Journal of Machine Engineering最新文献_第3页

A Comparative Study of CNN, LSTM, BiLSTM, and GRU Architectures for Tool Wear Prediction in Milling Processes 基于CNN、LSTM、BiLSTM和GRU结构的铣削刀具磨损预测比较研究

Journal of Machine Engineering Pub Date : 2023-10-18 DOI: 10.36897/jme/174019

Fabio C. Zegarra, Juan Vargas-Machuca, Alberto M. Coronado

{"title":"A Comparative Study of CNN, LSTM, BiLSTM, and GRU Architectures for Tool Wear Prediction in Milling Processes","authors":"Fabio C. Zegarra, Juan Vargas-Machuca, Alberto M. Coronado","doi":"10.36897/jme/174019","DOIUrl":"https://doi.org/10.36897/jme/174019","url":null,"abstract":"Accurately predicting machine tool wear requires models capable of capturing complex, nonlinear interactions in multivariate time series inputs. Recurrent neural networks (RNNs) are well-suited to this task, owing to their memory mechanisms and capacity to construct highly complex models. In particular, LSTM, BiLSTM, and GRU architectures have shown promise in wear prediction. This study demonstrates that RNNs can automatically extract relevant information from time series data, resulting in highly precise wear models with minimal feature engineering. Notably, this approach avoids the need for excessively large window sizes of data points during model training, which would increase model complexity and processing time. Instead, this study proposes a procedure that achieves low prediction errors with window sizes as small as 100 data points. By employing Bayesian hyperparameter optimization and two preprocessing techniques (detrend and offset), RMSE errors consistently fall below 10. A key difference in this study is the use of boxplots to provide a better representation of result variability, as opposed to solely reporting the best values. The proposed approach matches more complex state-of-the-art methods and offers a powerful tool for wear prediction in engineering applications.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884591","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

Journal of Machine Engineering Pub Date : 2023-10-17 DOI: 10.36897/jme/174018

Arash Ebrahimi Araghizad, Faraz Tehranizadeh, Kemal Kilic, Erhan Budak

引用次数: 0

Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements 淬硬模具钢回转车削的多目标优化节能和提高表面粗糙度

Journal of Machine Engineering Pub Date : 2023-09-27 DOI: 10.36897/jme/172877

Tat Khoa Doan, Trung Thanh Nguyen, An-Le Van

引用次数: 0

Towards the Digital Model of Tool Lifecycle Management in Sheet Metal Forming 钣金成形中刀具生命周期管理的数字化模型研究

Journal of Machine Engineering Pub Date : 2023-09-15 DOI: 10.36897/jme/171664

Vidosav D. Majstorovic, Vojin Vukadinovic, Jovan Zivkovic

引用次数: 0

Advanced Cascaded Scheduling for Highly Autonomous Production Cells with Material Flow and Tool Lifetime Consideration using AGVs 先进的级联调度高度自主生产单元与物料流和工具寿命的考虑使用agv

Journal of Machine Engineering Pub Date : 2023-09-06 DOI: 10.36897/jme/171749

Eddi Miller, Jan Schmitt, Tobias Kaupp, Bastian Engelmann

引用次数: 0

Recent Advances in Precision, Sustainability and Safety of Machine Tools 机床精度、可持续性和安全性的最新进展

