The International Journal of Advanced Manufacturing Technology

Lin, Guilin; Shi, Hongyan; Liu, Xianwen; Wang, Zhaoguo; Zhang, Hao; Zhang, Junliang

doi: 10.1007/s00170-024-14193-4pmid: N/A

Difficult-to-machine materials are characterized by high hardness, strength, and anisotropy. During machining, tools can suffer from adhesion, abrasion, material detachment, and high cutting temperatures. These factors result in severe adhesive wear, abrasive wear, oxidative wear, and diffusion wear. Intense tool wear leads to more burrs, delamination, chipping, and dimensional errors in the parts. It significantly increases production costs and reduces machining efficiency. Therefore, further research into tool wear is of great importance. This paper reviews the characterization and monitoring of tool wear, the morphology and mechanism of wear, and measures for improving wear, with a focus on tool wear in the machining of difficult-to-machine materials. Through a comprehensive review of existing research findings, this work offers a perspective on the investigation of tool wear, providing an effective guide for future research. And it is of great significance to improve tool life and cutting quality.

Sujuan, Wang; Tao, Zhang; Bowen, Hu; Guoqun, Miu; Zhanwen, Sun; To, Sandy

doi: 10.1007/s00170-024-14129-ypmid: N/A

The milling process has proven to be a versatile process for the manufacturing of complex components at the macro- and micro-scales. Development of the cutting force prediction model in milling is important for process planning and optimization, as well as the controlling of machining accuracy. The well-established milling force prediction models include analytical, empirical, and numerical models, among which the analytical models are the most useful for characterizing the milling process and enhancing the understanding of the mechanics of the milling process. This paper makes a detailed review on the analytical models for the force predictions in macro- and micro-milling processes by analyzing the calculation modeling of the instantaneous uncut chip thickness (IUCT) and the determination methods of milling force coefficients. The development of the IUCT model starts from the studying of the effects of circular and trochoidal tool tip locus, later tool and workpiece deflections, tool runout, and tool wear, then the effects of cutting tool edge radius and workpiece material properties in the micro-milling process. The methods for cutting force coefficients are summarized and divided into three subgroups: the first is in constant form and obtained from the experiment, the second is expressed as the functions of the depth of cut, while the third is represented as the polynomial form under different influencing factors including machining conditions, tool geometries, and IUCT effect. The modeling laws and the key challenges for milling forces are also discussed for future research.

Shaikh, Mustafiz; Kahwash, Fadi; Lu, Zhilun; Alkhreisat, Mohammad; Mohammad, Ashfaq; Shyha, Islam

doi: 10.1007/s00170-024-14218-ypmid: N/A

This paper conceptualises an understanding of advanced manufacturing methods to develop 3D-printed metallic orthopaedic implants, including a brief discussion on post-process machining. The significance of Metallic Additive Manufacturing (MAM) and its practicality for industrial applications is discussed through a juxtaposition with conventional casting and machining approach. Different alloys and suitable MAM techniques are thoroughly reviewed to determine optimum operating conditions. Although MAM can produce near-net shape parts, post-processing is an unavoidable requirement to improve surface quality and dimensional accuracy. A comparative study is presented, highlighting the importance of machining for post-processing in terms of cost savings and performance. Different materials are evaluated aiming to overcome problems associated with existing orthopaedic implants. The consequence of bone-implant mechanical mismatch leading to stress shielding and inadequate corrosion properties obstructing biodegradability are explored in detail. The effect of additive manufacturing parameters on mechanical, corrosion, and surface properties including biocompatibility is analysed. Evidence of MAM’s advantages over conventional manufacturing approaches, such as the use of functionally graded lattices and patient-specific customised designs, is also presented. Finally, for future studies, a two-way approach is conceptualised with material selection and manufacturing process control in progressions of implant development using MAM.Graphical Abstract[graphic not available: see fulltext]

Feng, Yuzhou; Fan, Kaiguo

doi: 10.1007/s00170-024-14200-8pmid: N/A

In order to achieve the causal diagnosis of life health of high-speed spindle system, a digital twin (DT)–driven prediction method is proposed based on the real-time monitoring of thermal characteristics. The finite element method is used to achieve the DT for thermal characteristics through real time correcting the thermal boundaries using the correction models. The long short-term memory recurrent neural network (LSTM-RNN) is used to predict the heat generations of bearings and motor; the prediction results are used to diagnose the health status according to the domain and threshold models. A heat change rate–based causal diagnosis model is proposed to judge the fault sources. The spindle wear and fault experiments are carried out to verify the effectiveness of the proposed DT system. The experimental results show that the DT accuracy of thermal characteristics exceeds 95%, and the proposed DT system can successfully monitor the health status of the spindle system.

