Design methodology for smart actuator services for machine tool and machining control and monitoring

This paper presents a methodology to design the services of smart actuators for machine tools. The smart actuators aim at replacing the traditional drives (spindles and feed-drives) and enable to add data processing abilities to implement monitoring and control tasks. Their data processing abilities are also exploited in order to create a new decision level at the machine level. The aim of this decision level is to react to disturbances that the monitoring tasks detect. The cooperation between the computational objects (the smart spindle, the smart feed-drives and the CNC unit) enables to carry out functions for accommodating or adapting to the disturbances. This leads to the extension of the notion of smart actuator with the notion of agent. In order to implement the services of the smart drives, a general design is presented describing the services as well as the behavior of the smart drive according to the object oriented approach. Requirements about the CNC unit are detailed. Eventually, an implementation of the smart drive services that involves a virtual lathe and a virtual turning operation is described. This description is part of the design methodology. Experimental results obtained thanks to the virtual machine are then presented

Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities

Development of the UMAC-based control system with application to 5-axis ultraprecision micromilling machines

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Increasing demands from end users in the fields of optics, defence, automotive, medical, aerospace, etc. for high precision 3D miniaturized components and microstructures from a range of materials have driven the development in micro and nano machining and changed the manufacturing realm. Conventional manufacturing processes such as chemical etching and LIGA are found unfavourable or limited due to production time required and have led mechanical micro machining to grow further. Mechanical micro machining is an ideal method to produce high accuracy micro components and micro milling is the most flexible enabling process and is thus able to generate a wider variety of complex micro components and microstructures. Ultraprecision micromilling machine tools are required so as to meet the accuracy, surface finish and geometrical complexity of components and parts. Typical manufacturing requirements are high dimensional accuracy being better than 1 micron, flatness and roundness better than 50 nm and surface finish ranging between 10 and 50 nm. Manufacture of high precision components and parts require very intricate material removal procedure. There are five key components that include machine tools, cutting tools, material properties, operation variables and environmental conditions, which constitute in manufacturing high quality components and parts. End users assess the performance of a machine tool based on the dimensional accuracy and surface quality of machined parts including the machining time. In this thesis, the emphasis is on the design and development of a control system for a 5-axis bench-type ultraprecision micromilling machine- Ultra-Mill. On the one hand, the developed control system is able to offer high motion and positioning accuracy, dynamic stiffness and thermal stability for motion control, which are essential for achieving the machining accuracy and surface finish desired. On the other hand, the control system is able to undertake in-process inspection and condition monitoring of the machine tool and process. The control of multi-axis precision machines with high-speed and high-accuracy motions and positioning are desirable to manufacture components with high accuracy and complex features to increase productivity and maintain machine stability, etc. The development of the control system has focused on fast, accurate and robust positioning requirements at the machine system design stage. Apart from the mechanical design, the performance of the entire precision systems is greatly dependent on diverse electrical and electronics subsystems, controllers, drive instruments, feedback devices, inspection and monitoring system and software. There are some variables that dynamically alter the system behaviour and sensitivity to disturbance that are not ignorable in the micro and nano machining realm. In this research, a structured framework has been developed and integrated to aid the design and development of the control system. The framework includes critically reviewing the state of the art of ultraprecision machining tools, understanding the control system technologies involved, highlighting the advantages and disadvantages of various control system methods for ultraprecision machines, understanding what is required by end-users and formulating what actually makes a machine tool be an ultraprecision machine particularly from the control system perspective. In the design and development stage, the possession of mechatronic know-how is essential as the design and development of the Ultra-Mill is a multidisciplinary field. Simulation and modelling tool such as Matlab/Simulink is used to model the most suitable control system design. The developed control system was validated through machining trials to observe the achievable accuracy, experiments and testing of subsystems individually (slide system, tooling system, monitoring system, etc.). This thesis has successfully demonstrated the design and development of the control system for a 5-axis ultraprecision machine tool- Ultra-Mill, with high performance characteristics, fast, accurate, precise, etc. for motion and positioning, high dynamic stiffness, robustness and thermal stability, whereby was provided and maintained by the control system

