the effects of the modification of the shape model on the temperature profile model, with the change in the 3D structures of the printed polymer material; the methodology presented in this paper allows the numerical model to be validated with an experimental study of the literature. The paper proposes future work and an experimental study to validate the results of the numerical model. [ABSTRACT FROM AUTHOR]

Robotic manipulators play an innovative role as a new method for high-precision, large-scale manufacturing of composite components. However, machining composite materials with these systems presents unique challenges. Unlike traditional monolithic materials, composites exhibit complex behaviour and inconsistent results during machining. Additionally, robotic manipulator as a machine tool often associates with stiffness and vibration issues which adds another layer of complexity to this approach. By employing a comprehensive analysis and a combination of quantitative and qualitative review methodology, this review paper aims to survey diverse properties of composite materials by different categories and their interaction with machining processes. Subsequently, a survey of manufacturing techniques for composite machining following with a review in various modeling practices to capture material machining behaviour under a systematic framework is presented. Thereafter, the reviewed literature examines the errors inherent in robotic systems, alongside ongoing research efforts in modeling to characterise robot behaviour and enhance its performance. Afterward, the paper explores the application of data-driven modelling methods, with a primary focus on digital twins, in enabling real-time monitoring and process optimisation. Finally, this paper aims to identify the gap in this field and suggests the potential routes for future research and application as well as their challenges. [ABSTRACT FROM AUTHOR]

During the five-axis flank milling process, the uncut chip area varies continuously with the cutter motion, which leads to a challenging issue for the geometric construction of the instantaneous uncut chip thickness (IUCT). In this paper, a novel approach to calculate the IUCT effectively considering the cutter runout effect is proposed. The element motion of the cutter extracted from the cutter location file (CLF) is described with one linear variable and two angular variables, which are necessary factors in the IUCT calculation of five-axis milling. The geometry relationship between cutter motion and IUCT has been analyzed, and the parametric expression of IUCT in five-axis milling can be deduced to predict the cutting force. The explicit five-axis IUCT expression facilitates a more comprehensive understanding of the key parameters in the cutting process, which could be helpful in optimizing the processing parameters. Compared to the numerical method based on true tooth trajectories, the time consumption of the proposed method is reduced greatly in the simulation. The experiment of five-axis flank milling is carried out, and the result reveals that the presented method can be well applied to the practical milling process. We believe that the IUCT model in this paper will promote the simulation and optimization system in five-axis machining. [ABSTRACT FROM AUTHOR]

This paper reviews the development of ultrasonic surface treatment techniques, including ultrasonic shot peening, ultrasonic peening treatment, and ultrasonic surface rolling techniques. Ultrasonic surface treatment techniques are effective technologies to induce severe plastic deformation and improve the mechanical properties and surface integrity of components. In recent years, numerous researchers have explored various ultrasonic surface treatment techniques to improve surface integrity using available facilities and equipment. Besides, due to the limitations in industrial applications, these techniques are expanding to improve various surfaces with specific geometric shapes. Despite the wide range of techniques in this field, this review focuses solely on industrial applications based on cold working. This article briefly explains each technique and its advantages and disadvantages compared to other techniques. Applications of these techniques are presented with descriptive illustrations, and their effects on the surface characteristics of ferrous and non-ferrous materials are summarized. Based on this, the existing shortcomings and limitations are discussed in this paper, and prospects for ultrasonic surface treatment approaches in future studies are considered. The present review enhances the knowledge of ultrasonic surface treatment techniques and provides a quick reference for the appropriate usage of each technique in relevant applications. [ABSTRACT FROM AUTHOR]