Wang, Haojie; Wang, Xiaoqiang; Tian, Yingjian; Ling, Yuanfei

doi: 10.1007/s00170-024-14189-0pmid: N/A

Ultrasonic rolling extrusion process (UREP) is the newly arisen surface strengthening technology, which can effectively reduce the surface roughness of the workpiece and improve the residual compressive stress at the certain depth on the surface so that it has great adaptability to the enhancement of the surface properties of the bearing ring. Through theoretical analysis, finite element simulation, and experiment method, the surface mechanical properties and the surface roughness of UREP strengthening when applied to the material of the wind power bearing ring are studied. Firstly, the strengthening principle of UREP is illustrated. Secondly, according to the motion trajectory of the rolling ball during UREP, the kinematic model of UREP is established. The forming principle of the surface micromorphology during UREP is explored. Thirdly, based on the contact characteristics between the rolling ball and the surface of the workpiece, the contact mechanics model of UREP is established. Based on Hertz contact theory, elastoplastic mechanics theory, and contact mechanics theory, the mechanical properties of the contact area between the rolling ball and the surface of the workpiece during UREP are analyzed. Finally, the simulation and experiment of 42CrMo steel cylindrical workpiece during UREP are carried out, and the variation trends in the simulation values are found to be consistent with those observed in the experimental results. The results show that the residual compressive stress generated in the surface of 42CrMo cylindrical workpiece after UREP gradually increases with the increase of the layer depth and then decreases and transforms into the residual tensile stress. Moreover, the surface roughness first decreases and then increases with the rise of the amplitude and the static pressure. Similarly, it gradually improves when the feed rate and rotational speed rises. The established UREP simulation is useful for imitating the actual machining process of 42CrMo steel during UREP, which extends the effective way for UREP parameter optimization.

Ying, Zechen; Jiang, Xiaojun; Zhang, Yun; Li, Sihong; Shen, Guancheng; Yang, Jin; Zhou, Huamin

doi: 10.1007/s00170-024-14171-wpmid: N/A

The stability of the injection molding process is critical to efficient production. However, environment and production disturbances pose challenges to maintaining a stable molding process. A two-stage dynamic adjustment strategy is proposed in this paper to increase weight consistency, considering fluctuation of density and fluidity based on products’ types and structure. This study investigates the factors influencing the weight stability of injection molding products during the injection and holding stages. Experiments show that the injection stage is affected by density fluctuations, while melt fluidity fluctuations influence the holding stage. Simulation experiments prove the efficacy of dynamic adjustment strategies for injection-sensitive products (ISP) and holding-sensitive products (HSP). Thinner products as ISPs benefit from adjustments of the injection stage parameters, while thicker products as HSPs require optimization of holding stage parameters. To prove its validity, this strategy was tested on two molds and improved weight stability by 60.0% and 34.8%, respectively.

Liu, Wengang; Shan, Chenwei; Qin, Kaifeng; Xia, Ziwen; Zhang, Menghua; Jia, Fangchao; Shu, Yiquan

