Journal of Machine Engineering最新文献

Fracture Mechanics-Based Modelling of Tool Wear in Machining Ti6Al4V Considering the Microstructure of Cemented Carbide Tools 基于断裂力学的加工 Ti6Al4V 时刀具磨损建模（考虑硬质合金刀具的微观结构

Journal of Machine Engineering Pub Date : 2024-06-07 DOI: 10.36897/jme/189588

Hossein Gohari, Bin Shi, M. H. Attia, Rachid M'Saoubi

{"title":"Fracture Mechanics-Based Modelling of Tool Wear in Machining Ti6Al4V Considering the Microstructure of Cemented Carbide Tools","authors":"Hossein Gohari, Bin Shi, M. H. Attia, Rachid M'Saoubi","doi":"10.36897/jme/189588","DOIUrl":"https://doi.org/10.36897/jme/189588","url":null,"abstract":"This study introduces a new wear model that can predict tool life in the milling process of Ti6Al4V using a cemented carbide tool. The model uses a finite element (FE) simulation to predict crack growth in the tool material microstructure. The FE model evaluates the crack propagation rate based on the real microstructure of the tool material, which is captured from microscopic images. To determine the normal and tangential forces operating on the flank face, an experimental procedure was developed based on three different flank wear widths. The FE model utilizes the elastic and fracture properties of tungsten carbide, and the elastic-plastic and fracture characteristics of cobalt binder to determine crack growth under the applied cutting forces. The crack propagation information combined with cutting conditions and the initial wear level are used to estimate the tool wear state. The developed model can predict tool life under different cutting conditions, tool geometries, and microstructure properties. Analysis of results showed that the error for the straight cuts was less than 6%, while for the complex cuts, it reached up to 20%. The accuracy of the model can be improved by extending the calibration test to higher levels of flank wear.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141371495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fuzzy Logic in Risk Assessment of Production Machines Failure in Forming and Assembly Processes 模糊逻辑在成型和装配过程中生产设备故障风险评估中的应用

Journal of Machine Engineering Pub Date : 2024-06-07 DOI: 10.36897/jme/189667

Anna Burduk, Dagmara Łapczyńska, Joanna Kochańska, K. Musiał, Jozef Husár

引用次数: 0

Influence of the Substrate Size on the Cooling Behavior and Properties of the DED-LB Process 基底尺寸对 DED-LB 工艺冷却行为和特性的影响

Journal of Machine Engineering Pub Date : 2024-06-06 DOI: 10.36897/jme/189582

Fabian Bieg, Clemens Maucher, H. Möhring

{"title":"Influence of the Substrate Size on the Cooling Behavior and Properties of the DED-LB Process","authors":"Fabian Bieg, Clemens Maucher, H. Möhring","doi":"10.36897/jme/189582","DOIUrl":"https://doi.org/10.36897/jme/189582","url":null,"abstract":"The laser-based Directed Energy Deposition (DED-LB) process involves a complex thermal history which strongly de-pends on the geometry of the deposited structure and substrate. The thermal mechanisms of the process are highly influenced by key process parameters like laser power, powder mass flow and scanning speed. Additionally, the size of the substrate influences the cooling behavior. The cooling behavior can be externally influenced and controlled by tempering the substrate, for example using a laser preheating method. The control of the cooling rate is crucial to ensure consistent properties and maintain constant conditions for subsequent finishing processes, irrespective of the size and geometry of the deposited structure and substrate. In this work, the influence of the substrate size on the cooling behavior and the properties of DED-LB manufactured structures is determined. The deposition of a cube with an edge length of 30 mm on different sized substrates and different cooling rates was simulated and executed. The impact of the different cooling behavior is evident in the hardness and the residual stresses of the deposited structures. Furthermore, the effect can be observed during a subsequent milling process. This work enables the creation of a model for the determination of the cooling rate and part properties depending on the substrate size.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"28 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic Detection of Axes for Turning Parts 自动检测用于车削零件的轴

