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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]

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 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]

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]

In high-speed milling, the machining system is affected by a chatter resulting from the dynamic interaction between the tool and the part, which can cause harmful effects on the tool and the machined surface of the part. Chatter occurs more frequently for the milling of thin-walled parts due to their low stiffness. In addition, the dynamic characteristics of thin-walled parts vary along the tool path. The dynamics of the part are therefore the dominant factor that should be considered in the modeling and the study of the milling process and must be performed in 3D, where the third dimension is the tool position. This paper studies the milling stability of Al 7075-T6 thin-walled parts during high-speed milling considering the variation of dynamic characteristics and develops three-dimensional stability lobe diagrams of the spindle speed, axial depth of cut, and tool position. The dynamic equations of motion are solved numerically using semi-discretization method. Modal parameters of the tool and the part were extracted experimentally by modal tests. Then, cutting tests were conducted to validate the established model by measuring the machined surface roughness which is used as a criterion for detecting instability. The experimentally obtained results correspond well with the predicted stability limits. Moreover, the influence of different cutting parameters on the machining stability along the tool path was investigated. It is found that the variable spindle speed improves significantly the cutting process, and the best selection of feed per tooth impacts positively on the machined surface quality. [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]

This scientific paper provides a comprehensive overview of the current state of research concerning the application of additive manufacturing (AM) technology, especially the fused filament fabrication (FFF) and fused granular fabrication (FGF) methods, where robotic manipulator systems are applied in fabrication processes. To achieve this, a Systematic Literature Review (SLR) was conducted to identify, select, and evaluate the most relevant research. A total of 63 papers sourced from the most relevant scientific database covering the period from 2019 to December 2023 were thoroughly analyzed and synthesized. The examination, analysis, and assessment of these papers provide insights about the integration of the AM processes with robot manipulator technology, presenting the types of polymers, blends, and polymeric matrix composites that are processed using this advanced technology. This paper highlights and discusses current gaps in this area and proposes future research directions, emphasizing the potential enhancements in flexibility, quality, consistency, productivity, safety, and cost-effectiveness in AM facilitated by robot-assisted systems. [ABSTRACT FROM AUTHOR]

The intelligent service of the digital twin machine tool provides convenience for the human operation interaction in the machine tool, and the real-time operation interaction between the human and the machine tool has high requirements for the real-time machining model simulation algorithm. Firstly, this paper proposes a simulation method based on the combination of augmented reality (AR) and digital twin of machine tool machining virtual-real fusion. Secondly, to improve the real-time interoperability between human and machine tools in the AR virtual-real fusion machining process, this paper proposes a fast Dexel model generation method based on binary tree space segmentation. The method is based on the 3D model of the workpiece preprocessing to generate a one-way Dexel model of the binary tree storage structure, using the tool and the workpiece overlap envelope in the binary tree structure to determine the interference region, and ultimately calculating the intersection line between the one-way generation line and the tool geometry to get the model of the workpiece after cutting. By analyzing the real-time performance of the algorithm, the algorithm satisfies the simulation calculation of Dexel models of different scales. Finally, through the example of real-time interactive operation between human and machine tool AR, the results show that the average display frame rate of this algorithm in the machining process reaches 55–60 frames, and the parameter error between the model after virtual machining and the actual machining model is within 1.3%. At the same time, 100 people were randomly selected to carry out AR interaction training, and the real-time performance experience of AR virtual-real fusion machining was comprehensively evaluated, and the results showed that the system can meet the real-time demand of interaction operation of most participants. [ABSTRACT FROM AUTHOR]

Since it is difficult to obtain 3D micro-electrodes, simple micro-electrodes with round or rectangular cross-sections are used when performing layer-by-layer scanning EDM to machine 3D micro-structures. This process can process 3D micro-structure, which has deficiencies of complicated technical process and low processing efficiency. In the study, copper was used to fabricate 3D micro-electrodes by micro-milling. Using a reciprocating processing method, micro-EDM was conducted with the 3D micro-electrodes to obtain 3D micro-structures. This method had the advantages of high processing efficiency and a simple technical process. The above work is the main content and novelty of this paper. The paper detailedly studied the effects of the stand-off distance and flushing quantity of dielectric fluid on the machining quality of 3D micro-structure. Furthermore, the effects of rough machining and finish machining on the machined surface were also analyzed. Finally, with flushing quantity of 0.3 L/min, stand-off distance of 300 μm, the 3D micro-structures with 5 μm dimensional error were machined in 304# stainless steel by applying 3D micro-electrodes in micro-EDM, which had good processing efficiency and processing accuracy. [ABSTRACT FROM AUTHOR]

Injection molding is in high demand in several industries due to its efficiency and versatility. Quality control plays a crucial role in ensuring the excellence of plastic products during injection molding. However, the phenomenon of weld lines has persisted due to the susceptibility of melt flow in the mold cavity for independent or multiple related parameters. This paper presents a comprehensive review of recent advances in minimizing weld lines during injection molding. This review study is categorized into four parts, namely, (1) causes of formation, (2) influencing factors and mechanisms, (3) numerical prediction methods, and (4) improvement methods for weld lines. In the end, based on the findings summarized in this review paper, future research directions for optimal control of weld lines are discussed. [ABSTRACT FROM AUTHOR]

