Simulation of Machining Operations Based on the VMT Concept (original) (raw)
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The future of machining lies in the fully autonomous machine tool. New technologies must be developed that predict, sense and action intelligent decisions autonomously. Digital twins are one component on this journey and are already having significant impact in the manufacturing industries. Despite this, the implementation of machining Digital Twins has been slow due to the computational burden of simulating cutting forces online resulting in no commercially available Digital Twin that can automatically control the machining process in real time. Addressing this problem, this research presents a machining Digital Twin capable of real-time adaptive control of intelligent machining operations. The computational bottleneck of calculating cutter workpiece engagements online has been overcome using a novel method which combines a priori calculation with real-time tool centre point position data. For the first time, a novel online machine-induced residual stress control system is presente...
VIRTUAL MODELLING AND SIMULATION OF A CNC MACHINE FEED DRIVE SYSTEM
This paper deals with the virtual modelling and simulation of a complex CNC machine tool feed drive system. The first phase of the study was the modelling of a very complex structure of the feed drive which consists of many elements (position, velocity and current control regulators, actuators, mechanical transmission elements, etc.). All these elements have great influence on important parameters of the machine tool such as movement stability, positioning accuracy and dynamic stiffness. For the modelling of the system the Matlab-SIMULINK and Matlab-Sim Scape Toolbox software was used. The Matlab-Sim Scape Toolbox allowed us to use the complete CAD model of the geometry of the machine tool, automatically calculating the selected properties. The influence of changing and optimizing several feed drive parameters (position loop gain Kv, proportional gain Kp of the velocity controller, integral gain of velocity controller-Tn, electrical drive time constant Te, total moving mass m, sampling period Ts, etc.) on the positioning accuracy and the dynamic stiffness was simulated, tested and validated. The finished Matlab-Simulink and Sim Scape models were initially visualized in the Matlab program. They were very simplified, comparing with their later visualization in the Virtual Reality EON Studio program.
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Tuning the control parameters of the feed drives for existing state of the art CNC machine tools, or retrofitting obsolete machine tools requires a close understanding of the position control process. The use of a mathematical model of the feed drive, combined with a computer simulation process is needed in order to fulfill the above mentioned tasks. In this paper some simulation tools for studying the CNC motion control systems are presented. Both single axis positioning regime and biaxial linear and circular interpolation regime were taken into consideration. The main goal of the research was to offer a handson integrated simulation tools compatible and able to use for improving the performances of both the existing industrial CNC controllers and also the PC-based controllers for retrofitted machine tools.
Development of a virtual machining system, part 3: cutting process simulation in transient cuts
International Journal of Machine Tools and Manufacture, 2002
In Parts 1 and 2 of this three-part paper, a mechanistic cutting force model was developed and machined surface errors for steady cuts under fixed cutting conditions were predicted. The virtual machining system aims to simulate and analyze the machining and the machined states in a general flat end-milling process. This frequently involves transient as well as steady cuts. Therefore, a method for simulating the cutting process of transient cuts needs to be developed to realize the virtual machining system concept. For this purpose, this paper presents a moving edge-node (ME) Z-map model for the cutting configuration calculation. The simulation results of four representative transient cuts in two-dimensional pocket milling and an application of off-line feed-rate scheduling are also given. In transient cuts, the cutting configurations that are used to predict the cutting force vary during the machining operation. The cutting force model (Part 1) and surface error prediction method (Part 2) were developed for steady cuts; these are extended to transient situations using the ME Z-map model to calculate the varying cutting configurations efficiently. The cutting force and surface errors are then predicted. To validate the feasibility of the proposed scheme, the measured and predicted cutting forces for transient test cuts were compared. The predicted surface error maps for transient cuts were constructed using a computer simulation. Also, off-line feed-rate scheduling is shown to be more accurately performed by applying the instantaneous cutting coefficients that were defined in Part I.
A comparison of model-based machining force control approaches
International Journal of Machine Tools …, 2004
Machining force regulation provides significant benefits in productivity and part quality. Adaptive techniques have typically been utilized due to the tremendous parameter variations that are found in machining processes. While adaptive controllers provide greater stability as compared to fixed-gain controllers, they have found very little headway in industry due to complexity in design, implementation, and maintenance. Recently, model-based techniques, with and without process compensation (i.e., the ability to directly adjust controller gains given known changes in process parameters), have been explored. This paper provides a comparison of four model-based machining force controllers; namely, linearization, log transform, nonlinear, and robust. These controllers are compared to an adaptive machining force controller in terms of transient performance and stability robustness with respect to parameter variations, and in terms of stability robustness with respect to unmodeled dynamics via simulation and experimental studies. The developed stability analyzes for the model-based controllers provide excellent predictions of the stability boundaries in the parameter space. Thus, stability robustness in terms of both model parameter variation and controller parameter adjustments can be systematically explored. Also, the results demonstrate that the stability robustness of the model-based controllers is insensitive to unmodeled servomechanism dynamics. While each force control approach performed satisfactorily in a laboratory environment, it can be generally concluded that their implementation should be dictated by the economics of the production environment.