scholarly journals A New Approach to the Consideration and Analysis of Critical Factors in Robotic Machining

2020 ◽  
Vol 10 (24) ◽  
pp. 8885 ◽  
Author(s):  
Iván Iglesias Sánchez ◽  
José Enrique Ares ◽  
Cristina González Gaya ◽  
Victor Rosales Prieto
Keyword(s):  
Tool Path ◽  
Cutting Tool ◽  
Experimental Tests ◽  
Industrial Robots ◽  
Process Conditions ◽  
Critical Factors ◽  
Robotic Machining ◽  
Robotic Cells ◽  
Experimental Trials ◽  
Path Deviation

The relative low stiffness of industrial robots is a major limitation on the development of flexible and reconfigurable systems in applications in which process forces and vibration lead into significant tool path deviations with respect to the programmed path as in the case of robotic machining. This paper presents a novel factorial procedure that allows for the preliminary study of the main conditions in robotic machining operations and it determines the critical factors that are affecting the machining path of any robotic cell in order to obtain the process conditions with lower path deviations. In this procedure the most influential robotic machining constraints were identified and classified, the factorial design of experiments was used to enable the execution of the experimental tests and the machining tool path deviation predictive methodology (PREMET) was used to determine the cutting tool path deviation between the programmed and the experimental path as a function of the process variables. Experimental trials have been carried out in order to determine the main factors that affect the robotic machining and influence the main constraints of the process, showing a reduction greater than a 36% of the cutting tool path deviation in groove milling of aluminum. The critical factors identified in order of importance are: hardness of the material, location of the workpiece, orientation of milling head relative to working direction and cutting conditions. This procedure can be extended to future factorial studies to improve the precision of robotic machining (in operations such as face milling, contouring, pocketing) and to establish design criteria for machining robotic cells.

A Generic, Geometric Approach to Accurate Machining-Error Predictions for 3-Axis CNC Milling of Sculptured Surface Parts: Part I — Modeling and Formulation

2006 ◽  
Author(s):  
Zezhong C. Chen ◽  
Wei Cai
Keyword(s):  
Tool Path ◽  
Cutting Tool ◽  
Geometric Model ◽  
Research Work ◽  
Geometric Approach ◽  
Cnc Machining ◽  
Sculptured Surface ◽  
Machining Error ◽  
Machining Errors ◽  
Tool Surface

In CNC machining, machining errors are usually caused by some of the sources such as cutting tool deflection, cutting tool wear, machine tool vibration, improper coolant/lubrication, and negative thermal effect. To increase product accuracy, much research has been carried out on the prediction of machining errors. However, in milling of sculptured surface parts, due to their curved shapes, the geometries of cutting tools do not match the parts’ surfaces well if the tools cut along the tool paths on the surfaces in a point-to-point way. As a consequence, machining error is inevitable, even if there is no other source of error in ideal machining conditions. To predict machining errors caused by this tool-surface mismatch, several methods have been proposed. Some of them are simple, and some represent the geometry of machined surfaces using cutter-swept surfaces. But none of these methods is accurate and practical. In this research work, a generic, geometric approach to predicting machining errors caused by the tool-surface mismatch is proposed for 3-axis sculptured surface milling. First, a new geometric model of the furrow formed by an APT tool moving between two neighboring cutter contact (CC) points is built. Second, the mathematical formula of cutting circle envelopes is derived. Then an algorithm for calculating machining errors in each tool motion is provided. Finally, this new approach is applied to two practical parts for the accurate machining-error predictions, and these predictions are then compared to the inaccurate predictions made by two established methods to demonstrate the advantages of this approach. This approach can be used in tool path planning for high precision machining of sculptured surface parts.

