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This paper discusses the health hazards faced in a company which produces printed paper packaging. The analysis is based on three main production processes, namely, printing, plate-making and washing. The components in the emissions of these processes are broken down into their chemical compositions and given a hazard rating. The analytic hierarchy process in the health hazard scoring system is introduced to evaluate the level of hazard of each process to the environment. When the hazard level encountered in each process is known, the necessary precautions and measures can be taken. [ABSTRACT FROM AUTHOR]

In this paper, a magnetic field-assisted WEDM-ECM complex process (MF-assisted WEDM-ECM) is proposed to solve the problems of traditional low-speed wire electrical discharge machining (WEDM-LS) of NiTi SMA, including low machining efficiency, high workpiece surface roughness, and large recast layer thickness. Electrolytic machining is used to remove the recast layer, and magnetic field-assisted method is used to reduce the surface roughness and improve the machining efficiency. Firstly, based on the double-layer model the removal thickness of recast layer is deduced, and the removal thickness of recast layer under different machining parameters is analyzed. In addition, based on the influence of magnetic field on discharge channel, the single spark crater analytical model is modified. Based on this model, combined with the electrochemical corrosion rate and the wire electrode vibration response equation, a continuous discharge corrosion mathematical model is established to predict the surface topography of the workpiece, and the simulation analysis is carried out. Finally, comparison of the experimental results of traditional WEDM-LS, MF-assisted WEDM-LS, ultrasonic vibration (USV)-MF complex-assisted WEDM-LS, and MF-assisted WEDM-ECM in machining NiTi SMA reveals that MF-assisted WEDM-ECM has the best machining performance. Compared with traditional WEDM-LS, the material removal rate (MRR) of MF-assisted WEDM-ECM was increased by 26.2%, the surface roughness value was reduced by 19.2%, and the thickness of recast layer was reduced by 44.25%. The average errors of the experimental and predicted values of workpiece surface roughness, recast layer removal thickness, and kerf width are 8.3%, 6.41%, and 3.58%, respectively, which verified the accuracy of the theoretical model proposed in this paper. [ABSTRACT FROM AUTHOR]

In the milling process, the wear area of the tool is often segmented using the traditional image processing method to quantify the tool wear value. However, these methods have the disadvantages of having weak anti-noise capabilities and low segmentation accuracy. Although the semantic segmentation network can achieve excellent segmentation accuracy, obtaining enough end mill wear images to support the semantic segmentation network's training is challenging due to the high acquisition cost of wear images. As a result, this paper suggests a small sample end mill wear area segmentation method based on transfer learning and generative adversarial networks to address the issue of insufficient samples of end mill wear images. In this paper, WGAN is used to generate wear images to expand the dataset with a few samples, and the transfer learning method is used to improve the generalization ability of the segmentation network and finally achieve small sample training. This approach increases mPA by 4.46% and mIOU by 8.97% when compared to merely using the semantic segmentation network for small sample training. According to experimental findings, this method not only has high stability and segmentation accuracy but also solves the problem of insufficient end mill wear image samples. The method proposed in this paper can be effectively applied to the intelligent detection of the tool wear state, improving the accuracy and stability of the measurement of the tool wear value. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is a pillar of the transition to Industry 4.0 and smart manufacturing. It can facilitate training, maintenance, assembly, quality control, remote collaboration and other tasks. AR has the potential to revolutionize the way information is accessed, used and exchanged, extending user's perception and improving their performance. This work proposes a Pervasive AR tool, created with partners from the industry sector, to support the training of logistics operators on industrial shop floors. A Human-Centered Design (HCD) methodology was used to identify operators difficulties, challenges, and define requirements. After initial meetings with stakeholders, two distinct methods were considered to configure and visualize AR content on the shop floor: Head-Mounted Display (HMD) and Handheld Device (HHD). A first (preliminary) user study with 26 participants was conducted to collect qualitative data regarding the use of AR in logistics, from individuals with different levels of expertise. The feedback obtained was used to improve the proposed AR application. A second user study was realized, in which 10 participants used different conditions to fulfill distinct logistics tasks: C1 — paper; C2 — HMD; C3 — HHD. Results emphasize the potential of Pervasive AR in the operators' workspace, in particular for training of operators not familiar with the tasks. Condition C2 was preferred by all participants and considered more useful and efficient in supporting the operators activities on the shop floor. [ABSTRACT FROM AUTHOR]

