5,997 research outputs found

    A holistic integrated dynamic design and modelling approach applied to the development of ultraprecision micro-milling machines

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    Ultraprecision machines with small footprints or micro-machines are highly desirable for micro-manufacturing high-precision micro-mechanical components. However, the development of the machines is still at the nascent stage by working on an individual machine basis and hence lacks generic scientific approach and design guidelines. Using computer models to predict the dynamic performance of ultraprecision machine tools can help manufacturers substantially reduce the lead time and cost of developing new machines. Furthermore, the machine dynamic performance depends not only upon the mechanical structure and components but also the control system and electronic drives. This paper proposed a holistic integrated dynamic design and modelling approach, which supports analysis and optimization of the overall machine dynamic performance at the early design stage. Based on the proposed approach the modelling and simulation process on a novel 5-axis bench-top ultraprecision micro-milling machine tool – UltraMill – is presented. The modelling and simulation cover the dynamics of the machine structure, moving components, control system and the machining process, and are used to predict the overall machine performance of two typical configurations. Preliminary machining trials have been carried out and provided the evidence of the approach being helpful to assure the machine performing right at the first setup

    Design of a five-axis ultra-precision micro-milling machine—UltraMill. Part 2: Integrated dynamic modelling, design optimisation and analysis

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    Using computer models to predict the dynamic performance of ultra-precision machine tools can help manufacturers to substantially reduce the lead time and cost of developing new machines. However, the use of electronic drives on such machines is becoming widespread, the machine dynamic performance depending not only on the mechanical structure and components but also on the control system and electronic drives. Bench-top ultra-precision machine tools are highly desirable for the micro-manufacturing of high-accuracy micro-mechanical components. However, the development is still at the nascent stage and hence lacks standardised guidelines. Part 2 of this two-part paper proposes an integrated approach, which permits analysis and optimisation of the entire machine dynamic performance at the early design stage. Based on the proposed approach, the modelling and simulation process of a novel five-axis bench-top ultra-precision micro-milling machine tool—UltraMill—is presented. The modelling and simulation cover the dynamics of the machine structure, the moving components, the control system and the machining process and are used to predict the entire machine performance of two typical configurations

    Improving the Dynamic Performance of Five-Axis CNC Machine Tool by using the Software-in-the-Loop (SIL) Platform

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    The paper presents the development and implementation of a Software-in-the-loop (SIL) platform allowing the real-time simulation of the hybrid model of five-axis CNC machine tool which is implemented in SIMULINK. The interfacing between dSPACE software and the feed drives models in SIMULINK is explined. The values for the simulated positioning errors between the position demand and simulated position of orthogonal trimming head for the gantry axis are in the order of microns so proposed SIL model is validated. The accurate SIL platform could be used to build and optimise the machining process models including CNC machine tools under cutting conditions and improve machines’ dynamic performance

    Design of ultraprecision machine tools with application to manufacturing of miniature and micro components

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    Currently the underlying necessities for predictability, producibility and productivity remain big issues in ultraprecision machining of miniature/microproducts. The demand on rapid and economic fabrication of miniature/microproducts with complex shapes has also made new challenges for ultraprecision machine tool design. In this paper the design for an ultraprecision machine tool is introduced by describing its key machine elements and machine tool design procedures. The focus is on the review and assessment of the state-of-the-art ultraprecision machining tools. It also illustrates the application promise of miniature/microproducts. The trends on machine tool development, tooling, workpiece material and machining processes are pointed out

    Simulation study for investment decisions on the EcoBoost camshaft machining line

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    Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company’s Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area. Keywords: simulation modelling, closed-loop network, automotive production system

    Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

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    Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

    Design, control and error analysis of a fast tool positioning system for ultra-precision machining of freeform surfaces