Improving the mixing homogeneity of heterogeneous powder in real time plays an essential role in ensuring the forming quality of functionally graded materials (FGM) produced by laser-directed energy deposition (L-DED). In order to achieve a high performance of material composition and proportion control as forming FGM parts, this paper investigates the mixing mechanism of several typical powders including 316L and NiCrCoAlY used for the L-DED process driven by compressed gas. An innovative pneumatic powder mixer is designed and optimized by the CFD-DEM simulation method to analyze the mixing characteristics of heterogeneous particles. To improve the real-time mixing homogeneity of different mixing ratios in the conveying process, mixing experiments based on differences in powder properties were conducted by the additive-subtractive composite machining center, and a coefficient of variation method was proposed to describe the mixing homogeneity of non-uniform powders. The results of micro-morphology and EDS indicate that the mixing quality of the two-phase flow is significantly enhanced with the four 45° compression inlets and 2 m/s inlet velocity structure. The results show that the numerical analysis method proposed in this paper can effectively describe the mixing law of heterogeneous particles, and the compressed air intake velocity should not exceed the initial two-phase flow velocity. The horizontal and vertical components generated by the compressed air intake at 45° are more conducive to the formation of favorable perturbations to the two-phase flow, and the number of four and eight compressed air intakes that act uniformly on the flow field is more appropriate. After a certain period of time, the two-phase flow with low error of mixed powder quality can be produced continuously. The mixed powder quality is obviously improved after the disturbance of compressed air intake. The mixing uniformity of powder with low spherical particle proportion can be effectively improved by increasing the preset mixing proportion of non-spherical particles. [ABSTRACT FROM AUTHOR]

Tool design is very important in the modern manufacturing industry. However, the traditional tool design process often has a heavy workload, which reduces the production efficiency of tool manufacturing enterprises. To deal with these problems, this paper proposes an integrated tool design platform to solve the problems in tool design. The tool-integrated design platform uses parametric modeling technology to allow design engineers to quickly create a geometric model of the tool by setting key parameters. The platform also introduces cutting simulation technology. Design engineers can perform simulation analysis on the platform and evaluate its performance and feasibility by simulating different tool design schemes. At the same time, this paper also uses cloud database technology to realize the function of multi-person remote collaborative design. In addition, the platform also uses genetic algorithm to optimize the cutting depth, cutting width, feed rate, and spindle speed of the tool with the minimum three-way milling force as the goal to guide the actual processing and production. In summary, by introducing technologies such as parametric modeling, parametric simulation, and cloud databases, enterprises can effectively solve the problems in the tool design process. The design time cycle is greatly shortened, and multi-person remote collaborative design becomes more convenient. This will significantly improve the enterprise's production efficiency and help the tool's precise design. [ABSTRACT FROM AUTHOR]

As an advanced high-performance material, carbon fiber-reinforced composites have become one of the most widely used and important materials among all composites, due to their lightweight, high modulus, high strength, low thermal expansion, and corrosion resistance. They are widely used in aerospace, military weaponry, renewable energy, and sports equipment. As a non-contact processing technology, laser processing has many advantages in the machining of carbon fiber-reinforced composites. However, the significant differences in thermal-physical properties between carbon fibers and the resin matrix present substantial challenges for laser processing. During the laser processing of CFRP materials, a heat-affected zone typically forms, which not only affects processing quality but also reduces processing efficiency. Therefore, reducing and eliminating the heat-affected zone has become a critical issue in the laser processing of CFRP materials. In recent years, extensive research on CFRP laser processing technology has been conducted both domestically and internationally, and this paper will provide a summary. This paper conducts a comprehensive and in-depth study of laser processing of carbon fiber composites and explores the effects of different parameters on the heat-affected zone. Additionally, this paper describes the treatment of carbon fiber composites using multi-energy field-assisted laser processing technology, as well as the modeling and optimization of process performance. Finally, an outlook on the development trends of laser processing of CFRP is provided. [ABSTRACT FROM AUTHOR]