The aim of this paper is to study the mechanical behavior of corrugated board boxes, focusing attention on the strength that the boxes are able to offer in compression under stacking conditions. A preliminary design of the corrugated cardboard structures starting from the definition of each individual layer, namely the outer liners and the innermost flute, was carried out. For this purpose, three distinct types of corrugated board structures that include flutes with different characteristics, namely the high wave (C), the medium wave (B), and even the micro-wave (E), were comparatively evaluated. More specifically, the comparison is able to show the potential of the micro-wave which would eventually allow a significant saving of cellulose in the fabrication process of the boxes, thus reducing the manufacturing costs and causing a lower environmental footprint. First, experimental tests were carried out to determine the mechanical properties of the different layers of the corrugated board structures. Tensile tests were performed on samples extracted from the paper reels used as base material for the manufacturing of the liners and flutes. Instead, the edge crush test (ECT) and box compression test (BCT) were directly performed on the corrugated cardboard structures. Secondly, a parametric finite element (FE) model to allow, on a comparative basis, the study of the mechanical response of the three different types of corrugated cardboard structures was developed. Lastly, a comparison between the available experimental results and the outputs of the FE model was carried out, with the same model being also adapted to evaluate additional structures where the E micro-wave was usefully combined with the B or C wave in a double-wave configuration. [ABSTRACT FROM AUTHOR]

A hot stamping process of quenchable steel tubes using a mandrel reinforced with eco-friendly fibers was developed to produce ultra-high strength steel hollow parts having enhanced lightweighting and crashworthiness. High internal pressure was generated to improve the die quenchability and shape accuracy of the formed parts by the fiber reinforcement. Wood sawdust, shredded copy paper, and plant fiber made of recycled toilet paper were chosen as the fibers, and not only the strength was evaluated from a uniaxial compression test but also the melting behavior of the mandrel was examined. The influence of the fiber reinforcement on the shape accuracy and die quenchability of hot-stamped parts was investigated. The generated internal pressure with the fiber-reinforced ice mandrel was higher than that with the pure ice mandrel without the reinforcement, and thus, the shape accuracy and die quenchability of hot-stamped parts were significantly improved even for a comparatively small change in internal volume of tubes. [ABSTRACT FROM AUTHOR]

Inspired by cloud computing, cloud manufacturing (CMfg) is a service-oriented manufacturing paradigm on an on-demand and pay-as-you-go business model through the internet. More specifically, new challenges for production planning and decision-making process have emerged in that resource scheduling and have gained the most attention, and there is an urgent need to determine the current status and identify issues and matters to be addressed in the future. This review paper is aiming to discuss aspects of the cloud-based resource scheduling problem through investigating the literature to date to identify the existing gaps and recommending the potential paths moving forward for researchers in this field. So far, literature reviews focused on a broad scope of cloud-based scheduling, as a new approach taking a "narrow scope" by focusing on resource scheduling and various steps of it in the cloud environment are considered. Using the data gathered from the popular databases, a comprehensive statistical analysis on the existing literatures is provided, and the rational sequences of the systematic literature review (SLR) are elaborated. The mathematical models in resource scheduling are thoroughly elucidated. Then, a comprehensive analysis of the main aspects of resource scheduling including the objective functions, constraints, and optimization algorithms is presented. Discussion of the findings of the review paper illustrates that time and cost gain more attention (almost 80%) among all objective functions, and the metaheuristic algorithms are the most widely used in the recent research papers. Finally, suggestions for potential future research to further consolidate this field have been enumerated. [ABSTRACT FROM AUTHOR]

Ultrasonic-assisted machining is an advanced method which could improve the process of machining. Besides, simulation modeling process is a method to help the researchers analyze different aspects of the process with more details in a shorter time. Simulation of ultrasonic-assisted machining is also a field of research that is of interest to researchers working in the field of machining processes. In recent years, a variety of papers have been published where cutting forces, chip formation, tool wear and temperature, and microstructure changes were simulated. That being the case, a review paper is required to represent the advances implemented by researchers in the simulation of ultrasonic-assisted machining process. Moreover, the difficulties and necessities of this process are mentioned at the end of this review paper. [ABSTRACT FROM AUTHOR]

The development of air bearing demands further research and certain guidance. The previous technical reviews focused on specific aspects, while bibliometric analysis employed in this paper gave a general overview on air bearing field and provided clearer research interest and development trend. The publications in the field of air bearing from 1990 to 2017 based on the Science Citation Index Expanded (SCIE) database were analyzed from the aspects of countries, institutions, research areas, journals, authors, keywords, reviews, and high cited papers, implemented by some representative and convincing indicators. The result showed that the USA held the dominant position in this field, followed by Japan and China. The University of California System held the top position in terms of total papers and h-indexes. It had shown a multi-disciplinary development trend of air bearings from the aspect of research area. Tribology related journal took high ranking of the list, in which "Journal of Tribology-Transactions of the ASME" ranked first. Bogy, D. B., made most contributions to the air bearing field, with the highest total citations and h-index. Thermal effects, foil bearing, dynamic analysis, and active compensation were hotspots. Reynolds equation, stability, optimization, load-carrying capacity, foil bearings, and aerostatic bearings were potential directions that might have greater opportunities for improvement. The improvement of air bearing requires common progress in multiple aspects. [ABSTRACT FROM AUTHOR]