Modified Approach for Cutting Force Measurement in Face Milling Process

In modern manufacturing processes, there is an ever increasing demand for higher productivity. The continuous demand for higher productivity and product quality asks for better understanding and control of machining processes by reducing machining time with the increase of cutting force and material removal rate. The variation in cutting force results in deflection in the tool and workpiece and which intern deteriorates geometrical accuracy. One of the methods of improving productivity and quality lies in fact, to develop monitoring system which can control and maintain the cutting force at a prescribed level by adjusting cutting parameters using adaptive control technique. The cutting force is one of the important characteristic variables to be monitored in the cutting processes. This research paper consists of an indirect cutting force estimator during face milling process. Cutting forces and torque models are derived from cutting geometry in face milling process. The relationship between feed motor current and cutting forces has been developed from the proposed force models. Cutting forces are measured indirectly by sensing the currents of feed drive servomotors through the Fanuc SERVOGUIDE software. The instantaneous current data captured through the software is utilized for determining the instantaneous torque developed by the feed motor and instantaneous cutting forces have been estimated by using force and torque models. Practical issues calculating cutting force using motor current on a commercial machining center is also carried out. The experimental methodology involved estimation of torque consumption by the motor, first during idle movement and second during actual machining of the component. The machining of the components using standard cutting condition has been carried out and the cutting force estimated using the above method were validated by comparing the cutting force data derived from an accurate dynamometer for similar cutting condition. Practical experimental results are found to be in agreement with the estimated value to an accuracy of ± 10%. This proves indirect measurement is quite reasonable and economical and it has an important application value with high compatibility and stability

Development of the UMAC-based control system with application to 5-axis ultraprecision micromilling machines

Increasing demands from end users in the fields of optics, defence, automotive, medical, aerospace, etc. for high precision 3D miniaturized components and microstructures from a range of materials have driven the development in micro and nano machining and changed the manufacturing realm. Conventional manufacturing processes such as chemical etching and LIGA are found unfavourable or limited due to production time required and have led mechanical micro machining to grow further. Mechanical micro machining is an ideal method to produce high accuracy micro components and micro milling is the most flexible enabling process and is thus able to generate a wider variety of complex micro components and microstructures. Ultraprecision micromilling machine tools are required so as to meet the accuracy, surface finish and geometrical complexity of components and parts. Typical manufacturing requirements are high dimensional accuracy being better than 1 micron, flatness and roundness better than 50 nm and surface finish ranging between 10 and 50 nm. Manufacture of high precision components and parts require very intricate material removal procedure. There are five key components that include machine tools, cutting tools, material properties, operation variables and environmental conditions, which constitute in manufacturing high quality components and parts. End users assess the performance of a machine tool based on the dimensional accuracy and surface quality of machined parts including the machining time. In this thesis, the emphasis is on the design and development of a control system for a 5-axis bench-type ultraprecision micromilling machine- Ultra-Mill. On the one hand, the developed control system is able to offer high motion and positioning accuracy, dynamic stiffness and thermal stability for motion control, which are essential for achieving the machining accuracy and surface finish desired. On the other hand, the control system is able to undertake in-process inspection and condition monitoring of the machine tool and process. The control of multi-axis precision machines with high-speed and high-accuracy motions and positioning are desirable to manufacture components with high accuracy and complex features to increase productivity and maintain machine stability, etc. The development of the control system has focused on fast, accurate and robust positioning requirements at the machine system design stage. Apart from the mechanical design, the performance of the entire precision systems is greatly dependent on diverse electrical and electronics subsystems, controllers, drive instruments, feedback devices, inspection and monitoring system and software. There are some variables that dynamically alter the system behaviour and sensitivity to disturbance that are not ignorable in the micro and nano machining realm. In this research, a structured framework has been developed and integrated to aid the design and development of the control system. The framework includes critically reviewing the state of the art of ultraprecision machining tools, understanding the control system technologies involved, highlighting the advantages and disadvantages of various control system methods for ultraprecision machines, understanding what is required by end-users and formulating what actually makes a machine tool be an ultraprecision machine particularly from the control system perspective. In the design and development stage, the possession of mechatronic know-how is essential as the design and development of the Ultra-Mill is a multidisciplinary field. Simulation and modelling tool such as Matlab/Simulink is used to model the most suitable control system design. The developed control system was validated through machining trials to observe the achievable accuracy, experiments and testing of subsystems individually (slide system, tooling system, monitoring system, etc.). This thesis has successfully demonstrated the design and development of the control system for a 5-axis ultraprecision machine tool- Ultra-Mill, with high performance characteristics, fast, accurate, precise, etc. for motion and positioning, high dynamic stiffness, robustness and thermal stability, whereby was provided and maintained by the control system.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Multi-agent framework based on smart sensors/actuators for machine tools control and monitoring

Throughout the history, the evolutions of the requirements for manufacturing equipments have depended on the changes in the customers' demands. Among the present trends in the requirements for new manufacturing equipments, there are more flexible and more reactive machines. In order to satisfy those requirements, this paper proposes a control and monitoring framework for machine tools based on smart sensor, on smart actuator and on agent concepts. The proposed control and monitoring framework achieves machine monitoring, process monitoring and adapting functions that are not usually provided by machine tool control systems. The proposed control and monitoring framework has been evaluated by the means of a simulated operative part of a machine tool. The communication between the agents is achieved thanks to an Ethernet network and CORBA protocol. The experiments (with and without cooperation between agents for accommodating) give encouraging results for implementing the proposed control framework to operational machines. Also, the cooperation between the agents of control and monitoring framework contributes to the improvement of reactivity by adapting cutting parameters to the machine and process states and to increase productivity

