scholarly journals Establishment of an Improved Material-Drilling Power Model to Support Energy Management of Drilling Processes

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2013 ◽  
Author(s):  
Shun Jia ◽  
Qingwen Yuan ◽  
Wei Cai ◽  
Qinghe Yuan ◽  
Conghu Liu ◽  
...  
Keyword(s):  
Machine Tool ◽  
Manufacturing Industry ◽  
Experimental Studies ◽  
Energy Modeling ◽  
Cnc Machining ◽  
Power Model ◽  
Cnc Milling ◽  
Machining Processes ◽  
Proposed Model ◽  
Process Energy

Drilling processes, as some of the most widely used machining processes in the manufacturing industry, play an important role in manufacturing process energy-saving programs. However, research focus on energy modeling of drilling processes, especially for the modeling of material-drilling power, are really scarce. To bridge this gap, an improved material-drilling power model is proposed in this paper. The obtained material-drilling power model can improve the accuracy of the material-drilling power and lay a good foundation for energy modeling and optimization of drilling processes. Finally, experimental studies were carried out on an XHK-714F CNC machining center (Hangzhou HangJi Machine Tool Co., Ltd., Hangzhou, China) and a JTVM6540 CNC milling machine (Jinan Third Machine Tool Co., Ltd., Jinan, China). The results showed that predictive accuracies with the proposed model are generally higher than 96% for all the test cases.

One Touch Workpiece Verification System for CNC Machining Using a Low-Cost Computer Vision Approach

2016 ◽  
Author(s):  
Maxwell K. Micali ◽  
Hayley M. Cashdollar ◽  
Zachary T. Gima ◽  
Mitchell T. Westwood
Keyword(s):  
Computer Vision ◽  
Low Cost ◽  
Cnc Machining ◽  
Potential Operator ◽  
Cnc Milling ◽  
Machining Processes ◽  
Loop Control ◽  
Operator Error ◽  
Verification System ◽  
Milling Machines

While CNC programmers have powerful tools to develop optimized toolpaths and machining plans, these efforts can be wholly undermined by something as simple as human operator error during fixturing. This project addresses that potential operator error with a computer vision approach to provide coarse, closed-loop control between fixturing and machining processes. Prior to starting the machining cycle, a sensor suite detects the geometry that is currently fixtured using computer vision algorithms and compare this geometry to a CAD reference. If the detected and reference geometries are not similar, the machining cycle will not start, and an alarm will be raised. The outcome of this project is the proof of concept of a low-cost, machine/controller agnostic solution that is applied to CNC milling machines. The Workpiece Verification System (WVS) prototype implemented in this work cost a total of $100 to build, and all of the processing is performed on the self-contained platform. This solution has additional applications beyond milling that the authors are exploring.

CNC Machine Tools

2009 ◽  
pp. 165-187 ◽  
Author(s):  
Xun Xu
Keyword(s):  
Machine Tool ◽  
Machine Tools ◽  
Manufacturing Industry ◽  
Human Action ◽  
Cnc Machining ◽  
Cnc Machine Tools ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Cnc Machines ◽  
Time Required

The introduction of CNC machines has radically changed the manufacturing industry. Curves are as easy to cut as straight lines, complex 3-D structures are relatively easy to produce, and the number of machining steps that required human action has dramatically reduced. With the increased automation of manufacturing processes with CNC machining, considerable improvements in consistency and quality can be achieved. CNC automation reduced the frequency of errors and provided CNC operators with time to perform additional tasks. CNC automation also allows for more flexibility in the way parts are held in the manufacturing process and the time required to change the machine to produce different components. In a production environment, a series of CNC machines may be combined into one station, commonly called a “cell”, to progressively machine a part requiring several operations. CNC controller is the “brain” of a CNC machine, whereas the physical configuration of the machine tool is the “skeleton”. A thorough understanding of the physical configuration of a machine tool is always a priority for a CNC programmer as well as the CNC machine tool manufacturers. This chapter starts with a historical perspective of CNC machine tools. Two typical types of CNC machine tools (i.e. vertical and horizontal machining centres) are first discussed. Tooling systems for a CNC machine tool are integral part of a CNC system and are therefore elaborated. Also discussed are the four principal elements of a CNC machine tool. They are machine base, machine spindle, spindle drive, and slide drive. What letter should be assigned to a linear or rotary axis and what if a machine tool has two sets of linear axes? These questions are answered later in the chapter. In order for readers to better comprehend the axis and motion designations, a number of machine tool schematics are given.