This paper provides a critical overview of experimental and computational studies conducted on additive manufacturing (AM) or 3D printing using bimetallic alloys. The review acknowledges the complexity introduced by mechanical interactions and significant interface anisotropies in multi-material AM, making the mechanisms of phase change and microstructure evolution more intricate. Various computational models, such as density functional theory (DFT), phase field, and finite element models, employed in the study of 3D printed bimetallic materials are discussed. The paper highlights the importance of future research in developing quantitative predictions that can simulate and forecast microstructure formation during the AM process. By incorporating computational modeling, this review underlines the potential for overcoming challenges associated with the intricate interactions between different materials in multi-material AM (MMAM). [ABSTRACT FROM AUTHOR]

Currently, the standard method of programming industrial robots is to perform it manually, which is cumbersome and time-consuming. Thus, it can be a burden for the flexibility of inspection systems when a new component with a different design needs to be inspected. Therefore, developing a way to automate the task of generating a robotic trajectory offers a substantial improvement in the field of automated manufacturing and quality inspection. This paper proposes and evaluates a methodology for automatizing the process of scanning a 3D surface for the purpose of quality inspection using only visual feedback. The paper is divided into three sub-tasks in the same general setting: (1) autonomously finding the optimal distance of the camera on the robot's end-effector from the surface, (2) autonomously generating a trajectory to scan an unknown surface, and (3) autonomous localization and scan of a surface with a known shape, but with an unknown position. The novelty of this work lies in the application that only uses visual feedback, through the image focus measure, for determination and optimization of the motion. This reduces the complexity and the cost of such a setup. The methods developed have been tested in simulation and in real-world experiments and it was possible to obtain a precision in the optimal pose of the robot under 1 mm in translational, and 0.1 ∘ in angular directions. It took less than 50 iterations to generate a trajectory for scanning an unknown free-form surface. Finally, with less than 30 iterations during the experiments it was possible to localize the position of the surface. Overall, the results of the proposed methodologies show that they can bring substantial improvement to the task of automatic motion generation for visual quality inspection. [ABSTRACT FROM AUTHOR]

Laser powder bed fusion (L-PBF) is an additive manufacturing technique that provides an opportunity to create complex NdFeB magnets, potentially enhancing their performance. L-PBF possesses its own processing challenges, such as porosity/cracks and thermal stresses due to rapid cooling. This study focused on optimizing the parameters and the use of elevated temperature (300–550 °C) powder bed heating to reduce defect generation. This paper includes a detailed process parameter investigation, which revealed samples with a maximum energy product, (BH)max, of 81 kJ/m3 (remanence, Br 0.72 T; coercivity, Hci 891 kA/m) without post/pretreatment, which are the highest (BH)max and Br for L-PBF-processed NdFeB commercial powder. It was observed that all the high-magnetism samples possessed high density, but not all the high-density samples possessed high magnetism. The SEM images and discussions are academically valuable since they clearly illustrate grain formation and morphology in the melt pool, areas where the literature provides limited discussion. Furthermore, this paper incorporates quantitative phase analyses, revealing that the magnetic properties increase with increasing volume fraction of the strong magnetic phase Nd2Fe14B. Another significant contribution of this paper is that it is the first study to investigate the effect of heated bed on L-PBF-NdFeB alloys. The density of the samples and Br can be improved with the use of elevated powder bed heating, while the Hc decreases. The (BH)max can also be improved from 55 to 84 kJ/m3 through elevated powder bed heating. The maximum magnetic properties obtained with the heated bed (400 °C) were as follows: Br, 0.76 T; Hci, 750 kA/m; and (BH)max, 84 kJ/m3. [ABSTRACT FROM AUTHOR]

Forging is a traditional and important manufacturing technology to produce various high strength products and is widely used in engineering fields such as automotive, aerospace and heavy industry. To produce highly accurate product, underfill that the material is not filled into the cavity should strongly avoided. For material saving and near-net product, flash should be minimized. To make the tool life long, it is preferable to produce product with low forging load. It is also preferable to uniformly deform the billet as much as possible for high strength product. Crack is a crucial defect and should strongly be avoided. Therefore, many requirements are taken into account in order to produce the forged product. To meet the requirements, design optimization in forging coupled with computer aided engineering (CAE) is an effective approach. This paper systematically reviews the related papers from the design optimization point of view. For the billet or die shape optimization, the papers are classified into four approaches. The process parameters optimization such as the billet temperature, the die temperature, the stroke length and the friction coefficient is conducted, and the related papers are also classified into four categories. The design variables and the objective function(s) used in the papers are clarified with the design optimization technique. The multi-stage forging including the hammer forging for producing complex product shape is also briefly reviewed. Finally, major performance indexes and the future outlook are summarized for the further development of design optimization in forging. [ABSTRACT FROM AUTHOR]

By studying the edge-workpiece engagement (EWE), and taking two inclination (lead and tilt) angles into account, the time-varying cutting areas and boundaries are determined, the instantaneous numerical chip thickness (NCT) within different EWEs at each point of the edge curve during the milling process of the ball end milling tool is solved, and the milling force and stability are calculated. The milling force and SLD of the model in this paper (NCT-EWE model) and the model in the literature (Altintas and Otzurk model) are compared. It is verified that the algorithm adopted in this paper has higher accuracy, and the algorithm is simple and fast. In addition, it is found that increasing the lead and tilt angles can reduce the milling force and improve the stability, and the free vibration in the stable region decreases gradually, while in the non-stable region, it increases. The algorithm in this paper has certain theoretical and application value for five-axis milling. [ABSTRACT FROM AUTHOR]

