Modeling and Identification of Feed Drive Kinematics and Cycle Time Calculation

Manufacturing ◽  
2003 ◽  
Author(s):  
Wencai Wang ◽  
Derek M. Yip-Hoi
Keyword(s):  
Machine Tool ◽  
Cycle Time ◽  
Manufacturing Systems ◽  
Kinematic Model ◽  
Cnc Machine ◽  
Machining Processes ◽  
Calculation Algorithm ◽  
Motion Data ◽  
Feed Drive ◽  
Time Calculation

Cycle time calculation plays a major role in the design of manufacturing systems. Accurate estimates are needed to correctly determine the capacity of a line in terms of the number of machines that must be purchased. Over estimation results in excess capacity and under estimation leads to unsatisfied demand. Due to the high automation and cutting speeds of modern machining processes, cycle time calculation must consider both the timing of various machining actions and the kinematics of feed motions. This paper presents a cycle time calculation algorithm that gives accurate cycle time results by considering the effects of jerk and acceleration of the machine tool drives. The kinematic model for axis motion is based on trapezoidal acceleration profiles along the toolpaths. Based on this model, an algorithm for identifying the kinematic parameters has been developed. This algorithm has the advantage of utilizing a minimal set of axis motion data thus reducing the amount of data that must be collected from experiments by the machine tool vendor or the machine tool’s enduser. The proposed cycle time calculation algorithm has been verified in machining a V6 cylinder head on a four axis CNC machine.

Researches Regarding the Use of Fuzzy Controllers within CNC Feed Drives

2015 ◽  
Vol 772 ◽  
pp. 229-234
Author(s):  
Radu Eugen Breaz ◽  
Octavian Bologa
Keyword(s):  
Machine Tool ◽  
Fuzzy Controller ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Fuzzy Controllers ◽  
Feed Drive ◽  
Feed Drives ◽  
Simulation Based ◽  
Position Controller ◽  
Dc Servomotor

This paper presents some simulation based upon a dynamic model of a feed-drive within the structure of a CNC machine tool. A DC servomotor was considered as actuation device for the feed drive. For a given set of parameters for the position controller, two fuzzy types of fuzzy controllers were tested by means of simulation. The first fuzzy controller was a proportional one, with one input and one output, while the second one was a two variables one, with two inputs and one outputp.

scholarly journals A Holonic-Based Self-Learning Mechanism for Energy-Predictive Planning in Machining Processes

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 739 ◽  
Author(s):  
Seung-Jun Shin ◽  
Young-Min Kim ◽  
Prita Meilanitasari
Keyword(s):  
Machine Tool ◽  
Process Planning ◽  
Predictive Modeling ◽  
Manufacturing Systems ◽  
Minimum Energy ◽  
Hybrid Learning ◽  
Prototype System ◽  
Learning Approach ◽  
Machining Processes ◽  
Self Learning

The present work proposes a holonic-based mechanism for self-learning factories based on a hybrid learning approach. The self-learning factory is a manufacturing system that gains predictive capability by machine self-learning, and thus automatically anticipates the performance results during the process planning phase through learning from past experience. The system mechanism, including a modeling method, architecture, and operational procedure, is structured to agentize machines and manufacturing objects under the paradigm of Holonic Manufacturing Systems. This mechanism allows machines and manufacturing objects to acquire their data and model interconnection and to perform model-driven autonomous and collaborative behaviors. The hybrid learning approach is designed to obtain predictive modeling ability in both data-existent and even data-absent environments via accommodating machine learning (which extracts knowledge from data) and transfer learning (which extracts knowledge from existing knowledge). The present work also implements a prototype system to demonstrate automatic predictive modeling and autonomous process planning for energy reduction in milling processes. The prototype generates energy-predictive models via hybrid learning and seeks the minimum energy-using machine tool through the contract net protocol combined with energy prediction. As a result, the prototype could achieve a reduction of 9.70% with respect to energy consumption as compared with the maximum energy-using machine tool.