Journal of Machine Engineering Pub Date : 2024-05-22 DOI: 10.36897/jme/188803

Martin Erler, Feyzi Emrah Başar, Alexander Brosius

引用次数: 0

Enabling Federated Learning Services Using OPC UA, Linked Data and GAIA-X in Cognitive Production 在认知生产中使用 OPC UA、关联数据和 GAIA-X 实现联合学习服务

Journal of Machine Engineering Pub Date : 2024-05-19 DOI: 10.36897/jme/188618

Christian Friedrich, Stefan Vogt, Franziska Rudolph, Paul Patolla, Jossy Milagros Grützmann, Orlando Hohmeier, Martin Richter, Ken Wenzel, Dirk Reichelt, Steffen Ihlenfeldt

{"title":"Enabling Federated Learning Services Using OPC UA, Linked Data and GAIA-X in Cognitive Production","authors":"Christian Friedrich, Stefan Vogt, Franziska Rudolph, Paul Patolla, Jossy Milagros Grützmann, Orlando Hohmeier, Martin Richter, Ken Wenzel, Dirk Reichelt, Steffen Ihlenfeldt","doi":"10.36897/jme/188618","DOIUrl":"https://doi.org/10.36897/jme/188618","url":null,"abstract":"Value creation in production is based on collaboration of different stakeholders and requires the secure and sovereign exchange of knowledge. Today, knowledge has mostly been built up individually and is only exchanged in a proprietary manner. This paper presents an exemplary pipeline for federated services in cross-domain and cross-company value creation networks for cognitive production. On the example of collaboratively training of a federated machine learning model, machine tool lifetime is predicted in industrial manufacturing for high-end operating resources (high-quality cutting tools). From the shop floor to the cloud, all service relevant information is structured using existing digital twin standards and a linked data approach. In particular, the Industry 4.0 Asset Administration Shell (AAS) and OPC UA are used for collecting and referencing operational and engineering data. GAIA-X connectors transfer the service relevant data through a shared data space. The solution enables intelligent analysis and decision-making under the prioritization of data sovereignty and transparency and, therefore, acts as an enabler for future collaborative, data-driven manufacturing applications.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"111 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141124934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In-Process Monitoring of Inhomogeneous Material Characteristics Based on Machine Learning for Future Application in Additive Manufacturing 基于机器学习的非均质材料特性序中监控，未来可应用于增材制造领域

Journal of Machine Engineering Pub Date : 2024-05-13 DOI: 10.36897/jme/187872

André Jaquemod, Marijana Palalić, Kamil Güzel, H. Möhring

{"title":"In-Process Monitoring of Inhomogeneous Material Characteristics Based on Machine Learning for Future Application in Additive Manufacturing","authors":"André Jaquemod, Marijana Palalić, Kamil Güzel, H. Möhring","doi":"10.36897/jme/187872","DOIUrl":"https://doi.org/10.36897/jme/187872","url":null,"abstract":"Additively manufactured components often show insufficient component quality due to the formation of different defects. Defects such as porosity result in material inhomogeneity and structural integrity issues. The integration of in-process monitoring in machining processes facilitates the identification of inhomogeneity characteristics in manufacturing, which is crucial for process adaptation. The incorporation of artificial defects in components has the potential to mimic and study the behaviour of real-world defects in a more controlled way. This study highlights the potential benefits of cutting force and vibration monitoring during machining operations with the goal of providing insights into the machining behaviours and the effects of the artificially introduced defects on the process. Detection of anomalies relies on identifying changes in force profiles or vibration patterns that might indicate the interaction between the tool and the defect. Machine learning algorithms were used to process and interpret the collected data. The algorithms are trained to recognize patterns, anomalies, or deviations from expected behaviours, which can aid in evaluating the effect of detected defects on the machining process and the resultant component quality. The main objective of this study is to contribute to enhancing quality control of machining processes for inhomogeneous materials.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"123 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140985441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Use of 3-DOF Laser Interferometer for Rapid Estimation of CNC Drives Settings 使用 3-DOF 激光干涉仪快速估算 CNC 驱动器的设定值