Large thin-walled parts are generally featured with large in-plane dimension and thin thickness. This kind of parts deforms easily under the action of gravity due to their low out-of-plane stiffness in the assembly process. In order to reduce the part deformation, the "N-2–1" locating principle is used for large thin-walled parts. The part deformation leads to the assembly gap between two parts, which affects the assembly quality. In this paper, the influence of the fixture layout on the assembly gap is considered. The assembly gap is taken as the optimization objective to minimize by integrating the modified direct stiffness method (MDSM) and the improved particle swarm optimization (IPSO) algorithm. Then, the assembly of two ship parts is studied and the results show that the optimization method proposed in this paper can effectively reduce the assembly gap between two large thin-walled parts. [ABSTRACT FROM AUTHOR]

In the process of aero-engine blade polishing, parameter uncertainties and unmodeled disturbances in the pneumatic end-effector cause fluctuation of the polishing force, affecting the quality of blade processing. To solve the problems mentioned above, a polishing force adaptive controller based on dual extended state observer is proposed. A novel mathematical model of the pneumatic end-effector is established based on the flow characteristics near the zero position of the proportional valve, and a matched disturbance factor is introduced. The controller proposed in this paper contains parameter adaptive law and dual extended state observer. The former aims to compensate for the parameter uncertainties, and the latter aims to compensate for the matched and unmatched disturbances, respectively. The experimental analysis including aero-engine blade polishing constant contact stress control is applied. Simulation and experimental studies show that the controller proposed in this paper can effectively compensate for the influence of parameter uncertainties and unmodeled disturbances on the fluctuation of the polishing force. The fluctuation of the polishing force is 0.41 N, and the quality of the surface finish of aero-engine blades is improved. [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]

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]

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]

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]

Many practical high-pressure die casting process (HPDCP) optimization problems are multi-objective optimization ones that optimize multiple quality attributes of castings, simultaneously. This paper proposed a new HPDCP optimization method for improving volume of shrinkage porosity (VSP) and air entrainment (AE) using Taguchi-based ProCAST simulation and multi-attribute decision-making (MADM)-based overall quality index. Taguchi orthogonal array was used to design ProCAST simulation experiment. MADM was used to convert multiple quality attributes into a single overall quality index (OQI). Taguchi optimization method was used to determine the optimal HPDCP parameters to maximize the OQI. By using the proposed method, this paper determined the optimal HPDCP parameters such as pouring temperature (PT), filling rate in shot sleeve (FR), piston velocity (PV) and preheating mold temperature (PMT) for improving the VSP and AE in carburetor housing with aluminum alloy AlSi9Cu1Mg. The optimal HPDCP parameters were PT of 640 °C, FR of 40%, PV of 6.5 m/s, and PMT of 150 °C. The PT was the most effective HPDCP parameter for improving the VSP and AE, and the next were FR, PV, and PMT. The proposed method could be actively applied to not only HPDCP but also other casting processes and other manufacturing processes. [ABSTRACT FROM AUTHOR]

In order to achieve an optimal system performance, decision makers are continually faced with the responsibility of making choices that will enhance availability and reduce failures cost. To realize this goal, it is crucial to ensure the timely maintenance of equipment, which often poses a significant challenge. However, the adoption of predictive maintenance (PdM) technology can offer a solution by enabling real-time maintenance, resulting in various benefits such as reduced downtime, cost savings, and enhanced production quality. Machine learning (ML) techniques are increasingly being used in the field of predictive maintenance to predict failures and calculate estimated remaining useful life (RUL) of equipment. A case study is proposed in this research paper based on a maintenance dataset from the aerospace industry. It experiments and compare multiple combination of feature engineering techniques and advanced ML models with the aim to propose the most efficient techniques for prediction. Moreover, future research papers can focus on the challenge of validating this proposed model in different industrial environments. [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]

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]

The thermal error is a significant factor that influences the machining accuracy of machine tools, and error compensation is an economical and effective method for enhancing the accuracy of machine tools. However, establishing a precise thermal error prediction model is crucial for thermal error compensation. In this paper, the subtraction-average-based optimizer-based CNN-GRU neural network (SABO-CNN-GRU) is applied to integrated thermal error modeling. Through conducting a thermal characteristic experiment, temperature rise data and thermal error data were collected from the linear feed system of LXK300X helical groove CNC machine tool. The fuzzy c-means clustering and grey correlation analysis are employed to identify temperature-sensitive points in the linear feed system. By utilizing the temperature rise data from these sensitive points along with feed shaft thermal errors as data samples, and using the SABO algorithm to optimize the CNN-GRU prediction model, the thermal error prediction model of SABO-CNN-GRU is established. To validate its superiority and practicality, a comparative analysis is conducted with traditional thermal error prediction models based on CNN-GRU and SO-ELM. The results demonstrate that SABO-CNN-GRU model outperforms both models in terms of mean absolute error (MAE), root mean square error (RMSE), remaining prediction deviation (RPD), mean square error (MSE), and determination coefficient (R2) in accurately predicting results. Building upon this achievement, this paper develops a real-time thermal error compensation system which effectively reduces maximum thermal errors from 80.5 to 17.6 μm after implementing compensation measures. Effectively reducing the influence of thermal errors and improving the machining accuracy of machine tools. [ABSTRACT FROM AUTHOR]