The current research on theoretical modeling of the surface roughness of brittle materials generally regards the tool as a rigid body. Incorporating tool factors into theoretical models of surface roughness is challenging because the influence of tool-workpiece coupling contact on surface roughness remains unclear. This paper investigates the tool-workpiece coupling contact mechanism using contact mechanics analysis: collision contact between the rake face and the material, adhesive contact between the cutting edge roundness and the material, and hertz contact between the flank face and the material. The tool-workpiece coupling contact causes the material to fracture and break, and the tool undergoes collision wear, adhesive wear, and abrasive wear. The formation of pits is attributed to the tool's cutting action on the workpiece, whereas the presence of hard convex peaks is a consequence of the workpiece's reverse cutting into the tool. A quantitative description of hard convex peaks and pits on machined surfaces was based on contact mechanics, fracture mechanics, and tribology. A novel theoretical model is developed for characterizing the surface roughness of brittle materials. Turning verification experiments were carried out using different tools, workpieces, and tool parameters. The predicted values and experimental measurements are similar and have the same trend, indicating that the model is accurate. This paper is the first to consider both the tool and the workpiece as the influencing objects of the surface roughness of brittle materials, and it innovatively incorporates tool wear and tool material properties into the parameters of the theoretical model of surface roughness. It offers a fresh perspective on predicting the theoretical surface roughness model for brittle materials. [ABSTRACT FROM AUTHOR]

Data not only plays an essential role in traditional shopfloor management, but it is also becoming even more important in Industry 4.0, particularly due to the increasing possibilities offered by new digital and data technologies and developments. In this context, the literature often refers to digital shopfloor management, the next generation shopfloor or other evolutionary synonyms. This raises the question of how to differentiate the content of data-oriented shopfloor management from digital shopfloor management. This paper discusses the state of the art — in terms of both data and digital perspectives — using a systematic literature review. Due to the complexity of the topic, three different levels of consideration — technology, organisation and people — are examined and discussed. Existing conceptual approaches are analysed in terms of conclusions and research gaps. It was found that the area of technology, including dedicated applications, is very well represented and researched in the literature. In comparison, there are larger research gaps in the other areas of organisation and people, which could be a possible reason for the lack of implementation of digital shopfloor management in practice. There is also a lack of holistic approaches that consider all three levels simultaneously and provide an overarching concept of maturity as a guideline, as well as taking into account the increasing trend towards value stream orientation. Apart from the research gaps, this paper could also define the term data-oriented shopfloor management and distinguish it from digital shopfloor management. [ABSTRACT FROM AUTHOR]

In recent years, nickel-based composite coatings have been widely used in aerospace, petrochemical, energy industry, and other fields due to their excellent wear resistance, corrosion resistance, and thermal stability. As a surface strengthening technology, laser cladding has the advantages of low dilution rate and heat-affected zone, and has obvious advantages in the preparation of nickel-based composite coatings. In this paper, the research progress of Ni-based composite coatings prepared by laser cladding is reviewed. Firstly, the characteristics and properties of the new material system of nickel-based composite coating are summarized. Secondly, the factors affecting the properties of nickel-based composite coatings were analyzed. The influence mechanism of cladding powder and process parameters on the microstructure, mechanical properties, and mechanical properties of the coatings was discussed in detail, and the measures to improve the properties of nickel-based composite coatings were proposed. Finally, the problems faced by the preparation of nickel-based composite coatings by laser cladding are introduced, and the future development trend is prospected. This paper will help to quickly understand the development status of this field and provide reference for solving practical production problems. [ABSTRACT FROM AUTHOR]