Geometric-physical modeling and simulation of tool machining processes is an effective realization for manufacturing prediction and verification. By integrating the scheme of CNC code analysis, process planning and optimization, cutting mechanism model, and other related aspects, micro cutting details were implemented to be simulated in advance, detected and monitored in the process, and analyzed afterwards, to achieve the purpose of "Verification IS Production." Pursuant to this purpose, this paper proposed a research framework of micro geometric modeling and physical simulation for machine tool cutting. On the basis of continuous improvements in 3D modules for cutting geometry simulation, the physical simulation research and verification was carried out with several typical scenes, in which the mappings between real occasions and simulation system were established. With the cutting physical models, this paper deeply investigated the simulation calculation and correction for various factors affecting the cutting performance and indicators and finally verifies, analyzes, and optimizes them through actual machining environments. The purpose of this paper is to explore a feasible and novel way for richer scenes and further research through the multi-element modeling of several comprehensive cutting cases and in-depth micro geometry and physics investigation. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is experiencing widespread adoption in many sectors including aerospace and biomedical. Several research works have already studied AM to ensure high quality final parts can be consistently achieved. To aid in virtually simulating the additive manufacturing processes, companies like ANSYS have developed simulation packages for their finite element software. These packages have been proven to be effective in predicting and minimizing distortion and warping, but their capability in predicting resultant mechanical characteristics requires further investigation. This paper focuses on using ANSYS Additive Suite (AAS) to predict the mechanical performance of polymer parts produced by a selective laser sintering process. Utilizing AAS, the process of additively manufacturing a tensile test specimen was simulated, followed by simulated tensile loading in ANSYS Mechanical. The output of this simulation was then experimentally verified with physical components. The results show that AAS can increase the accuracy of displacement prediction of a part under load within the elastic region with minimal experimentation required. However, it was also observed that the accuracy starts to decrease when approaching the yield point and consequently entering the plastic region due to the complexity of plastic behavior. When designing, the yield point is a critical design parameter and often considered the limit of a material. The process outlined in this paper allows for validation of AM design to be done faster, cheaper, and with more flexibility than possible using experimental or mathematical methods. Should this process be further refined, generative design possibilities will be significantly more powerful. [ABSTRACT FROM AUTHOR]

The utilization of the nickel-based superalloy GH4169 in the manufacturing of heat-resistant parts, such as aero-engine casings, blades and blisks, is prevalent due to its exceptional thermal fatigue strength, oxidation resistance and corrosion resistance. In spite of these favourable properties, GH4169 still poses challenges in machining, primarily due to its difficult-to-cut characteristics, which results in rapid tool wear and complex tool wear processes. Existing research efforts in the field of tool wear have mainly focused on establishing tool wear models based on wear mechanisms, field empirical or mathematical derivation to describe the tool wear process. Despite these efforts, the accuracy of the existing models in fitting the actual tool wear trend remains a challenge. This paper proposes a novel evolutionary cluster analysis method to analyse the evolution of tool wear, which serves as the theoretical basis for a more accurate tool wear model. Based on the evolution law of different stages of tool wear obtained by evolutionary cluster analysis, this paper establishes a tool wear model that reflects the characteristics of the distribution of tool wear values and accurately fits the actual tool wear trend. The proposed model is experimentally validated on the GH4169 tool wear data, and the results show that the proposed model has advantages over existing models in machining GH4169. [ABSTRACT FROM AUTHOR]

The R-Test measures the three-dimensional displacement of a tool center point with respect to a work table in five-axis machine tool, as linear axes are driven synchronously with a rotary axis. This paper experimentally compares the measuring performance of the R-Test instruments with (1) tactile linear displacement sensors, (2) laser displacement sensors based on the refraction in a glass ball lens (Laser R-Test), and (3) laser interferometers, in dynamic tests described in ISO 10791-6:2014. A tactile displacement sensor pushes its measuring contact to the target surface by a spring, and its stiffness can limit the measurement bandwidth. This paper experimentally investigates this influence in the measurement of dynamic synchronization error of rotary and linear axes particularly near the reversal point in the present tests. This paper also presents a test to measure the bandwidth of a tactile displacement sensor. [ABSTRACT FROM AUTHOR]