The wear of backup rolls will have a great impact on the quality of the shape of hot rolled strip sheet. In order to overcome the limitations of the finite element method (FEM) in calculating backup roll wear in terms of efficiency and accuracy, this paper proposes a tandem FEM + ML hybrid model to optimise the predictive effect of the finite element method (FEM) on backup roll wear. Firstly, a backup roll wear model based on FEM is established. Secondly, in order to select the optimal machine learning (ML) algorithm as the finite element error compensation model, three types of finite element error compensation models were established based on the random forest (RF) algorithm, the radial basis function (RBF) neural network algorithm, and the particle swarm optimisation support vector machine (PSO-SVM) algorithm. Finally, the three types of finite element error compensation models were connected in series with the FEM model to compare the prediction performance of the three types of FEM + ML models on backup roll wear. The numerical experimental results show that the FEM + PSO-SVM model can better predict the wear of the backup roll, and the PSO-SVM algorithm is the most suitable for building the finite element error compensation model. It is proved that the FEM + ML model proposed in this paper can effectively improve the accuracy and computational efficiency of the FEM model for predicting backup roll wear without adding microelements. In addition, among the hot rolling parameters, the rolling force has the greatest influence on the backup roll wear, and excessive rolling force for a single pass should be avoided to slow down the backup roll wear. [ABSTRACT FROM AUTHOR]

The digital twin (DT) technology is currently considered a key technology for the digital representation of real-world systems. The application of DT technology in smart manufacturing can provide accurate model support for the analysis of mechatronic equipment applications based on model simulations. However, for such a mechanics-electric-hydraulic-control coupled complex system of mechatronics equipment, how to quickly and effectively construct its consistent multi-domain DT mechanism model has become the biggest obstacle to the wide application of DT technology in this field. Therefore, based on the synthesis of existing model construction methods for mechatronics equipment, this paper proposes multi-domain, multi-level, parametric, and consistent mechatronics equipment DT mechanism model construction guidelines. Based on the proposed model construction guidelines, a DT mechanism model construction process for mechatronics equipment is given. Finally, a consistent multi-domain DT mechanism model of computer numerical control machine tools (CNCMT) is constructed by Simscape, to verify the feasibility of the proposed method. The solutions in this paper provide a reliable, rapid, and consistent mechanism model along with construction guidelines and theoretical systems for engineers or researchers that use DT technology to solve specific application problems. Also, the implementation of the virtual commissioning application case in this paper provides application guidance for service analysis based on the DT model. [ABSTRACT FROM AUTHOR]

As an important part of the real economy, manufacturing industry plays a major role in the whole human society. Smart manufacturing has become a strategic issue for many countries. Smart manufacturing puts forward higher requirements for the intelligence of shop-floor production process, product operation and maintenance, logistics and supply chain, which are inseparable from the support of advanced communication technology. As a new generation of mobile communication technology, 5G plays an important role in many areas of smart manufacturing with the characteristics of high bandwidth, low latency, and massive connectivity. This paper first analyzed the communication requirements for machine-to-machine, manufacturing Internet of Things, cyber-physical system-based manufacturing, logistics and supply chain, industrial Internet platform and digital twin–driven manufacturing. Based on the requirements, the research and application progress of 5G in manufacturing are investigated from the above six aspects. In addition, this paper proposed relevant future research hotspots for the further integration of 5G and the above-mentioned six areas of smart manufacturing. [ABSTRACT FROM AUTHOR]

The increase in port scale and business complexity has led to an increased demand for comprehensive and lean control on ports. The current operation mode is facing the bottleneck of the increasingly significant production efficiency and performance. Digital twin (DT) technology realizes holographic visual management and control patterns using cyber-physical fusion and promotes the transformation of a port to an intelligent operation mode. In this paper, the framework of a digital twin application system is proposed based on the analysis of business characteristics of large-scale comprehensive ports. Construction methods and technologies such as digital twin modeling, global ubiquitous perception, data mapping, and model fusion are analyzed. With regard to the construction needs of Qingdao Port's digital twin system, this paper presents a case study and illustrates the overall design process and function of the digital twin system for typical terminals. The system realizes the intelligent operation of the port with the core functions of three-dimensional visual monitoring and optimal dispatching based on real-time perception data. This paper serves as a feasible reference for future intelligent development of large ports and the application of digital twin technology. [ABSTRACT FROM AUTHOR]