In recent years, manufacturers have increasingly applied automation techniques to enhance efficiency and remain competitive. Material handling is an essential activity in any production process. Its effectiveness has a significant impact on production costs. Automated guided vehicle (AGV) systems have become a strategic tool for factories and automated warehouses. They can reduce production costs and improve delivery times in a competitive business scenario. One of the main problems encountered in managing AGVs is the dispatching decision. The present paper proposes a vehicle dispatching system based on a multi-attribute cascaded fuzzy system with a state-space-based Petri net model to predict the future states of the factory. This work aims to reduce the production system's makespan and/or tardiness values. Additionally, the paper presents one simulated factory scenario to evaluate the proposed fuzzy system against five other dispatching methods. The statistical validation results of the simulations show a 97% confidence level in the hypotheses of this work. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the application of machine learning (ML) techniques for predicting the spatiotemporal evolution of thermal fields during additive manufacturing (AM) processes. AM, also known as three-dimensional printing, has gained significant attention in various industries due to its potential for rapid prototyping and customized production. However, accurately predicting and controlling the thermal behavior during the AM process is crucial for ensuring the quality and reliability of the printed components. Traditional physics-based models (PBM) often face challenges in capturing AM's complex dynamics and inherent uncertainties. In recent years, ML algorithms, particularly neural networks (NNs), have shown promising results in predicting the thermal field evolution. This paper reviews the existing literature and highlights the critical methodologies and recent advancements in NN-based predictions. It explores novel perspectives by discussing the hybrid modeling approaches, including the combination of PBMs with NNs. This overview highlights the evolving landscape of predictive techniques in the context of AM and underscores the potential for enhancing accuracy and efficiency in thermal field prediction. The paper also discusses the challenges and outlines future directions for enhancing the accuracy and efficiency of thermal field prediction in AM. By synthesizing current research, this overview will guide researchers and practitioners toward leveraging NNs effectively for optimizing thermal management in AM processes. The insights presented underscore the transformative potential of NN predictions in advancing AM capabilities. [ABSTRACT FROM AUTHOR]

Ball screws are subjected to complex loads during machining processes, which affects the position accuracy of the feed shaft of machine tools. The lack of a reliable model for analyzing the deformation of the ball screw, coupled with the unclear relationship between the deformation of the ball screw and the position error of the feed shaft, makes it challenging to accurately predict and compensate for the position error. The objective of the present research is to investigate the correlation between the deformation of the ball screw and the position error of the feed shaft to improve the accuracy of the machine tool. First, this paper establishes a FEM model to explore the loading and deformation of the ball screw. Secondly, a method for predicting position errors based on the deformation of the ball screw is proposed. Finally, the ball screw-loading test device is used for the position error compensation experiment to verify the reliability of the prediction method. This paper serves as a reference for understanding the generation mechanism of position errors in machine tool feed systems. [ABSTRACT FROM AUTHOR]

The unequal pitch end milling cutter can change the feed per tooth and the cut-in and cut-out period of each cutter tooth by changing the distribution of the pitch of the end milling cutter so that the energy in the milling frequency domain is dispersed to achieve the purpose of reducing the milling vibration. Because the amplitude of vibration in the milling process is closely related to the milling force, this paper establishes the instantaneous static milling thickness model based on the real trajectory of the milling edge according to the milling process of the end milling cutter with unequal pitch and establishes the instantaneous dynamic milling thickness model based on the regeneration effect, on which the instantaneous milling force model is established. At the same time, the relationship model of milling force coefficient is established according to the average milling force method. From the relationship model of milling force coefficient, the linear relationship between average milling force and average feed per tooth is obtained. Then, the finite element simulation method is used to simulate the actual milling process of milling typical material Al7075-T6 with unequal pitch end mill, and the milling force coefficient is fitted by the simulation results. Finally, the accuracy of the milling force model and the finite element model has been validated through experiments, and the feasibility of calibrating the milling force coefficients through finite element simulation method has been demonstrated. The milling force model of unequal pitch end mill and the method of calibrating the milling force coefficient by finite element simulation proposed in this paper will provide a theoretical basis for the study of unequal pitch end mill in vibration reduction. [ABSTRACT FROM AUTHOR]

Because of the high manufacturing precision and efficiency, the segmented grinding and ball-end milling method is often used in the finish machining process of the variable screw rotor instead of form grinding. To study the process of the rotor ball-end milling and improve the precision of the machining process simulation, the accurate tool-workpiece surface contacting model and cutting force model must be established first. In this paper, the normal cutting depth iteration algorithm was proposed to study the time-varying mapping relationship between the cutting edge trajectory and the workpiece. And the normal cutting depth was used instead of the cut-in angle, cut-out angle, and undeformed chip thickness to establish the cutting force model. The influence of the transitional surface topography on the undeformed chip thickness in the cut-in and cut-out process was calculated by this method. Then, the cutting force of the screw rotor cut-in process could be simulated precisely in the finish cutting process. In this paper, the normal manufacturing error of the rotor surface and cutting force of the screw rotor were measured, and the results showed that the experimental data and the simulation data were within 15%, which proved that the method could accurately simulate the cutting force and surface topography in the ball-end milling process. [ABSTRACT FROM AUTHOR]