scholarly journals PREDICTION OF ENERGY CONSUMPTION IN THE LEADWELL V-40 IT CNC MACHINING CENTER THROUGH ARTIFICIAL NEURAL NETWORKS

2021 ◽  
pp. 1-5
Author(s):  
Miguel Angel Rodriguez Cabal ◽  
Juan Gonzalo Ardila Marín ◽  
Juan Sebastian Rudas Florez
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Energy Consumption ◽  
Manufacturing Industry ◽  
Cnc Machining ◽  
Machining Processes ◽  
Machining Center ◽  
Artificial Neural ◽  
Five Axis ◽  
Cnc Machining Center

Energy consumption in machining processes has become a problem for today's manufacturing industry. The use of neural networks and optimization algorithms for modeling and prediction of consumption as a function of the cut-off parameters in processes of this type has aroused the interest of research groups. The present work used artificial neural networks (ANN) to predict the energy consumption of a Leadwell V-40iT® five-axis CNC machining center, based on experimental data obtained through a factorial experimental design 53. ANN was programed in Matlab®. From the study was concluded that the depth per pass (Ap) is the variable that has the most influence on the prediction model of energy consumption with a 77% of relative importance, while the feed rate is the least relevant with 9% of importance.

A Decision Support System for Capturing CNC Operator Knowledge

2011 ◽  
Vol 5 (5) ◽  
pp. 655-662 ◽  
Author(s):  
Wikan Sakarinto ◽  
◽  
Hiroshi Narazaki ◽  
Keiichi Shirase
Keyword(s):  
Decision Support ◽  
Cnc Machining ◽  
Numerical Control ◽  
Cnc Milling ◽  
Machining Processes ◽  
Product Data ◽  
Know How ◽  
Milling Operations ◽  
Data Assessment ◽  
Computer Aided

The main job of Computer Numerical Control (CNC) operators is to capture and use knowledge to assess product data. CNC operators assess Computer-Aided Manufacturing (CAM) files before proceeding to CNC machining processes. Decision Support Systems (DSS), for these operators, is provided by Expert Systems (ES) designed to manage and learn intelligently from previous data and information and produce recommended actions and decisions. The purpose of the DSS is (i) to assist inexperienced operators in assessment using stored know-how of experienced operators and to collect additional knowledge in interaction between the DSS and experienced operators during semiautomatic assessment, and (ii) to present collected knowledge to users based on contexts or constraints the user must deal with in product data assessment. After outlining the DSS, the discussion is about its usefulness in dealing information and knowledge discrepancies between CAM and CNC operators - an important problem in practice that has been rather neglected so far - focusing on CNC milling operations.

A Relativistic Newtonian Mechanics Predicts with Precision the Results of Recent Neutrino-Velocity Experiments

2014 ◽  
Vol 6 (1) ◽  
pp. 1032-1035 ◽  
Author(s):  
Ramzi Suleiman
Keyword(s):  
Null Hypothesis ◽  
Experimental Studies ◽  
Theoretical Models ◽  
Newtonian Mechanics ◽  
Speed Of Light ◽  
Symmetry Principle ◽  
Proposed Model ◽  
Significant Difference ◽  
The One ◽  
Complete Collapse

The research on quasi-luminal neutrinos has sparked several experimental studies for testing the "speed of light limit" hypothesis. Until today, the overall evidence favors the "null" hypothesis, stating that there is no significant difference between the observed velocities of light and neutrinos. Despite numerous theoretical models proposed to explain the neutrinos behavior, no attempt has been undertaken to predict the experimentally produced results. This paper presents a simple novel extension of Newton's mechanics to the domain of relativistic velocities. For a typical neutrino-velocity experiment, the proposed model is utilized to derive a general expression for . Comparison of the model's prediction with results of six neutrino-velocity experiments, conducted by five collaborations, reveals that the model predicts all the reported results with striking accuracy. Because in the proposed model, the direction of the neutrino flight matters, the model's impressive success in accounting for all the tested data, indicates a complete collapse of the Lorentz symmetry principle in situation involving quasi-luminal particles, moving in two opposite directions. This conclusion is support by previous findings, showing that an identical Sagnac effect to the one documented for radial motion, occurs also in linear motion.