Magnetic-electrolytic plasma polishing is a method employed for achieving metal surface planarization through the synergistic effects of electrochemical dissolution and plasma discharge. While numerous studies have focused on elucidating the electrochemical reaction mechanism, there exists a notable gap in understanding and modeling the impact of plasma discharge on material removal. Consequently, this paper introduces a novel plasma discharge kinetic model designed to elucidate the discharge behavior within electrolytic plasma. The innovation lies in the representation of electron collisions in plasma discharges using the Boltzmann kinematic equation. This enables the derivation of the physical dynamics of electrons, including their momentum distribution functions during ionization collisions. Furthermore, the paper incorporates an instantaneous high-temperature melting mechanism resulting from plasma discharge into the surface material removal equation. Corresponding boundary conditions are established for numerical simulations. To validate the proposed model, magnetic-electrolytic plasma polishing experiments are conducted, varying the magnetic field intensities, with TA1 titanium alloy as the test material. Simulation results reveal that the magnetic field enhances the spatial electric field created by the uneven distribution of ion electrons. This enhancement expedites the plasma discharge process towards the anode, generating interference currents that counterbalance the required material removal current. Experimental data is provided to corroborate the model, consistently demonstrating a positive correlation between circuit current and material removal rate. This research underscores the rationality and reliability of the material removal model for plasma discharge, providing a fundamental understanding of electromagnetic plasma polishing. [ABSTRACT FROM AUTHOR]

This paper introduces a novel special-structure field shaper actuator designed to achieve precise spatial distribution of the Lorentz force in electromagnetic sheet metal forming. By precisely designing the bottom profile of the field shaper, the generated Lorentz forces on the workpiece can be controlled to meet various forming requirements. Moreover, the actuator incorporates multiple solenoid field coils to compensate for energy loss in the field shaper, effectively multiplying the input energy. The use of solenoid-type field coils allows for decoupling the optimization of system inductance from the design of the Lorentz force distribution, simplifying the reinforcement of the field coils and enhancing the limit input energy. The paper presents the analytical working principle and control rules to achieve the desired Lorentz force distribution and system inductance. Furthermore, a detailed design method based on numerical simulations is demonstrated to improve forming profiles and uniformity in thin-walled shell part forming. The simulation results indicate that the optimized actuator can reduce the radial thinning variance and the maximum thinning rate by 85% and 35%, respectively. The feasibility of the actuator and design method is verified through a series of comparison experiments, which exhibit a significant reduction in the maximum thinning rate (from 18 to 12%). This research represents a promising advancement in electromagnetic sheet metal forming, offering improved forming capabilities compared to conventional actuators. [ABSTRACT FROM AUTHOR]

In robot grinding, the path planning has always been the main factor affecting the grinding efficiency. To improve the accuracy and automation level of robot grinding, a novel path planning method based on workpiece point cloud is proposed for the grinding of weld seam on curved surface. First, the point cloud of workpiece is obtained by the binocular structured light camera. After data preprocessing, this paper presents a novel approach of tangent planes determination based on the idea of point cloud slicing, which involves 3D projection and image binary extraction. Second, an approach for extracting the weld feature points is proposed based on the deviation term. By calculating the intersecting points between tangent planes and workpiece point cloud, this approach identifies the weld profile and extracts the feature points located in weld center. Then, to reduce the vibration in grinding, the feature points are polynomial fitted to generate a continuous weld grinding path, and a method of posture planning for grinding tool is presented based on grinding tool model and grinding process. Finally, this paper builds the "robot + 3D vision" platform and designs the grinding actuator, the effectiveness of this proposed method is verified by experiments. [ABSTRACT FROM AUTHOR]

In this paper, a new method of electrochemical machining with sheet metal electrode (SME-ECM) is innovatively proposed to meet the challenges of internal gear machining. During the electrochemical machining of internal gears, the distribution of electrolyte flow around the corner area of the internal gear is a critical problem, because the dimensional accuracy at the corner directly determines the sidewall accuracy of the internal gear. In view of the phenomena such as stray flow field, gas accumulation in the machining corner area, and uneven removal in different machining areas during the machining process of internal gears, this paper carries out theoretical analysis and experimental investigation on the three flow field models of forward flow (Ff), reverse flow (Rf), and lateral flow (Lf) through multi-physics coupling simulation, flow field observation, and machining experiment. The processing characteristics of the corner area under the influence of different factors (flow field model, processing stage, flow rate, gas distribution) are obtained. The results show that under the same electrolyte pressure, the Lf model has the least residual gas in the corner region, with a gas content of less than 1.5e-5, and the machining current could reach 2.92 A, which has a significant advantage in the processing uniformity, indicating that the Lf flow field model has the advantage of electrochemical machining of internal gears. The research in this paper lays a theoretical foundation for further electrochemical machining of internal gears. [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]

Magnetic field-assisted finishing (MFAF) technology, as a non-traditional surface finishing technology, has a unique advantage in machining components composed of complex shapes and difficult-to-process materials and has been widely concerned. To date, more than thirty MFAF technologies have been developed; however, there has not been a detailed study to classify these technologies and compare and contrast the advantages and limitations of these technologies. Therefore, in order to promote the development of MFAF technology, MFAF technology is reviewed in detail in this study. This paper introduces the origin and development of MFAF technology and proposes a classification method based on media. On this basis, the differences of wear mechanisms and the action mechanism of composite processing are discussed, the representative MFAF techniques are overviewed, and the commonly used material removal models of MFAF techniques are summarized. Finally, the possible research directions of MFAF process in the future are described. This paper has important reference value for researchers in the field of ultra-precision machining. [ABSTRACT FROM AUTHOR]