The 3D inspection process based on the use of optical sensors is more widely used for industrial applications, due to their great ability to scan the entire surface in a short time. Laser-plane sensors mounted on coordinate measuring machines (CMMs) are commonly used for high-precision inspection. However, measurement quality is affected by the sensor path, defined primarily by the sensor orientation and position. Executing the scan path on the machine is time-consuming, and potential collision problems can occur. In this context, the aim of this paper is to develop a 3D scan simulation tool to evaluate a given scan path in terms of visibility and quality. Scanning quality is first investigated and evaluated experimentally depending on the configurations of the laser-plane sensor relative to the part geometry. The developed simulator is therefore based on the qualification results. The principle of the simulator is formulated by functions expressing visibility and quality conditions relative to scanning distance and angle. The path simulator is set up by visualizing the two conditions on facets of the part surface, and the quality is then estimated through the corresponding function. A case study is presented to illustrate the proposed simulation tool for scanning a test part defined by its CAD model with a given sensor path. The results are compared to real scans obtained from the sensor. This study demonstrates the effectiveness of the proposed simulation tool for predicting and estimating measurement quality. The outcome of the presented research in this paper has to be used as a predictive tool to evaluate scan paths in order to scan industrial parts with the required quality. Its integration into CMMs enables accurate anticipation of scanning results, thereby enhancing operational efficiency. [ABSTRACT FROM AUTHOR]

Due to their high hardness at elevated temperatures and chemical stability, alumina-based ceramic cutting tools have been successfully applied in the machining of ferrous materials, especially quenched and tempered steels. Their low fracture toughness, however, makes it difficult to finish them by grinding, as cracks and defects can occur. In addition, its application in machining processes demands appropriate edge preparation to avoid tool failure. Within this context, the paper aims to demonstrate the applicability of an experimental Al2O3 + MgO ceramic cutting insert in hard turning. For this, grinding tests were performed to determine the most appropriate conditions to improve its surface and edge quality. The effects of cutting and feed speeds, grinding wheel bonding material, and abrasive grain size were investigated. Moreover, different cutting-edge geometries were prepared in this tool material and tested in turning a hardened AISI 4140 steel (50 HRC) to determine their performance regarding tool life and workpiece roughness. The results demonstrated that a finer grinding wheel (D15) combined with high cutting (60 m/s) and feed (10 mm/min) speeds leads to the lowest surface roughness and edge chipping. In addition, both symmetric (Κ = 1) and asymmetric (Κ = 2) edge roundings led to higher tool lives in hard turning in comparison to a single chamfered tool, as they contributed to better load distribution in the cutting region. The paper provides information for the manufacture and application of alumina-based ceramic cutting inserts in the metalworking industry, as it disseminates good manufacturing practices and recommendations for appropriate cutting-edge geometry. [ABSTRACT FROM AUTHOR]

As a cutting-edge additive manufacturing (AM) technology, the selective thermoplastic electrophotographic process (STEP) has opened up possibilities for mass production with its combination of real engineering plastics and potential high part quality. To improve the accuracy and fidelity of STEP for the most demanding applications, this paper proposes a novel method encompassing both pre-processing and in-process dimensional compensations. Iterative compensation before production is achieved through physics-driven simulation, resulting in input masks that better match the required dimensions at the design level. Layer-wise compensation is implemented during the production process through the laser profiler system, thereby suppressing the accumulation of surface unevenness during printing. With the compensation method proposed in this paper, the maximum distortion during simulated printing is decreased by 86.2%, and surface unevenness is effectively controlled during the printing process. [ABSTRACT FROM AUTHOR]