Development of Multi-Axis Laser-Assisted Milling Device

2017 ◽  
Author(s):  
Dong-Hyeon Kim ◽  
Wan-Sik Woo ◽  
Won-Shik Chu ◽  
Sung-Hoon Ahn ◽  
Choon-Man Lee
Keyword(s):  
Heat Source ◽  
Tool Path ◽  
Cutting Tool ◽  
Field Studies ◽  
Flat Surfaces ◽  
Laser Heat ◽  
Complex Shapes ◽  
Laser Heat Source ◽  
Removal Processes ◽  
Machining Productivity

Laser-assisted machining (LAM) process is an effective method to facilitate material removal processes for difficult-to-cut materials. In LAM process, the mechanical strength of various materials is reduced by a laser heat source focused in front of the cutting tool during machining. Since the laser heat source is located ahead of the cutting tool, the workpiece is preheated by the heat source. This enables difficult-to-cut materials to be machined more easily with low cutting energy, increasing the machining productivity and accuracy. It is difficult to apply laser-assisted milling (LAMilling) to workpieces having complex shapes, because it is not easy to control laser preheating and the cutting tool path for three-dimensionally shaped workpieces. LAMilling has only been used in limited fields such as single-direction machining of flat surfaces. To apply this process in the industrial field, studies on workpieces having various shapes are needed. This study aims to develop a laser-assisted milling device having multiple axes and to investigate the machining characteristics of several difficult-to-cut materials.

scholarly journals Kinematic Tool-Path Smoothing for 6-Axis Industrial Machining Robots

2021 ◽  
Vol 15 (5) ◽  
pp. 621-630
Author(s):  
Shingo Tajima ◽  
◽  
Satoshi Iwamoto ◽  
Hayato Yoshioka
Keyword(s):  
High Speed ◽  
Tool Path ◽  
Trajectory Generation ◽  
Linear Interpolation ◽  
Joint Space ◽  
Industrial Robots ◽  
Generation Algorithm ◽  
High Flexibility ◽  
Tool Motion ◽  
Trajectory Generation Algorithm

The demands for machining by industrial robots have been increasing owing to their low installation cost and high flexibility. A novel trajectory generation algorithm for high-speed and high-accuracy machining by industrial robots is proposed in this paper. Linear interpolation in the workspace and smooth trajectory generation at the corners are important in industrial machining robots. Because industrial robots are composed of rotational joints, the joint space has a nonlinear relationship with the workspace. Therefore, linear interpolation in the joint space, which has been widely used in conventional machine tools, does not guarantee linear interpolation in the actual machining workspace. This results in the degradation of the machining surface. The proposed trajectory generation algorithm based on the decoupled approach can achieve linear interpolation in the workspace by separating the position commands into Cartesian coordinates and the orientation commands into spherical coordinates. In addition, a novel corner smoothing method that generates a smooth and continuous trajectory from discrete commands is proposed in this paper. The proposed kinematic local corner smoothing generates a smooth trajectory by using a 3-segmented constant jerk profile at the corners in the joint space. The sharp corners can thereby be replaced by smooth curves. The resulting cornering error is controlled by varying the cornering duration. The simulation results demonstrate the effectiveness of the proposed kinematic smoothing algorithm in achieving linear tool motion in straight sections and in generating smooth trajectories at corner sections within the user-defined tolerance.

Some Theory and Algorithms Pertaining to Machinability and Visibility

Manufacturing ◽  
2002 ◽  
Author(s):  
Mahadevan Balasubramaniam ◽  
Taejung Kim ◽  
Sanjay Sarma
Keyword(s):  
Path Planning ◽  
Tool Path ◽  
Cutting Tool ◽  
Machining Process ◽  
Planning Problem ◽  
Topological Connectivity ◽  
Almost All ◽  
Feasible Space ◽  
Path Planning Problem ◽  
Theoretical Results

In previous work, we and others have developed visibility-based tool path generation schemes. Almost all previous research implicitly assumes that all visible parts are machinable. Though usually true practice, this assumption hides several subtleties inherent to the geometry of the machining process. Here, we define machinability in a stricter sense, as a generalization of the robotic path planning problem. Then, we define various “tight” necessary conditions for strict machinability, and show the connections between these conditions. After demonstrating the richness of the information contained in visibility, we show how to compute visibility effectively. Visible directions constitute an approximate feasible configuration space of a cutting tool. We also address questions pertaining to the topological connectivity of the feasible space. The theoretical results of this paper lay down a firmer foundation of machining path planning.