Electric pulse–assisted machining (EPAM) can improve the quality of the machined surface, lower the machining stress on the material, and increase the material's machinability. It offers a useful machining technique for working hard and difficult-to-machine metals with little plasticity. To account for this, this paper reviews experiments of EPAM using the electroplasticity effects (EPE) of metals and describes the use of electroplasticity in terms of plastic forming machining and cutting machining, and it also depicts the processes and benefits of EPAM. The experimental results show that the partial stress reduction during EPAM is up to 70%, the roughness is decreased by 40%, the work-hardening is reduced by 44%, and the material's machinability is partially improved. Various hypotheses have been pioneered by academics regarding the electroplasticity effect's mechanism, and they have all undergone experimental testing. Most academics today think that there are various mechanisms involved in electroplasticity, and that certain metals have various mechanistic effects. The paper gives theoretical suggestions for the use and further development of electroplasticity by summarizing the current processes of electroplasticity in terms of thermal and athermal effects. The thermal effect is the Joule heating effect. Other athermal effects include the electron wind effect, skin effect, pinch effect, magnetostrictive effect, de-pinning effect, and vibration effect. A summary diagram of the application and mechanism effects of EPE in processing is also included in the script. Finally, the article summarizes EPE, provides a constructive outlook on the future development of EPAM, and reveals the current problems. [ABSTRACT FROM AUTHOR]

Bearings are pivotal components in mechanical systems, providing crucial support to rotating bodies. However, traditional bearings are susceptible to failure caused by friction and wear. This vulnerability is particularly pronounced in scenarios involving ultrahigh speeds and extreme conditions, necessitating the minimization of bearing losses and the enhancement of performance. Magnetic bearings, distinguished by their frictionless operation, absence of lubrication requirements, and high-speed capabilities, offer a promising solution to mitigate bearing failure attributable to friction. Nevertheless, a comprehensive review of magnetic bearings, encompassing their structural attributes, modeling mechanisms, and control strategies, is currently lacking in the literature. This paper aims to address this gap by conducting an exhaustive literature review on magnetic bearings. The objective is to provide scientists with a profound understanding of the structural characteristics, operational mechanisms, control performance, and future development trajectories of this technology. The paper begins by categorizing various magnetic bearings and conducting an in-depth analysis of their properties and characteristics, focusing on their magnetic circuit structures. Subsequently, it delves into the working principles and performance of mathematical models for magnetic bearings with different configurations, outlining the modeling procedures and optimization approaches. Additionally, the paper highlights the impact of control strategies on the performance of magnetic bearings. Modern control theory has demonstrated a remarkable 50% improvement in position accuracy and adjustment time compared to traditional PID control. Finally, the paper offers a glimpse into the future of magnetic bearing design, modeling mechanisms, and control strategies, presenting prospective directions for further advancements in this field. [ABSTRACT FROM AUTHOR]

Nickel-based alloys have great application value in aerospace, biomedical industry, chemical industry, and other fields. However, nickel-based alloys are known to be difficult to process, which will generate a lot of heat and friction during processing, which limits the application range of nickel-based alloys. Therefore, a large amount of cutting fluid needs to be used during processing, and the cutting fluid will cause harm to human health and the environment. In order to solve these problems, scholars proposed to use the minimum quantity lubrication (MQL) to replace the conventional flood cooling lubrication technique. Recently, many papers have proposed to use MQL for lubrication /cooling in the processing of nickel-based alloys. However, few studies have approached this topic comprehensively. To bridge this gap, this study conducts a comprehensive literature review of the progress made in the processing of nickel-based alloys using various MQL methods. It should be noted that these studies are divided into four categories: vegetable oil-based MQL, cryogenic cooling-based MQL, solid lubricant-based MQL, and electrostatic atomization-based MQL. It is crucial to compare the advantages of these cooling and lubricating technologies in machining nickel-based alloys, analyze their experimental results, and assess their impact on machining quality and tool wear. This review reveals that compared to traditional MQL, vegetable oil-based MQL is more energy-saving and environmentally friendly, resulting in approximately 30% improvement in surface quality and a 50% reduction in tool wear. The addition of solid lubricants to vegetable oil further enhances its lubrication performance. Cryogenic cooling-based MQL enables the attainment of finer grains and smaller sawtooth chips. Electrostatic atomization MQL, by altering the atomization process of traditional MQL, produces more uniform droplets, leading to a 42.4% reduction in tool wear and a 47% improvement in machined surface quality. The purpose of this paper is to help researchers identify existing gaps and to enable MQL to improve the processing quality and application range of nickel-based alloys. Finally, the present technical challenges and future research directions are put forward. [ABSTRACT FROM AUTHOR]