Journal of Machine Engineering Pub Date : 2023-08-29 DOI: 10.36897/jme/169941

Uhlmann Eckart

{"title":"Recent Advances in Precision, Sustainability and Safety of Machine Tools","authors":"Uhlmann Eckart","doi":"10.36897/jme/169941","DOIUrl":"https://doi.org/10.36897/jme/169941","url":null,"abstract":"Machine tools are the main driver of economic, environmental and social sustainability in industrial production. The ongoing shift from mass production to highly individualized, small batch manufacturing requires machine tools to be more flexible to changing needs while maintaining at least the same level of productivity. However, flexibility and productivity are at odds with the necessity for resource and energy efficiency. At the same time, more sophisticated workpiece specifications are pushing the boundaries regarding precision and dynamics of machine tools. In such a high-performance context, machine safety plays a major role and is becoming increasingly challenging due to higher kinetic energies of moving components. This paper examines recent advances in machine tool precision, sustainability, and safety. Six comprehensive case studies are provided to illustrate how these improvements contribute to an increased productivity. Hardware and software solutions for pose-controlled robotic manufacturing and thermoelectrically tempered high-performance spindles will be presented. Modular machine tool frames based on building blocks and an adaptive cooling system with thermoelectric generators for linear direct drives demonstrate their major impact on resource and energy efficiency. Machine safety is addressed through an analysis of potential hazards as well as improved protective measures. Model-based predictions precisely identify critical process parameters that lead to unbalance-induced failure of slim tool extensions, while on the protection side, new statistical models are applied to assess the protective performance of safeguards much more accurately. The cutting-edge technologies for machine tools presented in this paper will help manufacturers to cope with current and future challenges in industrial production.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47254890","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

Unsupervised and Supervised Machine Learning Methods for Cutting Tool Path Clustering and RUL Estimation in Manufacturing 制造业刀具路径聚类和RUL估计的无监督和有监督机器学习方法

Journal of Machine Engineering Pub Date : 2023-08-25 DOI: 10.36897/jme/171432

Fabio C. Zegarra, J. Vargas-Machuca, A. Roman-Gonzalez, A. Coronado

引用次数: 0

Method of the environmentally friendly dry single-pass honing with use of the superimposed low frequency oscillations 利用叠加低频振荡的环保型干式单道珩磨方法

Journal of Machine Engineering Pub Date : 2023-08-24 DOI: 10.36897/jme/171391

Rozek André, Uhlmann Eckart

引用次数: 0

Surface Roughness Investigation Through Interplay of Cutting Speed and Thermal-Assisted Machining in High-Speed Machining of SKD11 Steel 切削速度与热辅助加工共同作用下SKD11钢高速加工表面粗糙度研究

Journal of Machine Engineering Pub Date : 2023-08-22 DOI: 10.36897/jme/170980

Long-Vinh Bui, Thi-Bich Mac, D. Nguyen

{"title":"Surface Roughness Investigation Through Interplay of Cutting Speed and Thermal-Assisted Machining in High-Speed Machining of SKD11 Steel","authors":"Long-Vinh Bui, Thi-Bich Mac, D. Nguyen","doi":"10.36897/jme/170980","DOIUrl":"https://doi.org/10.36897/jme/170980","url":null,"abstract":"This study aims to investigate the interplay between cutting speed and Thermal-Assisted Machining (TAM) concerning surface roughness during the high-speed machining of SKD11 steel. The integration of pre-cutting workpiece heating introduces a temperature factor that intricately affects surface roughness. The primary objective is to ascertain optimal speed and temperature ranges that synergistically enhance machining efficiency, curtail costs, and elevate surface quality. The experimental protocol initiates with room temperature milling of SKD11 steel, progressively elevating the temperature gradient to systematically appraise temperature's impact on surface roughness under both conventional and elevated cutting speeds. Subsequent experimentation, conducted within specific temperature thresholds, entails stepwise augmentation of cutting speed to elucidate the influence of high-speed conditions on surface roughness. The ensuing analysis meticulously examines the ramifications of distinct cutting speed intervals on surface roughness. Ultimately, the study furnishes pragmatic recommendations for judiciously selecting cutting speeds and heating temperature parameters across diverse machining scenarios.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46608721","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

A Study on the Influence of Printing Orientation in Metal Printing Using Material Extrusion Technology on the Mechanical Properties of 17-4 Stainless Steel Products 材料挤压金属印刷中印刷方向对17-4不锈钢制品力学性能影响的研究

Journal of Machine Engineering Pub Date : 2023-08-19 DOI: 10.36897/jme/170509

Cuong Van Nguyen, Longji Dang, A. Le, Danh Thanh Bui

引用次数: 0