Geometric Modeling of Cutter/Workpiece Engagements in 3-Axis Milling Using Polyhedral Models

2007 ◽  
Author(s):  
Eyyup Aras ◽  
Derek Yip-Hoi
Keyword(s):  
Cutting Forces ◽  
Geometric Modeling ◽  
Tool Path ◽  
Cutting Tool ◽  
Milling Process ◽  
Mapping Technique ◽  
Depth Of Cut ◽  
Modeling Methodology ◽  
Machining System ◽  
Engagement Angle

Modeling the milling process requires cutter/workpiece engagement (CWE) geometry in order to predict cutting forces. The calculation of these engagements is challenging due to the complicated and changing intersection geometry that occurs between the cutter and the in-process workpiece. This geometry defines the instantaneous intersection boundary between the cutting tool and the in-process workpiece at each location along a tool path. This paper presents components of a robust and efficient geometric modeling methodology for finding CWEs generated during 3-axis machining of surfaces using a range of different types of cutting tool geometries. A mapping technique has been developed that transforms a polyhedral model of the removal volume from Euclidean space to a parametric space defined by location along the tool path, engagement angle and the depth-of-cut. As a result, intersection operations are reduced to first order plane-plane intersections. This approach reduces the complexity of the cutter/workpiece intersections and also eliminates robustness problems found in standard polyhedral modeling and improves accuracy over the Z-buffer technique. The CWEs extracted from this method are used as input to a force prediction model that determines the cutting forces experienced during the milling operation. The reported method has been implemented and tested using a combination of commercial applications. This paper highlights ongoing collaborative research into developing a Virtual Machining System.

A novel approach to machining process fault detection using unsupervised learning

2020 ◽  
pp. 095440542093755
Author(s):  
Thomas McLeay ◽  
Michael S Turner ◽  
Keith Worden
Keyword(s):  
Fault Detection ◽  
Unsupervised Learning ◽  
Tool Path ◽  
Cutting Tool ◽  
Novelty Detection ◽  
Cutting Parameters ◽  
Machining Process ◽  
Machining Processes ◽  
Workpiece Material ◽  
Data Set

The most common machining processes of turning, drilling, milling and grinding concern the removal of material from a workpiece using a cutting tool. The performance of machining processes depends on a number of key method parameters, including cutting tool, workpiece material, machine configuration, fixturing, cutting parameters and tool path trajectory. The large number of possible configurations can make it difficult to implement fault detection systems without having to train the system to a particular method or fault type. The research of this article applies a novel method to detect the changing state of a process over time in order to detect faulty machining conditions such as worn tools and cutting depth changes. Unlike studies in the previous literature in this domain, an unsupervised learning method is used, so that the method can be applied in production to unfamiliar processes or fault conditions. In the case presented, novelty detection is applied to a multivariate sensor feature data set obtained from a milling process. Sensor modalities include acoustic emission, vibration and spindle power and time and frequency domain features are employed. The Mahalanobis squared-distance is used to measure discordancy of each new data point, and values that exceed a principled novelty threshold are categorised as fault conditions.