Investigating Cyber-Physical Threats of Numerically Controlled Manufacturing Processes

2020 ◽  
Author(s):  
Joseph Piacenza ◽  
Kenneth J. Faller ◽  
Bradley Regez ◽  
Luisfernando Gomez
Keyword(s):  
Manufacturing Systems ◽  
Ex Situ ◽  
Raspberry Pi ◽  
Manufacturing Processes ◽  
Device Design ◽  
Cnc Machine ◽  
Machining Processes ◽  
Machine Performance ◽  
Design Iteration ◽  
Lathe Machine

Abstract Motivated by cyber-physical vulnerabilities in precision manufacturing processes, there is a need to externally examine the operational performance of Computer Numerically Controlled (CNC) manufacturing systems. The overarching objective of this work is to design and fabricate a proof-of-concept CNC machine evaluation device, ultimately re-configurable to the mill and lathe machine classes. This device will assist in identifying potential cyber-physical security threats in manufacturing systems by identifying perturbations, outside the expected variations of machining processes, and comparing the desired command inputted into the numerical controller and the actual machine performance (e.g., tool displacement, frequency). In this directed research, a device design is presented based on specific performance requirements provided by the project sponsor. The first design iteration is tested on a Kuka KR 6 R700 series robotic arm, and machine movement comparisons are performed ex-situ using Keyence laser measurement sensors. Data acquisition is performed with a Raspberry Pi 4 microcomputer, controlled by custom, cross-platform Python code, and includes a touch screen human-computer interface. A device design adapted for a CNC mill is also presented, and the Haas TM-2 is used as a case study, which can be operated by technicians to check CNC machine accuracy, as needed, before a critical manufacturing process.

scholarly journals Integrated Geometric Error Compensation of Machining Processes on CNC Machine Tool

Procedia CIRP ◽  
2013 ◽  
Vol 8 ◽  
pp. 135-140 ◽  
Author(s):  
Xiaoyan Zuo ◽  
Beizhi Li ◽  
Jianguo Yang ◽  
Xiaohui Jiang
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Geometric Error ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Machining Processes

Analysis and Simulation of Screw Joint in CNC Machine Tool

2011 ◽  
Vol 141 ◽  
pp. 203-207
Author(s):  
Ya Wei Zhang ◽  
Wei Min Zhang
Keyword(s):  
Machine Tool ◽  
Fem Simulation ◽  
Cnc Machine Tools ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Feed Drive ◽  
Screw Joint ◽  
Drive Systems ◽  
Multi Body ◽  
Feed Drive System

CNC machine tools has always screw joints in its feed drive systems; In order to obtain good performance of CNC machine tool, it is necessary to model the screw joint with more accuracy and to research its influence on the vibration characters of the feed drive system. In this paper, the screw joint is analyzed by multi-body system theory and is modeled as flexible multi-body; Its mathematical describe of constraint condition is given by the modeling of screw joint. A revise factor is introduced into the process of FEM simulation to reflect the deformation in the screw joint. By this way, the effect of deformation in the screw joint is researched in the modeling under the ANSYS circumstance, the harmonic response under considering deformation contrast to that of without deformation. From the analysis in the simulation, it is necessary to take the deformation of screw joint into account.