doi: 10.1007/s00170-024-14165-8pmid: N/A

Thin-walled carbon/carbon (C/C) composites are a typical difficult-to-machine material due to the characteristics of thin walls, low stiffness, and high strength. In this paper, three ultrasonic-assisted machining methods and surface morphology of C/C composite thin-walled small holes were studied. The influence of machining parameters on average axial force and hole surface morphology was explored by single-factor experiments and orthogonal experiments. A quantitative comparison was conducted to evaluate the machining defects of drilling, reaming, and grinding. The results of single-factor experiments showed that the surface quality of drilling initially improved and then deteriorated with the increase of spindle speed. Additionally, increasing feed rate resulted in a deterioration in surface quality, while increasing amplitude to a certain extent led to an improvement. In orthogonal experiments, the effect of ultrasonic amplitude on the average axial force of reaming and grinding was greater than that of drilling. In terms of surface quality, the minimum evaluation factor Qc of the grinding, reaming, and drilling could reach 1.0137, 1.0198, and 1.0253, respectively. Further optimized by a multivariate optimization function, the optimal parameters of grinding were obtained as the speed of 6200 r/min, feed rate of 40 mm/min, and amplitude of 8 μm and the minimum values of Qc could reach 1.0128.

Gkertzos, Petros; Kotzakolios, Athanasios; Kostopoulos, Vassilis

doi: 10.1007/s00170-024-14173-8pmid: N/A

Due to the increase in 3D printing popularity, optimizing the procedure has become an important aspect of fused deposition modeling (FDM) research. As such, a numerical framework that captures the effect of all parameters involved in the process can aid in manufacturing optimization by overcoming the cost and time limitations of experimental methods. In this work, a numerical physics-based model is created that takes as input process parameters, simulates the phenomenon, and identifies the temperature history and developed mechanical stresses during printing. Initially, this model is validated through images taken from an infrared camera. Then, a design of experiments (DOE) sequence that covers the range of each input variable is created and multiple designs are evaluated. Correlations are examined and factor analysis on each output is performed indicating that material and bed temperature are the most important parameters affecting mechanical stresses, while fan speed dominates cooling. The simulation data are fed into data-driven models to provide accurate estimations on cooling duration, plastic strain, and von Misses stress and in turn aid in optimal parameter selection. This work improves existing numerical approaches by incorporating multiple process parameters and aids in digital twinning of FDM.

Malashin, Ivan; Martysyuk, Dmitriy; Tynchenko, Vadim; Evsyukov, Dmitriy; Nelyub, Vladimir; Borodulin, Aleksei; Gantimurov, Andrei; Galinovsky, Andrey

doi: 10.1007/s00170-024-14134-1pmid: N/A

The paper proposes a machine learning (ML) approach for clustering analysis to classify images from video recordings of melt pools during selective laser melting (SLM) printing process. By employing this method, each moment in the video is categorized into specific groups based on thermal impact. This allows for an understanding of the heat released on the surface at any given moment during printing. The greater the thermal impact on the powder, the higher the likelihood of defect occurrence. t-SNE method was used for dimensionality reduction of the image vectors. Subsequently, k-means and DBSCAN algorithms were applied to cluster these reduced dimensions. The resulting clustered images were then analyzed by an expert to determine the type of class: overheating, underheating, or normal. By identifying the location on the part where the image was taken, it was possible to trace the origin of potential defects.

Chen, Kao-Yi; Khoiruddin, Sukhoiri; Lin, Chieh-Fong; Ho, Ming-Hsiu; Huang, Cheng-Fu; Lee, Sheng-Chan; Chan, Chien-Wei; Mardiono, Intan; Fuh, Yiin-Kuen

doi: 10.1007/s00170-024-14178-3pmid: N/A

This study contributed to the comparison of insulation cotton configurations for the investment casting quality of industrial valve parts. Due to the complexity, parts of industrial valve bodies are usually produced by casting. However, the investment casting production process has several problems, such as shrinkage porosity. Currently, the investment casting industry uses cotton configuration to solve the problem of shrinkage porosity. Therefore, this study compared three cotton installation treatments in the mold shell to determine the optimal use of cotton. There are three schemes of the type of cotton installation on the shell that will be observed, including the triangular insulation cotton area denoted as case A installed 55-mm and case B installed 90-mm cotton on the right and left sides, and case C denoted with adding bracket arms on the upper side. In this study, we used RMM (retained melt modulus) and the finite element model to analyze the shrinkage porosity’s location and to monitor the porosity that occurred during the solidification process. The result showed that cotton could reduce shrinkage porosity by 3.30%, 1.95%, and 1.47% for case A, case B, and case C, respectively. Therefore, the best alternative is case C, add the cotton and bracket arm on the upper side, which is the optimal strategy to prevent shrinkage porosity.