In the last decade, the use of additive manufacturing (AM) systems in manufacturing has increased drastically and studies show that additive manufacturing has potential of becoming the next sustainable manufacturing solution. There are multiple additive manufacturing processes currently in research and practice and have varying degrees of energy consumption. Energy consumption could be an important consideration in adopting a specific AM Method. However, the current literature review reveals that there is a lack of well-established methodology to map the energy consumption in an AM process. This paper aims to narrow this gap by developing a structured and robust method to map energy footprint in additive manufacturing processes using modified Sankey diagrams. The proposed approach allows engineers and researchers to visualize energy consumption in different steps of the additive manufacturing process and select the optimal energy efficient method. The paper demonstrates the proposed methodology through two case studies involving selective laser melting (SLM) process and fused filament fabrication (FFF) process. The novelty of using Sankey diagrams for mapping energy consumption in AM lies in their ability to provide a clear and intuitive representation of complex energy systems. The modular architecture of the Sankey diagrams aids in the effective mapping, visualization, and analysis of energy flow. It is shown that the proposed methodology can provide insight into potential changes for energy saving in additive manufacturing processes. [ABSTRACT FROM AUTHOR]

With the advent of printed electronics, electrode manufacturing has made significant progress. In contrast to the traditional lift-off method, printing methods offer several advantages. They are not limited by the shape, structure, or material of the substrate, allowing for the manufacturing of electrodes using a wider range of materials. The manufacturing process can be completed at low temperatures, and the cost is reduced due to less material consumption. Printing methods can be broadly categorized into plate printing and plateless printing. Screen printing is a representative plate printing method, while inkjet printing is a typical plateless method. The two techniques are widely used in electrode manufacturing due to their convenience and the easily customized graphics. Screen printing is particularly efficient for processing electrodes in large quantities, while inkjet printing offers greater flexibility, allowing for quick adjustments to the shape of electrodes. This paper reviews recent advances in electrode manufacturing based on printing, focuses on the characteristics of screen printing and inkjet printing, and makes discussions about the main issues and challenges and the potential solutions. [ABSTRACT FROM AUTHOR]

Cr-Co-Mo-Ni high-hardness steel is widely used in critical mechanical transmission components. It has the difficult-to-cut characteristic because of its high hardness and high strength. In the cutting process, the machining cutting force is large, the tool is worn quickly, and the machining accuracy is poorly maintained. It has become one of the crux of restricting the improvement of quality and production efficiency of innovative products. In order to solve the above problems, this paper carried out research on the electrochemical machining process to achieve high-quality and efficient machining of high-hardness gear steel splines. Firstly, the process characteristics of ECM of internal spline are analyzed. The electrochemical field model is established by the multi-physical field coupling simulation platform, and the effects of the main electrolytic process parameters on the forming accuracy were numerically simulated and analyzed. Meanwhile, the three-dimensional simulation model of electrolyte flow field in the inner cavity of the electrolytic fixture is established, and the influence of electrolyte flow direction and electrolyte back pressure on the flow field distribution is explored. The platform of electrochemical machining system is set up. An experimental study on electrochemical machining of involute internal splines is carried out to further optimize the electrochemical machining process parameters. The test results showed that the electrolysis accuracy and efficiency of the 41-tooth involute spline workpiece are optimized when the electrolyte is 8% NaNO3, the back pressure of the electrolyte is 0.2 MPa, the feed speed is 1.8 mm/min, and the processing voltage is 16.0 V. The machining accuracy of the method proposed in this paper meets the actual requirements of actual gear application. Compared with the traditional slotting process, the machining efficiency is improved by 62.5%, the tool wear is reduced, and the machining accuracy retention is improved. It has important application value for advanced machining technology of high-performance materials. [ABSTRACT FROM AUTHOR]

Machining time and energy consumption are common process planning evaluation metrics. However, it is difficult to obtain accurate machining time and energy consumption values in the process planning stage, which may result in non-optimal obtaining process routes. To solve these problems, this paper proposes a flexible process planning method based on processing time and energy consumption prediction models. The historical processing data is analyzed, and a prediction model of machining time and energy consumption based on a radial basis function neural network is proposed. Considering the flexibility of multiple processes, a mathematical model of the flexible process planning problem based on the machining time and energy consumption prediction model is established. A multi-objective algorithm using a multidimensional real number coding method is proposed for problem-solving with the completion time and energy consumption minimization as the optimization objective. Two algorithms with better multi-objective optimization performance, the strength Pareto evolution algorithm 2, and the dominance ranking genetic algorithm II are selected for comparative analysis to obtain a better effect of optimization. The better algorithm is selected with the best parameters. Finally, case studies are conducted to verify the validity of the prediction model and the flexible process planning model. [ABSTRACT FROM AUTHOR]