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    This thesis was previously held under moratorium from 03/12/19 to 03/12/21Freeform surfaces are widely found in advanced imaging and illumination systems, orthopaedic implants, high-power beam shaping applications, and other high-end scientific instruments. They give the designers greater ability to cope with the performance limitations commonly encountered in simple-shape designs. However, the stringent requirements for surface roughness and form accuracy of freeform components pose significant challenges for current machining techniques—especially in the optical and display market where large surfaces with tens of thousands of micro features are to be machined. Such highly wavy surfaces require the machine tool cutter to move rapidly while keeping following errors small. Manufacturing efficiency has been a bottleneck in these applications. The rapidly changing cutting forces and inertial forces also contribute a great deal to the machining errors. The difficulty in maintaining good surface quality under conditions of high operational frequency suggests the need for an error analysis approach that can predict the dynamic errors. The machining requirements also impose great challenges on machine tool design and the control process. There has been a knowledge gap on how the mechanical structural design affects the achievable positioning stability. The goal of this study was to develop a tool positioning system capable of delivering fast motion with the required positioning accuracy and stiffness for ultra-precision freeform manufacturing. This goal is achieved through deterministic structural design, detailed error analysis, and novel control algorithms. Firstly, a novel stiff-support design was proposed to eliminate the structural and bearing compliances in the structural loop. To implement the concept, a fast positioning device was developed based on a new-type flat voice coil motor. Flexure bearing, magnet track, and motor coil parameters were designed and calculated in detail. A high-performance digital controller and a power amplifier were also built to meet the servo rate requirement of the closed-loop system. A thorough understanding was established of how signals propagated within the control system, which is fundamentally important in determining the loop performance of high-speed control. A systematic error analysis approach based on a detailed model of the system was proposed and verified for the first time that could reveal how disturbances contribute to the tool positioning errors. Each source of disturbance was treated as a stochastic process, and these disturbances were synthesised in the frequency domain. The differences between following error and real positioning error were discussed and clarified. The predicted spectrum of following errors agreed with the measured spectrum across the frequency range. It is found that the following errors read from the control software underestimated the real positioning errors at low frequencies and overestimated them at high frequencies. The error analysis approach thus successfully revealed the real tool positioning errors that are mingled with sensor noise. Approaches to suppress disturbances were discussed from the perspectives of both system design and control. A deterministic controller design approach was developed to preclude the uncertainty associated with controller tuning, resulting in a control law that can minimize positioning errors. The influences of mechanical parameters such as mass, damping, and stiffness were investigated within the closed-loop framework. Under a given disturbance condition, the optimal bearing stiffness and optimal damping coefficients were found. Experimental positioning tests showed that a larger moving mass helped to combat all disturbances but sensor noise. Because of power limits, the inertia of the fast tool positioning system could not be high. A control algorithm with an additional acceleration-feedback loop was then studied to enhance the dynamic stiffness of the cutting system without any need for large inertia. An analytical model of the dynamic stiffness of the system with acceleration feedback was established. The dynamic stiffness was tested by frequency response tests as well as by intermittent diamond-turning experiments. The following errors and the form errors of the machined surfaces were compared with the estimates provided by the model. It is found that the dynamic stiffness within the acceleration sensor bandwidth was proportionally improved. The additional acceleration sensor brought a new error source into the loop, and its contribution of errors increased with a larger acceleration gain. At a certain point, the error caused by the increased acceleration gain surpassed other disturbances and started to dominate, representing the practical upper limit of the acceleration gain. Finally, the developed positioning system was used to cut some typical freeform surfaces. A surface roughness of 1.2 nm (Ra) was achieved on a NiP alloy substrate in flat cutting experiments. Freeform surfaces—including beam integrator surface, sinusoidal surface, and arbitrary freeform surface—were successfully machined with optical-grade quality. Ideas for future improvements were proposed in the end of this thesis.Freeform surfaces are widely found in advanced imaging and illumination systems, orthopaedic implants, high-power beam shaping applications, and other high-end scientific instruments. They give the designers greater ability to cope with the performance limitations