Effect of guide rail profile errors on the motion accuracy for a heavy-duty hydrostatic turntable

2019 ◽  
Vol 233 (15) ◽  
pp. 5350-5362 ◽  
Author(s):  
Yongsheng Zhao ◽  
Hongchao Wu ◽  
Congbin Yang ◽  
Ligang Cai ◽  
Zhifeng Liu
Keyword(s):  
Machine Tool ◽  
Reynolds Equation ◽  
Machining Accuracy ◽  
Guide Rail ◽  
Heavy Duty ◽  
Motion Equations ◽  
Rotating Speed ◽  
Proposed Model ◽  
Reaction Forces ◽  
Profile Errors

The motion accuracy of hydrostatic turntable is the key in improving the machining accuracy of heavy-duty machine tool. However, the motion accuracy of hydrostatic turntable depends not only on the offset load but also on the rotating speed of the turntable as well as the profile errors of the guide rails. In this paper, a simulation model is developed to analyze the effect of guide rail profile errors on the motion accuracy of hydrostatic turntable. The reaction forces of preload thrust bearing and hydrostatic circular oil pads are obtained based on the Reynolds equation of the lubricant film. The motion equations of hydrostatic turntable are derived in which the profile errors of two guide rails are considered. The results show that the motion accuracy of hydrostatic turntable can be affected by wavelength, amplitude of profile errors and speed, and offset load of turntable. Finally, the motion accuracy of heavy-duty hydrostatic turntable used in XCKA28105 type turning and milling composite machine tool is obtained by using the presented method. Comparing with the experimental results, the proposed model can be used to predict the machining accuracy caused by the profile errors of guide rails for any heavy-duty hydrostatic turntable.

scholarly journals Recurrent neural networks with long term temporal dependencies in machine tool wear diagnosis and prognosis

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Jianlei Zhang ◽  
Yukun Zeng ◽  
Binil Starly
Keyword(s):  
Neural Network ◽  
Tool Wear ◽  
Machine Tool ◽  
Recurrent Neural Network ◽  
Machine Tools ◽  
Prediction Performance ◽  
Sequential Data ◽  
Diagnosis And Prognosis ◽  
Proposed Model

AbstractData-driven approaches for machine tool wear diagnosis and prognosis are gaining attention in the past few years. The goal of our study is to advance the adaptability, flexibility, prediction performance, and prediction horizon for online monitoring and prediction. This paper proposes the use of a recent deep learning method, based on Gated Recurrent Neural Network architecture, including Long Short Term Memory (LSTM), which try to captures long-term dependencies than regular Recurrent Neural Network method for modeling sequential data, and also the mechanism to realize the online diagnosis and prognosis and remaining useful life (RUL) prediction with indirect measurement collected during the manufacturing process. Existing models are usually tool-specific and can hardly be generalized to other scenarios such as for different tools or operating environments. Different from current methods, the proposed model requires no prior knowledge about the system and thus can be generalized to different scenarios and machine tools. With inherent memory units, the proposed model can also capture long-term dependencies while learning from sequential data such as those collected by condition monitoring sensors, which means it can be accommodated to machine tools with varying life and increase the prediction performance. To prove the validity of the proposed approach, we conducted multiple experiments on a milling machine cutting tool and applied the model for online diagnosis and RUL prediction. Without loss of generality, we incorporate a system transition function and system observation function into the neural net and trained it with signal data from a minimally intrusive vibration sensor. The experiment results showed that our LSTM-based model achieved the best overall accuracy among other methods, with a minimal Mean Square Error (MSE) for tool wear prediction and RUL prediction respectively.