Monitoring of Tool and Component Wear for Self-Adaptive Digital Twins: A Multi-Stage Approach through Anomaly Detection and Wear Cycle Analysis

In today’s manufacturing landscape, Digital Twins play a pivotal role in optimising processes and deriving actionable insights that extend beyond on-site calculations. These dynamic representations of systems demand real-time data on the actual state of machinery, rather than static images depicting idealized configurations. This paper presents a novel approach for monitoring tool and component wear in CNC milling machines by segmenting and classifying individual machining cycles. The method assumes recurring sequences, even with a batch size of 1, and considers a progressive increase in tool wear between cycles. The algorithms effectively segment and classify cycles based on path length, spindle speed and cycle duration. The tool condition index for each cycle is determined by considering all axis signals, with upper and lower thresholds established for quantifying tool conditions. The same approach is adapted to predict component wear progression in machine tools, ensuring robust condition determination. A percentage-based component state description is achieved by comparing it to the corresponding Tool Condition Codes (TCC) range. This method provides a four-class estimation of the component state. The approach has demonstrated robustness in various validation cases

Monitoring the misalignment of machine tools with autoencoders after they are trained with transfer learning data

CNC machines have revolutionized manufacturing by enabling high-quality and high-productivity production. Monitoring the condition of these machines during production would reduce maintenance cost and avoid manufacturing defective parts. Misalignment of the linear tables in CNCs can directly affect the quality of the manufactured parts, and the components of the linear tables wear out over time due to the heavy and fluctuating loads. To address these challenges, an intelligent monitoring system was developed to identify normal operation and misalignments. Since damaging a CNC machine for data collection is too expensive, transfer learning was used in two steps. First, a specially designed experimental feed axis test platform (FATP) was used to sample the current signal at normal and five levels of left-side misalignment conditions ranging from 0.05 to 0.25 mm. Four different algorithm combinations were trained to detect misalignments. These combinations included a 1D convolution neural network (CNN) and autoencoder (AE) combination, a temporal convolutional network (TCN) and AE combination, a long short-term memory neural network (LSTM) and AE combination, and a CNN, LSTM, and AE combination. At the second step, Wasserstein deep convolutional generative adversarial network (W-DCGAN) was used to generate data by integrating the observed characteristics of the FATP at different misalignment levels and collected limited data from the actual CNC machines. To evaluate the similarity and limited diversity of generated and real signals, t-distributed stochastic neighbor embedding (T-SNE) method was used. The hyperparameters of the model were optimized by random and grid search. The CNN, LSTM, and AE combination demonstrated the best performance, which provides a practical way to detect misalignments without stopping production or cluttering the work area with sensors. The proposed intelligent monitoring system can detect misalignments of the linear tables of CNCs, thus enhancing the quality of manufactured parts and reducing production costs

Model Referenced Condition Monitoring of High Performance CNC Machine Tools

Generally, machine tool monitoring is the prediction of the system’s health based on signal acquisition and processing and classification in order to identify the causes of the problem. The producers of machine tools need to pay more attention to their products life cycle because their customers increasingly focus on machine tool reliability and costs. The present study is concerned with the development of a condition monitoring system for high speed Computer Numerical Control (CNC) milling machine tools. A model is a simplification of a real machine to visualize the dynamics of a mechatronic system. This thesis applies recent modelling techniques to represent all parameters which affect the accuracy of a component produced automatically. The control can achieve an accuracy approaching the tolerance restrictions imposed by the machine tool axis repeatability and its operating environment. The motion control system of the CNC machine tool is described and the elements, which compose the axis drives including both the electrical components and the mechanical ones, are analysed and modelled. SIMULINK models have been developed to represent the majority of the dynamic behaviour of the feed drives from the actual CNC machine tool. Various values for the position controller and the load torque have been applied to the motor to show their behaviour. Development of a mechatronic hybrid model for five-axis CNC machine tool using Multi-Body-System (MBS) simulation approach is described. Analysis of CNC machine tool performance under non-cutting conditions is developed. ServoTrace data have been used to validate the Multi-body simulation of tool-to-workpiece position. This thesis aspects the application of state of art sensing methods in the field of condition monitoring of electromechanical systems. The ballscrew-with-nut is perhaps the most prevalent CNC machine subsystem and the condition of each element is crucial to the success of a machining operation. It’s essential to know of the health status of ballscrew, bearings and nut. Acoustic emission analysis of machines has been carried out to determine the deterioration of the ballscrew. Standard practices such as use of a Laser Interferometer have been used to determine the position of the machine tool. A novel machine feed drive condition monitoring system using acoustic emission (AE) signals has been proposed. The AE monitoring techniques investigated can be categorised into traditional AE parameters of energy, event duration and peak amplitude. These events are selected and normalised to estimate remaining life of the machine. This method is shown to be successfully applied for the ballscrew subsystem of an industrial high-speed milling machine. Finally, the successful outcome of the project will contribute to machine tool industry making possible manufacturing of more accurate products with lower costs in shorter time