Precision complex surfaces components are in high demand for optical imaging, high-power lasers, and medical implants. Magnetorheological finishing (MRF) is widely used in ultra-precision machining of complex surfaces components due to its advantages of low processing cost, high precision, stable removal function, no surface damage, and the ability to achieve nano-scale surface roughness and micro-scale surface shape accuracy. However, the removal efficiency of MRF is still low, the material removal mechanism is not completely clear, and the properties of magnetorheological fluid (MR fluid) need to be improved, so its application in industrial production is limited. In order to further promote the development of MRF and break through the difficulties of current MRF, it is necessary to review and summarize the MRF technology. Recent studies progress on MRF need to be more comprehensive. It is not comprehensive to introduce only several different removal theories and the appearance of compound MRF. Research progress like MR fluid, MRF tools or other also should be mentioned in a short sentence. This paper gives a detailed literature review on MRF for complex surfaces. Firstly, the principle of MRF is introduced. The finishing tools are classified based on shape and the workpieces suitable for each tool are analyzed. Some new compound MRF techniques with high machining efficiency are introduced. Then, the researches on MRF influence function and force were reviewed, and the researches on three factors affecting MRF machining performance, including process parameters, MR fluid, and magnetic pole arrangement, were reviewed. Finally, the key works of MRF technology in the future are prospected: material removal theory, preparation of high performance MR fluid, and development of novel composite MRF based on interdisciplinary and universal optimization of MRF machine tools. This paper has important reference value for researchers in MRF-related fields. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions during belt grinding is of great significance for environmentally friendly production in the manufacturing industry. In this paper, in order to better grinding aero-engine titanium alloy blades with the abrasive belt, an improved NSGA-II multi-objective optimization algorithm was proposed, which reduced the carbon emissions during the grinding process while ensuring the same surface roughness and material removal rate. Firstly, through analysis and finite element simulation, the model of abrasive belt grinding force is established and the rationality of the model is verified by experiments; furthermore, the carbon emission model of abrasive belt grinding and the multi-objective optimization model based on the improved NSGA-II algorithm are established; finally, the results of the algorithm are verified and compared through numerical simulation and experiments. Compared with the NSGA-II algorithm and the multiple objective particle swarm optimization algorithm, the optimization results of the algorithm in this paper have better diversity and uniformity and can find better non-dominated optimal solutions; the process parameters selected by the algorithm in this paper can more effectively reduce the carbon emissions during grinding. The optimization method proposed in this paper has certain reference significance for engineering practice. [ABSTRACT FROM AUTHOR]

Nanofluids are efficient heat transfer media that have been developed over the past 27 years and have been widely used in the electronic microchannel, engine, spacecraft, nuclear, and solar energy fields. With the high demand for efficient lubricants in manufacturing, the application of nanofluids in machining has become a hot topic in academia and industry. However, in the context of the huge amount of literature in the past decade, existing review cannot be used as a technical manual for industrial applications. There are many technical difficulties in establishing a mature production system, which hinder the large-scale application of nanofluids in industrial production. The physicochemical mechanism underlying the application of nanofluids in machining remains unclear. This paper is a complete review of the process, device, and mechanism, especially the unique mechanism of nanofluid minimum quantity lubrication under different processing modes. In this paper, the preparation, fluid, thermal, and tribological properties of nanofluids are reviewed. The performance of nanofluids in machining is clarified. Typically, in friction and wear tests, the coefficient of friction of jatropha oil-based alumina nanofluids is reduced by 85% compared with dry conditions. The cutting fluid based on alumina nanoparticles improves the tool life by 177–230% in hard milling. The addition of carbon nanotube nanoparticles increases the convective heat transfer coefficient of normal saline by 145.06%. Furthermore, the innovative equipment used in the supply of nanofluids is reviewed, and the atomization mechanisms under different boundary conditions are analyzed. The technical problem of parameterized controllable supply system is solved. In addition, the performance of nanofluids in turning, milling, and grinding is discussed. The mapping relationship between the nanofluid parameters and the machining performance is clarified. The flow field distribution and lubricant wetting behavior under different tool-workpiece boundaries are investigated. Finally, the application prospects of nanofluids in machining are discussed. This review includes a report on recent progress in academia and industry as well as a roadmap for future development. [ABSTRACT FROM AUTHOR]

Metal additive manufacturing is an active field of innovation. However, for laser power bed fusion (LPBF), supports removal is a major constraint. In this technology, supports are strongly welded to the part to tightly maintain it, avoid distortion, and evacuate thermal load. Although supports are usually optimized for manual removal, machining is often necessary, which can affect post-processing productivity. This paper proposes a comprehensive methodological approach to optimize the selection of cutting parameters, cutting tools, and support structure for LPBF. The aim is to help additive manufacturers find supports that reduce machining costs in terms of time and cutting tool degradation, from among the numerous support designs available. This approach can also optimize the design of lattice structures used inside parts. Our results show that among the 11 designs tested, honeycomb and squared pattern grid supports are the most efficiently machined using the 8-teeth tangential milling of the 3 tools tested, with a good post-machined surface roughness and tools' health. The method considers low magnification optical analysis and an accelerometer sensor, which is easy to use even for small- and medium-sized enterprises. This paper also proposes and analyzes a new kind of porous support using this method. [ABSTRACT FROM AUTHOR]

The contemporary industry has witnessed a significant transformative development with the integration of artificial intelligence (AI) in various industrial systems, resulting in an enhanced automation for heightened productivity and efficiency. However, mastering this level of automation can be challenging for some applications, such as manufacturing inspection, which can be delicate while maintaining a precise cadence for an in-line manufacturing scale. In this paper, a systematic machine vision-based approach for on-machine inspection is proposed in order to automate and improve inspection process towards computer numerical control (CNC) machined parts. The approach incorporates remapping algorithm and image processing operations to accurately extract desired features. Subsequently, these features will undergo dimensional inspection based on their generated point clouds. Tests were applied on a sample part using a complementary metal–oxide–semiconductor (CMOS) camera mounted on the spindle of 5-axis CNC machining center. The paper explores numerous aspects related to different stages of the approach and their impact on the resulting inspected features evaluations. It also highlights significant findings regarding critical factors for conducting well-structured experiments at various stages. Promising results have shown the significance of the presented work regarding industrial automation technology, ultimately improving manufacturing efficiency throughout the production line. [ABSTRACT FROM AUTHOR]