Journal of Machine Engineering Pub Date : 2024-05-13 DOI: 10.36897/jme/188203

G. Budzyń, J. Rzepka

引用次数: 0

Impact of a Variation in Wire Feed Speed on Deposits from the Wire Arc Additive Manufacturing (WAAM) 送丝速度变化对线弧快速成型（WAAM）沉积物的影响

Journal of Machine Engineering Pub Date : 2024-05-13 DOI: 10.36897/jme/188308

Alizée Remy, U. Nwankpa, M. Rauch, J. Hascoët, G. Ruckert

{"title":"Impact of a Variation in Wire Feed Speed on Deposits from the Wire Arc Additive Manufacturing (WAAM)","authors":"Alizée Remy, U. Nwankpa, M. Rauch, J. Hascoët, G. Ruckert","doi":"10.36897/jme/188308","DOIUrl":"https://doi.org/10.36897/jme/188308","url":null,"abstract":"Metal Additive Manufacturing (MAM) is one of the innovative industrial technologies of the last decade, which presents some benefits as compared to traditional manufacturing techniques. MAM is faster, less expensive, and allow the manufacturing of large, complex components than casting, foundry etc. Understanding the influence of process parameters on the deposited matter and material characteristics is essential for the manufacturing of industrial parts. Current research concentrates on the impact of parameters on the fabricated structure geometry, microstructure and mechanical properties. There are limited number of studies, that focus on the possibility of Wire Feed Speed (WFS) parameter variation during deposition. In this work, a series of trials were realised with Cold Metal Transfer. The results showed that the quantity of material deposited was lesser than the theoretical value. The variation obtained was explained by the difference between the inputted WFS on the generator and the actual WFS output. Hence, the result on the influence of the variation of WFS on bead geometry was applied to a thermofluid model with Ti-6Al-4V alloy to confirm the sensitivity of this parameter in the quantity and geometry of the material deposited.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"81 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140983329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Potential of Additive Manufacturing of Metal Components to Reduce Environmental Impacts 金属部件增材制造在减少环境影响方面的潜力

Journal of Machine Engineering Pub Date : 2024-04-15 DOI: 10.36897/jme/186988

Antoine Balidas, O. Kerbrat, J. Hascoet

引用次数: 0

A New Grey Box Approach for Friction Modelling of Machine Tool Drives 机床驱动摩擦建模的灰箱新方法

Journal of Machine Engineering Pub Date : 2024-03-20 DOI: 10.36897/jme/186269

A. Rüppel, M. Meurer, Thomas Bergs

{"title":"A New Grey Box Approach for Friction Modelling of Machine Tool Drives","authors":"A. Rüppel, M. Meurer, Thomas Bergs","doi":"10.36897/jme/186269","DOIUrl":"https://doi.org/10.36897/jme/186269","url":null,"abstract":"Measurement of the process force in milling is usually conducted by using piezo-electric dynamometers which are costly and reduce the stiffness of the system. A less invasive alternative is an indirect estimation of cutting forces based on the power of the servo drives. However, a correction of frictional effects from the transmission system is necessary to achieve accurate results. Most machine tools are equipped with ball-screw drives whose friction behavior is highly nonlinear due to dependency on both velocity and position. This study provides a novel approach to consider all frictional and inertial effects in transmission behavior of ball-screw drives by utilizing the well-established generalized M AXWELL slip (GMS) model and combines it with a data-based approach, namely support vector regression (SVR). The approach acquires the internal states of the GMS model and uses them as an addition-nal input for the SVR. The model is validated on different experiments conducted on a five-axis machining center and compared to established friction models, as well as a sole SVR. The results show the model to have errors between 7% and 12% over the full working range of the x-and y-axes, respectively, outperforming the benchmark models significantly.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"28 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140226727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0