The proposed paper uses Taguchi design of experiments and topology optimization to design a low throat angle and lightweight structure of an open gap (C-frame) stamping press. First, finite element analysis was used for discussing the effects of frame structure deformation by various parameters, such as upper round corner (R1), eccentric distance of upper round corner (L1), throat depth (K), lower round corner of throat (R2), and eccentric distance of lower round corner of throat (L2). With throat angle as the quality objective, we conducted single-objective optimization using Taguchi's smaller-the-better formula. The optimal values of the quality objectives were as follows: R1 was 60 mm, L1 was 30 mm, L2 was 340 mm, and R2 was 48 mm, the resulting throat angle of which was 0°1′18.99″. The throat angle resulting from this parameter combination in the static analysis with 44% force area was 0°1′18.50″. The weight of the frame was approximately 5971 kg. We also confirmed the influence of the four process parameters on the quality objectives and their mathematical relationships using analysis of variance (ANOVA) and multiple regression analysis. Next, LSM (level set method) topology optimization was used to create an optimized structure. The analysis of the optimized structure using LSM showed that the deformation with 100% force area increased by 2.6%. However, the throat angle decreased by 0°0′0.78″, and the mass of the machine dropped by 444 kg. The proposed paper shows the process of using a combination of optimization methodologies to create an optimal structure, and the results show that the proposed methodology can improve not only throat angle but also structure weight. [ABSTRACT FROM AUTHOR]

Plug & Produce aims to revolutionize manufacturing by enabling seamless machine integration into production processes without extensive programming. This concept, leveraging multi-agent systems (MAS), offers increased flexibility and faster production ramp-up times after reconfiguration. As automated manufacturing moves towards greater human integration, this paper addresses safe operation within the Plug & Produce concept. The main safety challenge arises from autonomous decision-making, as agents in the MAS lack awareness of the risk consequences of their behavior. Additionally, the difficulty of perceiving the system's exact behavior leads to the implementation of overly restrictive safety measures. This limits the system's flexibility and ability to make decisions for efficient production. This paper proposes a method utilizing multi-agent control to conduct automatic safety analysis and reason task allocations to avoid risks. The method's benefits are the generation of control actions that comply with safety requirements during operation, eliminating the need for overly restrictive safety measures and allowing more effective equipment utilization. The method's benefit is illustrated through a manufacturing scenario with two different configurations: one using a hazardous machine and the other using a less hazardous one. Formal verification using the model checker NuSMV demonstrated that safety requirements were satisfied in both configurations, without the need for manual modifications of the safety control system after reconfiguration. The results for this specific manufacturing scenario showed that there are more reachable states (20 states) in the safer second configuration, compared to the first configuration (16 states). This means that the presented control strategy dynamically adjusts the system's behavior to confirm safety. Hence, this method maintains safety without fixed safety rules that limit the operations. [ABSTRACT FROM AUTHOR]

The kraft manufacturing process is the main pulping process in the paper industry. The kraft chemical recovery process is an efficient technology that enables the recycling of the pulping chemicals and the generation of electrical power. However, this process presents substantial issues related to energy consumption and environmental emissions. One of the main fundamental elements of the kraft process is the lime kiln. Lime kiln gas consumption, SO2, and NOx air emissions are key factors from the energy saving point of view (i.e., energy efficiency) and environmental pollution in this industrial process, respectively. Knowledge of the process variables involved in a lime kiln and how these are related to gas consumption and air emissions is essential to predict the kiln's behavior and minimize its environmental effects. The aim of this research study is to build a regression model for each one of the three prime variables (gas consumption, SO2, and NOx emissions) of a lime kiln employed in the paper manufacturing process using the multivariate adaptive regression splines (MARS) method in combination with the artificial bee colony (ABC) technique. These two statistical learning techniques were combined, thereby obtaining an easy-to-interpret mathematical model with a high goodness-of-fit. A coefficient of determination greater than 0.9 is obtained for all the modeled variables. Moreover, the particular contribution or importance of the input variables in each model is also calculated. The results thus obtained are a useful instrument to gain a better understanding of the dynamics of the lime kiln and the involvement of the process variables in gas consumption and gas emissions. [ABSTRACT FROM AUTHOR]