Adaptive Industrial Robots Using Machine Vision

2018 ◽  
Author(s):  
Vladimir Kuts ◽  
Tauno Otto ◽  
Toivo Tähemaa ◽  
Khuldoon Bukhari ◽  
Tengiz Pataraia
Keyword(s):  
Machine Vision ◽  
Manufacturing Industry ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Engineering Industry ◽  
Test Environment ◽  
Operation System ◽  
Robotic Cells ◽  
Self Learning ◽  
Human Robot Collaboration

The use of industrial robots in modern manufacturing scenarios is a rising trend in the engineering industry. Currently, industrial robots are able to perform pre-programmed tasks very efficiently irrespective of time and complexity. However, often robots encounter unknown scenarios and to solve those, they need to cooperate with humans, leading to unnecessary downtime of the machine and the need for human intervention. The main aim of this study is to propose a method to develop adaptive industrial robots using Machine Learning (ML)/Machine Vision (MV) tools. The proposed method aims to reduce the effort of re-programming and enable self-learning in industrial robots. The elaborated online programming method can lead to fully automated industrial robotic cells in accordance with the human-robot collaboration standard and provide multiple usage options of this approach in the manufacturing industry. Machine Vision (MV) tools used for online programming allow industrial robots to make autonomous decisions during sorting or assembling operations based on the color and/or shape of the test object. The test setup consisted of an industrial robot cell, cameras and LIDAR connected to MATLAB through a Robot Operation System (ROS). The online programming tests and simulations were performed using Virtual/Augmented Reality (VR/AR) toolkits together with a Digital Twin (DT) concept, to test the industrial robot program on a digital object before executing it on the real object, thus creating a safe and secure test environment.

Off-line error compensation in corner milling process

2016 ◽  
Vol 232 (7) ◽  
pp. 1172-1181 ◽  
Author(s):  
Caixu Yue ◽  
Xianli Liu ◽  
Yunpeng Ding ◽  
Steven Y Liang
Keyword(s):  
Cutting Force ◽  
Error Compensation ◽  
Tool Path ◽  
Chip Thickness ◽  
Milling Process ◽  
Process Conditions ◽  
Force Model ◽  
Tool Deflection ◽  
Profile Error ◽  
Compensation Algorithm

Tool deflection induced by cutting force could result in dimensional inaccuracies or profile error in corner milling process. Error compensation has been proved to be an effective method to get accuracy component in milling process. This article presents a methodology to compensate profile errors by modifying tool path. The compensation effect strongly depends on accuracy of the cutting force model used. The mathematical expression of chip thickness is proposed based on the true track of cutting edge for corner milling process, which considers the effect of tool deflection. The deflection of tool is calculated by finite element method. Then, an off-line compensation algorithm for corner profile error is developed. Following the theoretical analysis, the effect of the error compensation algorithm is verified by experimental study. The outcome provides useful comprehension about selection of process conditions for corner milling process.

Tool Path Generation Method of Equal Approximation Error for Free-Form Surface in High Speed Machining

2010 ◽  
Vol 102-104 ◽  
pp. 544-549 ◽  
Author(s):  
Chun Jiang Zhou ◽  
Hong Chun Chen
Keyword(s):  
High Speed ◽  
Tool Path ◽  
Cutting Tool ◽  
End Milling ◽  
Approximation Error ◽  
Tool Path Generation ◽  
Free Form ◽  
Path Generation ◽  
High Speed Machining ◽  
Free Form Surface

The development of surface high-speed machining has put forward higher demands for uniform cutting load and smooth cutting tool path. Most current tool-path planning methods are based on constant scallop height, but they have the disadvantage of path point redundancy during the path discretization process. To overcome the problem, a tool path generation method of equal approximation error in each step for free-form surface is presented based on geodesic principle and curvature judgment. In this method, the NURBS curve is employed to realize smooth transition for adjacent two tool paths in high-speed machining. A certain angle of inclination of flat-end milling cutter during multi-axis machining improves the machining efficiency. Because of the advantage of this machining condition, the cutter location point generation algorithm during the machining condition is given by the method. The method is verified and simulated by C++. Experiment results proved that it can obtain uniform cutting load and continuous smooth cutting tool path during surface high-speed machining by the proposed method.

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