Zerrendatu Ikerketa-Artikuluak honen arabera: egilea "2c5affc0a348a10ebc2b25f645e18192"
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A Coupled Eulerian Lagrangian Model to Predict Fundamental Process Variables and Wear Rate on Ferrite-pearlite Steels
Saez de Buruaga, Mikel; Esnaola, Jon Ander; Aristimuño, Patxi Xabier; Soler Mallol, Daniel; ARRAZOLA, PEDRO JOSE (Elsevier B.V., 2017)A coupled Eulerian-Lagrangian Finite Element model of the orthogonal cutting process was developed to predict the influence that ferritepearlite steel variants have on fundamental process variables and tool wear. As a case ... -
Determination of emissivity and temperature of tool rake face when cutting AISI 4140
Soler Mallol, Daniel; Aristimuño, Patxi Xabier; Saez de Buruaga, Mikel; ARRAZOLA, PEDRO JOSE (Elsevier B.V., 2019)A method for measuring tool temperature in the tool/chip contact zone of the rake face of a tool during dry orthogonal cutting using thermography is presented. This method used a new calibration method that combined with ... -
Determining tool/chip temperatures from thermography measurements in metal cutting
Saez de Buruaga, Mikel; Soler Mallol, Daniel; Aristimuño, Patxi Xabier; Esnaola, Jon Ander; ARRAZOLA, PEDRO JOSE (Elsevier, 2018)Temperature measurement in metal cutting is of central importance as tool wear and surface integrity have been demonstrated to be temperature dependent. In this context, infrared thermography is presented as a reliable ... -
Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process
ARRAZOLA, PEDRO JOSE; Aristimuño, Patxi Xabier; Saez de Buruaga, Mikel (Elsevier, 2023)Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data-driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing ... -
FEM modeling of hard turning 42CrMoS4 steel
Saez de Buruaga, Mikel; Gainza, Leire; Aristimuño, Patxi Xabier; Soler Mallol, Daniel; Ortiz-de-Zarate, Gorka; ARRAZOLA, PEDRO JOSE (Elsevier B.V., 2019) -
Mechanical properties of friction induced nanocrystalline pearlitic steel
Saez de Buruaga, Mikel; Soler Mallol, Daniel; ARRAZOLA, PEDRO JOSE (Springer Nature, 2022)Nanocrystalline structured variants of commercially available alloys have shown potential for boosting the mechanical properties of these materials, leading to a reduction in waste and thereby retaining feasible supply ... -
Microstructural aspects of the transition between two regimes in orthogonal cutting of AISI 1045 steel
Saez de Buruaga, Mikel; Soler Mallol, Daniel; ARRAZOLA, PEDRO JOSE (Elsevier, 2018)In depth understanding of tool-chip friction behavior is a significant aspect for tool wear performance in steels. In the present work attention has been paid to the strain mode of the chip section in contact with the rake ... -
Microstructure based flow stress model to predict machinability in ferrite–pearlite steels
Saez de Buruaga, Mikel; Aristimuño, Patxi Xabier; Soler Mallol, Daniel; ARRAZOLA, PEDRO JOSE (Elsevier Ltd., 2019)A new flow stress model is proposed to describe the behaviour of ferrite–pearlite steels based on microstructure properties, including the effect of high strains, strain rates and temperatures. The model introduces strain ... -
New Calibration method to measure Rake Face Temperature of the tool during Dry Orthogonal Cutting using Thermography
Soler Mallol, Daniel; ARRAZOLA, PEDRO JOSE; Aristimuño, Patxi Xabier; Saez de Buruaga, Mikel; Garay, Ainara (Elsevier Ltd., 2018)A new method for measuring temperature in the rake face of a tool during dry orthogonal cutting using ther- mography is presented. In addition, a new technique is also used to calibrate the infrared camera. Using ... -
A novel machine learning‐based methodology for tool wear prediction using acoustic emission signals
Saez de Buruaga, Mikel; Badiola, Xabier; Vicente, Javier (MDPI, 2021)There is an increasing trend in the industry of knowing in real-time the condition of their assets. In particular, tool wear is a critical aspect, which requires real-time monitoring to reduce costs and scrap in machining ... -
Tool remaining useful life prediction using bidirectional recurrent neural networks (BRNN)
Badiola, Xabier; Saez de Buruaga, Mikel; Vicente, Javier (Springer, 2023)Nowadays, new challenges around increasing production quality and productivity, and decreasing energy consumption, are growing in the manufacturing industry. In order to tackle these challenges, it is of vital importance ...