This paper investigates the cutting mechanism of stone–plastic composite through orthogonal cutting experiments of finite element simulations. In this work, special attention was given to chip formation and morphology, cutting force, temperature, and surface roughness. Four main types of chip morphology where modeled: cracking chip, element chip, segmental chip, and ribbon chip. The workpiece surface was smoothest in the case of ribbon chips, followed by segmental, element, and cracking chips. Heat generation, depth of cut, and cutting forces were directly proportional to one another. Experimental results and simulation results were in good agreement, confirming that the simulation model developed herein can be used for further investigation of orthogonal cutting processes. [ABSTRACT FROM AUTHOR]

The contact angle (CA) of a water droplet on the polished aluminum surfaces is usually between 60° and 90°. This paper discusses a tuned bulk micro-manufacturing approach for transforming the surface topology of aluminum simultaneously at the micro- and nano-length scales, thereby significantly influencing its wetting characteristics. The approach is cheap, easy to implement, and scalable. The treated aluminum surfaces appeared like roughly polished surfaces at the macroscale and were found to be robust and non-toxic. They exhibited a paper towel effect by showing extreme surface wettability (CA of zero) to many industrial liquids, i.e., wetting on these surfaces is only a function of the surface roughness but not the fluid type. This extreme wetting ability to multiple liquids (or ultra-omniphilicity) was generated by sequentially creating a sub-surface micro- and nano-cavity architecture with nano-cavities within the embryos of micro-cavities interconnected by a network of micro-grooves. [ABSTRACT FROM AUTHOR]

Drilling is an essential process in the construction of aircraft panels made from composite/metal stack materials, and it has a considerable impact on the performance of the aircraft during flight and its overall lifespan. Among CFRP/Al/Ti, CFRP/Ti, and CFRP/Al stacks, CFRP/Al panels are widely used in the aviation industry. This paper examines in detail the developments made in the drilling of stacks made of carbon fiber reinforced polymer (CFRP) and aluminum (Al), with the goal of determining how different machining parameters affect the quality of the holes. The primary requirements for aircraft components are to attain a low level of hole surface roughness, minimize burr heights, reduce the diameter difference in stack-up, and minimize delamination. The subject matter encompasses a wide range of tool shapes, materials, drilling parameters, and innovative methods of cooling and coating, all with the goal of reducing hole damage and improving quality. In addition, the paper examines several forms of hole damage and presents modern methodologies for their quantification. This review study aims to develop a reliable standard for achieving accuracy, optimal productivity, and reducing harm in the drilling procedure of CFRP/Al stacks in aerospace applications. Future works on analysis of bond strength, hardness, and coefficient of friction of coated drill bits and application of nano fluid-based coolants may further enhance the drilling quality. [ABSTRACT FROM AUTHOR]

In this paper, a non-supervised technique for on-line paper characterisation is presented. The method uses self-organising maps (SOM) and texture analysis for clustering different kinds of paper according to their properties. A light-through technique is used to get pictures of paper. Then, effective texture features are extracted from greyscale images and the dimensionality of the feature data is reduced with SOM allowing visual analysis of measurements. The method makes it possible to implicitly extract important information about paper formation. The approach provides excellent results. A classification error below 1% was achieved for four quality classes when local binary pattern (LBP) texture features were used. The improvement to the previously used texture features in paper inspection is huge: the classification error was reduced by over 40 times. In addition to the excellent classification accuracy, the method also offers a self-intuitive user interface and a synthetic view of the inspected data. [ABSTRACT FROM AUTHOR]