This paper explores the concept of autonomous decision rules of Industry 4.0. The goal is to model and simulate a production system in which products autonomously choose the resource in which they will be processed based on shortest completion time (shortest queue length). For validation and benchmark, a production system previously presented in the literature is modeled. The performance of the autonomous model is evaluated in comparison to a model with dedicated lines for each product. In the previous work considered, a specific interarrival function and only deterministic parameters for the processing times are used, with no consideration of setup times. After validation, the proposed models are simulated with other parameters (different probability distributions for interarrival and processing times) and are extended to include machine setups, according to different rules. Reductions in total throughput times and their variability were observed for the systems with autonomous products, when compared to those with dedicated lines, which indicates greater responsiveness and stability of the shop floor. An optimization model for scheduling was also proposed and applied to the same system and input data of the simulation of autonomous products, for comparison. The results showed that the proposed decision rule based on the queues' length, used in the simulation, can yield solutions of good quality, close to the optimal solution. This paper contributes to extend and generalize the results of the literature and the discussion about variability seeks to motivate organizations to implement systems with autonomous products. [ABSTRACT FROM AUTHOR]

This paper presents a case study conducted in an assembly cell specifically designed for the automated drilling of an aeronautical structure. The study shows how techniques approached by the 4.0 industry have the potential to contribute to manufacturing, breaking the limits imposed by the previous state-of-the art systems. This paper proposes a method that utilizes a committee of neural networks to calculate an indicator for the final quality of drilled holes. The method analyzes data obtained by monitoring the electric current consumed by the drilling system drive. Considering the tests carried out on a real product, the method presents an accuracy of 95% and has the potential to increase the efficiency of the drilling process, reducing the cycle time by up to 25%, since it can avoid measurement steps and physical inspections which increase the cycle time of the drilling process. The proposal contributes to the literature by presenting an unprecedented application and to the praxis by solving a relevant problem of the aerospace industry. [ABSTRACT FROM AUTHOR]

Surface roughness is widely used for product quality assessment due to its ability to accurately portray the fatigue strength, wear resistance, surface hardness, and other properties of a product. In this paper, a spatiotemporal adaptive ensemble prediction method (STAEP) was proposed through the combination of static cutting parameters and dynamic vibration signals. We firstly performed envelope analysis of the vibration signal for the amplitude modulation phenomenon of vibration measurement and extracted the surface roughness features of the signal envelope. Meanwhile, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was also performed to decompose the complex vibration signal into intrinsic mode functions of different frequency ranges. Then, the features contained in the processed vibration signal were extracted by statistics and one-dimensional convolutional neural network (1D-CNN), respectively. The extracted features were fused via a hybrid feature selection method based on Pearson correlation coefficient and random forest. Finally, the highly correlated features were fed into the spatiotemporal adaptive support vector regression and bi-directional gated recurrent unit for surface roughness ensemble prediction. In this paper, surface roughness prediction experiments were conducted on the open-source dataset S45C and GAMHE 5.0. In comparison with the results of the latest methods, the proposed model has the highest prediction accuracy on both datasets, and the mean absolute percentage error on the test set is reduced by 5.4395% on average compared to the best comparison method. Moreover, ablation experiments were conducted to verify the effectiveness of the proposed model and its components. [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]

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]

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]

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]

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]

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 present paper provides an overview of the state-of-the-art research, outlining the applications of the Industry 4.0 (I4.0) technologies on the aircraft manufacturing sector and their maturity state based on the technology readiness level (TRL) scale. A literature review has been conducted for the identification, selection, and evaluation of the published research. A total of 57 papers extracted from the two most relevant scientific databases for the area (Web of Science and Scopus), from 2010 to March 2021, were analysed and summarized. The research, analysis, and evaluation of these papers has provided an outlook of how the aircraft manufacturing industry is inserted into the I4.0 context, based on a classification of the I4.0 technologies maturity for this industrial branch. Then, a survey was performed with 12 specialists from 5 different aircraft manufacturing companies aiming to report the practical point-of-view in this area. Thus, this paper highlights and discusses the gaps found in the literature related to the I4.0 technologies applied to aircraft manufacturing and their main useful implications not only from the academic point-of-view but also from competitive business aspects, providing recommendations for industrial managers, engineers, and stakeholders. Finally, this paper proposes new opportunities and challenges for future research. [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]