The article focuses on the analysis of changes in the surface morphology of planer knives modified with four different anti-wear coatings: multilayer, monolithic, monolithic-gradient, and gradient. The coatings described in the article affect the extension of planer tools service life in the range from 153 to 269%. The main objective of the paper was to determine the effect of vacuum-plasma modification of working surfaces of tools intended for machine processing of wooden parts on their geometric structure. The research was carried out on planer knives made of HS6-5–2 high-speed steel and used in industrial conditions. The present work sums up the knowledge resulting from the exploitation tests of modified knives with the features defining the morphology of their working surfaces. The paper comprehensively characterizes the 3D surface roughness parameters, as well as other characteristics such as isotropy and depths histogram. The knife surface modified with a gradient coating (longest life 269%) had a high level of anisotropy. Rose directions with texture directions present that this kind of coating generated structure with 4.23% value of isotropy. The distribution of ordinates was characterized by high clustering and an negative skewness (Ssk = − 0.74). The results described can be used in the design and quality assessment of thin anti-wear coatings, as well as in preparation of substrates for their application. [ABSTRACT FROM AUTHOR]

This paper presents a computer-based methodology to support the design for additive manufacturing of metal components. Metal additive manufacturing, and in particular powder bed fusion systems, are playing a prominent role in the industry 4.0 scenario. The state of the art concerning design methods and tools to support design for additive manufacturing is reviewed by the authors. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened, and the computer-aided technologies to support the approaches implementation are described. Indeed, the state of the art design for additive manufacturing general workflow can be enriched by holistic approaches, use of numerical simulation, and integration and automation between the required tasks. The paper provides a methodology based on the systematic use of numerical simulation to achieve the optimization of both products and associated processes. To take advantage of the holistic perspective, the approach relies on the use of integrated product-process design platforms, allowing to streamline the digital process chain. Product design is based on the systematic integration of topology optimization and automatized tools for concept development and selection and subsequent product simulation driven design refinement. Process design is based on a systematic use of process simulation to prevent manufacturing flaws related to the high thermal gradients of metal processes and minimize residual stress and deformations. This is achieved by working on both the build cycles layouts and the 3D models' distortion compensation. An automotive use case of product and process design performed through the proposed simulation-driven integrated approach is provided to assess the actual method suitability for effective re-designs of additive manufacturing high-performance metal products. The bridged gaps are systematically outlined, and further developments are discussed. [ABSTRACT FROM AUTHOR]

Compression mold tooling fabrication has been traditionally conducted via machining processes—for example, computerized numerical control machining, mill, or lathe operations. While subtractive manufacturing operations provide high-precision tooling, they have an extended lead time and generate material waste, which increases manufacturing costs. This paper analyzes direct metal laser sintering (DMLS) as a viable alternative to traditional compression mold manufacturing. DMLS is an additive manufacturing process that uses high-powered lasers to fuse metal powders in a layered approach to create high-precision metal components. Through layering materials, DMLS can produce complex geometries which can have features impossible to machine from traditional manufacturing methods. Additionally, DMLS uses less material for parts, reducing material costs and lead times. In this paper, DMLS manufactured mold was computationally studied against a traditional compression mold's thermal and pressure requirements. The DMLS mold was designed with a honeycomb structure to reduce material usage while maintaining structural integrity. Computational analysis showed that the production requirement, "maximum deflection of 0.001 inches," was achieved with the DMLS when pressures and temperatures were similar to those required for the tooling. In addition, DMLS-produced mold utilized 74% less material than a traditionally manufactured mold. [ABSTRACT FROM AUTHOR]

Ultrasonic atomization technology has recently been widely used in industry due to its higher atomization efficiency. This paper proposes a method of electrostatic-assisted ultrasonic atomization spraying and designs a particular ultrasonic power supply that can directly introduce high-voltage static electricity onto the surface of the ultrasonic atomization so that the liquid can contact the charge and enhance the charging effect. This paper conducts numerical simulation analysis on the atomization process and statistically analyzes the numerical simulation atomization particle size through image processing. In addition, this paper designs experiments from two aspects of atomization particle size and film-forming effect. The results show that the experimental results are consistent with the numerical simulation results, verifying the accuracy of the numerical simulation results. It shows that in sub-droplet formation, introducing static electricity will increase the number of capillary waves, promote two mechanisms of the capillary pinch-off mechanism and the Rayleigh-plain instability, reduce atomization particle size, and increase atomization efficiency. Compared with the traditional airflow beam method, the film-forming surface quality of the electric field beam method is higher, and the surface roughness is lower. It solves the problem that airflow affects film-forming quality in traditional ultrasonic spraying with the airflow beam method. It provides a theoretical basis and scientific guidance for applying electrostatic-assisted ultrasonic atomization technology in the atomization and film preparation industry. [ABSTRACT FROM AUTHOR]