Model Research on Special Metal Cutting NC Machine Tool

2007 ◽  
Vol 10-12 ◽  
pp. 806-811
Author(s):  
Tong Zhao ◽  
P.Q. Ye ◽  
H. Zhang ◽  
X.K. Wang
Keyword(s):  
Machine Tool ◽  
Metal Cutting ◽  
Relation Module ◽  
Nc Machine Tool ◽  
Model Research ◽  
Unit Model ◽  
Proposed Model ◽  
Control Research ◽  
Function Unit ◽  
Nc Machine

In this paper the model of special metal cutting NC machine Tool is presented, which consists of a base module, an overall control module, particular functional modules as well as a relation module. Each module involved in aforementioned model will be composed by software, hardware and mechanical parts, so as to combine the convergence of the ideas of modularization and mechanical-electrical integration into current understanding of special NC machine tool through the proposed model. Specially, the relation module is introduced to deal with the linking among all the other modules. The presented model aims to broaden the perspective of machine designers intending to increase the efficiency in machine design. By giving the so-called function unit model a novel modeling approach is delivered to carry out control research of special metal cutting NC machine, which is followed by the formalization description method presented as a possible abstraction methodology towards the efficient description and identification of special metal cutting NC machine tool.

An analytical model for predicting the shear strength of unsaturated soils

2022 ◽  
pp. 1-57
Author(s):  
Tuan A. Pham ◽  
Melis Sutman
Keyword(s):  
Shear Strength ◽  
Analytical Model ◽  
Unsaturated Soils ◽  
High Performance ◽  
Micromechanical Model ◽  
Experimental Studies ◽  
Stress Equilibrium ◽  
Proposed Model ◽  
New Equation ◽  
Multi Phase

The prediction of shear strength for unsaturated soils remains to be a significant challenge due to their complex multi-phase nature. In this paper, a review of prior experimental studies is firstly carried out to present important pieces of evidence, limitations, and some design considerations. Next, an overview of the existing shear strength equations is summarized with a brief discussion. Then, a micromechanical model with stress equilibrium conditions and multi-phase interaction considerations is presented to provide a new equation for predicting the shear strength of unsaturated soils. The validity of the proposed model is examined for several published shear strength data of different soil types. It is observed that the shear strength predicted by the analytical model is in good agreement with the experimental data, and get high performance compared to the existing models. The evaluation of the outcomes with two criteria, using average relative error and the normalized sum of squared error, proved the effectiveness and validity of the proposed equation. Using the proposed equation, the nonlinear relationship between shear strength, saturation degree, volumetric water content, and matric suction are observed.

A Novel Error Equivalence Model on the Kinematic Error of the Linear Axis of High-End Machine Tool

2021 ◽  
Author(s):  
Xinxin LI ◽  
Zhi-Min Li ◽  
Sun Jin ◽  
Jichang Zhang ◽  
Siyi Ding ◽  
...  
Keyword(s):  
Machine Tool ◽  
Elastic Deformation ◽  
Numerical Control ◽  
Small Displacement ◽  
Kinematic Error ◽  
Guide Rail ◽  
Linear Guide ◽  
Proposed Model ◽  
Equivalence Model ◽  
Kinematic Errors

Abstract The kinematic errors of the linear axis play a key role in machining precision of high-end CNC (Computer Numerical Control) machine tool. The quantification of error relationship is still an urgent problem to be solved in the assembly process of the linear axis, especially considering the effect of the elastic deformation of rollers. A systematic error equivalence model of slider is proposed to improve the prediction accuracy for kinematic errors of the linear axis which contains the base, the linear guide rail and carriage. Firstly, the geometric errors of assembly surface of linear guide rail are represented by small displacement torsor. According to the theory of different motion of robots, the error equivalence model of a single slider is established, namely the geometric error of assembly surface of linear guide rail and the pose error of slider is equivalent to the elastic deformation of roller. Based on the principle of vector summation, the kinematic error of a single slider is mapped to the carriage and the kinematic error of the linear axis is obtained. Besides, experiments validation of kinematic error model of the linear axis is carried out. It is indicated that the proposed model is accurate and feasible. The proposed model can provide an accurate guidance for the manufacturing and operation performance of the linear axis in quantification, and a more effective reference for the engineers at the design and assembly stage.

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