Machining Accuracy Analysis for Computer-aided Fixture Design Verification

1996 ◽  
Vol 118 (3) ◽  
pp. 289-300 ◽  
Author(s):  
Y. Rong ◽  
Y. Bai
Keyword(s):  
Manufacturing Systems ◽  
Cnc Machine Tools ◽  
Machining Accuracy ◽  
Fixture Design ◽  
Accuracy Analysis ◽  
Design Verification ◽  
Cnc Machine ◽  
Machining Processes ◽  
Machining Errors ◽  
Computer Aided

This paper presents a machining accuracy analysis for computer-aided fixture design verification. While discussing the utilization of CNC machine tools and machining centers, machining errors are described in terms of deterministic and random components and analyzed on the bases of their sources, where high machining accuracy and multi-operation under a single setup become major characteristics of manufacturing systems. In machining processes, a resultant dimension may be generated in terms of several relevant dimensions. The dependency of variation among these dimensions is examined and the relationships of locating datum and machining surfaces are analyzed. Variation among linear and angular dimensions are considered. Five basic models of dimension variation relationships are proposed to estimate the machining error, where different formulas of resultant dimension variation are given for different combinations of variation among relevant dimensions. A datum-machining surface relationship graph (DMG) is developed to represent the dependent relationships. A matrix-based reasoning algorithm is designed to search for the shortest path in the DMG. Once the relationship between a specified pair of surfaces is identified, different models of corresponding relationships may be utilized to estimate the possible machining errors which can be used to compare the fixturing accuracy requirement.

scholarly journals INTELLIGENT MACHINING: REAL-TIME TOOL CONDITION MONITORING AND INTELLIGENT ADAPTIVE CONTROL SYSTEMS

2018 ◽  
Vol Vol.18 (No.1) ◽  
pp. 5-18 ◽  
Author(s):  
M. HASSAN ◽  
A. SADEK ◽  
M.H. ATTIA ◽  
V. THOMSON
Keyword(s):  
Adaptive Control ◽  
Real Time ◽  
Condition Monitoring ◽  
High Speed ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Tool Condition Monitoring ◽  
Cnc Machine ◽  
Machining Processes ◽  
Tool Condition

Unmanned manufacturing systems has recently gained great interest due to the ever increasing requirements of optimized machining for the realization of the fourth industrial revolution in manufacturing ‘Industry 4.0’. Real-time tool condition monitoring (TCM) and adaptive control (AC) machining system are essential technologies to achieve the required industrial competitive advantage, in terms of reducing cost, increasing productivity, improving quality, and preventing damage to the machined part. New AC systems aim at controlling the process parameters, based on estimating the effects of the sensed real-time machining load on the tool and part integrity. Such an aspect cannot be directly monitored during the machining operation in an industrial environment, which necessitates developing new intelligent model-based process controllers. The new generations of TCM systems target accurate detection of systematic tool wear growth, as well as the prediction of sudden tool failure before damage to the part takes place. This requires applying advanced signal processing techniques to multi-sensor feedback signals, in addition to using ultra-high speed controllers to facilitate robust online decision making within the very short time span (in the order of 10 ms) for high speed machining processes. The development of new generations of Intelligent AC and TCM systems involves developing robust and swift communication of such systems with the CNC machine controller. However, further research is needed to develop the industrial internet of things (IIOT) readiness of such systems, which provides a tremendous potential for increased process reliability, efficiency and sustainability.

Model of a CNC Feed Drive for On-Site Tuning of the Controllers for Single Axis Motion

2016 ◽  
Vol 841 ◽  
pp. 133-138
Author(s):  
Radu Eugen Breaz ◽  
Sever Gabriel Racz ◽  
Octavian Bologa ◽  
Melania Tera
Keyword(s):  
Machine Tool ◽  
Machine Tools ◽  
Cnc Machine Tools ◽  
Simulation Tool ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Feed Drive ◽  
Feed Drives ◽  
Contouring Accuracy ◽  
High Degree

The accuracy of CNC machine-tools is heavily influenced by the correct tuning of the feed drives controllers. While an initial tuning is performed by the machine-tool manufactures, in time the values have to be changed by the user in order to preserve positioning and contouring accuracy of the machine. This paper presents a model of a CNC feed drive, for a particular CNC machine-tool, but with a high degree of generality. The objective is to provide the user the necessary knowledge, together with a simple, yet accurate simulation tool, in order to assist him in the process of tuning the controllers.

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