Human fingers possess compliant contact interfaces with predetermined compliance properties. Replicating these compliance properties in robotic limbs, particularly anthropomorphic hands, can significantly impact grasp stability and contact area. To address the limitations of homogeneous layers of soft material commonly used in anthropomorphic hands, this paper proposes optimizing differentiated structures to design soft pads, which consist of a continuous external layer (skin) coupled with an internal layer featuring voids. To achieve the desired compliance properties replicating those of human fingers, the paper introduces five distinct patterns for differentiated structures, along with their corresponding finite element analysis (FEA) models. Subsequently, by formulating an appropriate optimization function, the shapes of these patterns have been optimized to match the compliance of the human finger, and it has been demonstrated that one of the proposed and optimized pads closely approximates this target through the proposed methodology. The results affirm that this approach offers an effective solution for designing soft pads whose behavior needs to be aligned with the compliance of a specific target. [ABSTRACT FROM AUTHOR]

This paper examines an innovative approach to the automated inspection of turbine blades in power generation systems. By integrating point cloud generated from computer-aided design (CAD) with iterative methods, this methodology aims to improve the efficiency and accuracy of the inspection process. The combination of theoretical blade geometry data, captured via CAD point clouds, with advanced algorithms derived from iterative methods, allows for a rapid assessment of the blade's condition. This approach has the potential to reduce inspection times, increase assessment accuracy, and detect anomalies at an early stage. The paper explores in detail the key aspects of this method, including the creation and alignment of CAD point cloud with real blades, the application of iterative methods to detect degradation and anomalies, and the preliminary results obtained from specific case studies. However, challenges remain, such as the quality of input data and the need to develop iterative models specific to each application. Future prospects include the refinement of data capture techniques, the exploration of new iterative methods, and the integration of machine learning for even more advanced automation. Overall, this approach represents a significant advance in the field of industrial maintenance, enabling proactive and efficient management of turbine blade inspection and maintenance. It offers advantages in terms of cost, speed, and reliability for maintaining the sustainability and performance of power generation systems. [ABSTRACT FROM AUTHOR]

In order to realize CNC incremental forming of unequal height sheet metal parts with large forming angles on both sides of the sheet metal part, a three-stage incremental forming method is proposed. In this method, the sheet metal parts are inclined to the required angle during the forming process, and in order to ensure reasonable material flow during the forming process, the forming toolpath adopts the inclined forming toolpath, the contour line forming toolpath, and the equal interval parallel downward forming toolpath, and the algorithms for constructing the forming model and forming toolpath for each stage are also given. The case studies of the algorithm show that the proposed algorithms can generate the required forming model and forming toolpath. And three different forming methods of numerical simulation and forming experiments had been conducted; the results show that the forming method proposed in this paper is compared to the traditional two-stage and three-stage forming methods, the minimum thickness is large about 0.119 mm and 0.125 mm, the difference between the thickness is reduced by about 0.101 mm and 0.114 mm, the average profile deviation is reduced by 0.077 mm and 0.131 mm, and no bulging phenomenon occurs, which indicates that the profile dimensional accuracy of the sheet metal parts obtained by the forming method proposed in this paper is better, the minimum thickness is larger and uniformly distributed, and the forming quality is better. [ABSTRACT FROM AUTHOR]

The design process of automotive trimming die is very complicated, time-consuming, and error-prone process because of the complex geometric shape of the part surfaces and the trimming lines. This paper presents a systematic methodology for intelligent design of automotive trimming die. Template subtraction and bounding volume strategy (TSBV) is presented to unify the design process of blades in pad, punch, and trimming inserts. The novel horizontal and vertical offset algorithms are developed to construct the quality-derived surfaces based on geometric offset mapping (DS-GOM) quickly and stably, which are applied to generate the bounding surfaces of the template solids in TSBV. Finally, a robust and intelligent design system for trimming die of automotive panel is implemented on NX platform in this paper. And the intelligent system is adopted to design the trimming die for the actual and classical automotive panels to verify the effectiveness and stability of the developed system. Compared with traditional method, the generated surfaces by DS-GOM have the smooth transition which can improves the robustness of developed system. Case studies and industrial applications have demonstrated that the system can improve the design efficiency by 74.2% compared with generic design system. [ABSTRACT FROM AUTHOR]