commonly encountered in simple-shape designs. However, the stringent requirements for surface roughness and form accuracy of freeform components pose significant challenges for current machining techniques—especially in the optical and display market where large surfaces with tens of thousands of micro features are to be machined. Such highly wavy surfaces require the machine tool cutter to move rapidly while keeping following errors small. Manufacturing efficiency has been a bottleneck in these applications. The rapidly changing cutting forces and inertial forces also contribute a great deal to the machining errors. The difficulty in maintaining good surface quality under conditions of high operational frequency suggests the need for an error analysis approach that can predict the dynamic errors. The machining requirements also impose great challenges on machine tool design and the control process. There has been a knowledge gap on how the mechanical structural design affects the achievable positioning stability. The goal of this study was to develop a tool positioning system capable of delivering fast motion with the required positioning accuracy and stiffness for ultra-precision freeform manufacturing. This goal is achieved through deterministic structural design, detailed error analysis, and novel control algorithms. Firstly, a novel stiff-support design was proposed to eliminate the structural and bearing compliances in the structural loop. To implement the concept, a fast positioning device was developed based on a new-type flat voice coil motor. Flexure bearing, magnet track, and motor coil parameters were designed and calculated in detail. A high-performance digital controller and a power amplifier were also built to meet the servo rate requirement of the closed-loop system. A thorough understanding was established of how signals propagated within the control system, which is fundamentally important in determining the loop performance of high-speed control. A systematic error analysis approach based on a detailed model of the system was proposed and verified for the first time that could reveal how disturbances contribute to the tool positioning errors. Each source of disturbance was treated as a stochastic process, and these disturbances were synthesised in the frequency domain. The differences between following error and real positioning error were discussed and clarified. The predicted spectrum of following errors agreed with the measured spectrum across the frequency range. It is found that the following errors read from the control software underestimated the real positioning errors at low frequencies and overestimated them at high frequencies. The error analysis approach thus successfully revealed the real tool positioning errors that are mingled with sensor noise. Approaches to suppress disturbances were discussed from the perspectives of both system design and control. A deterministic controller design approach was developed to preclude the uncertainty associated with controller tuning, resulting in a control law that can minimize positioning errors. The influences of mechanical parameters such as mass, damping, and stiffness were investigated within the closed-loop framework. Under a given disturbance condition, the optimal bearing stiffness and optimal damping coefficients were found. Experimental positioning tests showed that a larger moving mass helped to combat all disturbances but sensor noise. Because of power limits, the inertia of the fast tool positioning system could not be high. A control algorithm with an additional acceleration-feedback loop was then studied to enhance the dynamic stiffness of the cutting system without any need for large inertia. An analytical model of the dynamic stiffness of the system with acceleration feedback was established. The dynamic stiffness was tested by frequency response tests as well as by intermittent diamond-turning experiments. The following errors and the form errors of the machined surfaces were compared with the estimates provided by the model. It is found that the dynamic stiffness within the acceleration sensor bandwidth was proportionally improved. The additional acceleration sensor brought a new error source into the loop, and its contribution of errors increased with a larger acceleration gain. At a certain point, the error caused by the increased acceleration gain surpassed other disturbances and started to dominate, representing the practical upper limit of the acceleration gain. Finally, the developed positioning system was used to cut some typical freeform surfaces. A surface roughness of 1.2 nm (Ra) was achieved on a NiP alloy substrate in flat cutting experiments. Freeform surfaces—including beam integrator surface, sinusoidal surface, and arbitrary freeform surface—were successfully machined with optical-grade quality. Ideas for future improvements were proposed in the end of this thesis

    Study and Development of Mechatronic Devices and Machine Learning Schemes for Industrial Applications

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    Obiettivo del presente progetto di dottorato è lo studio e sviluppo di sistemi meccatronici e di modelli machine learning per macchine operatrici e celle robotizzate al fine di incrementarne le prestazioni operative e gestionali. Le pressanti esigenze del mercato hanno imposto lavorazioni con livelli di accuratezza sempre più elevati, tempi di risposta e di produzione ridotti e a costi contenuti. In questo contesto nasce il progetto di dottorato, focalizzato su applicazioni di lavorazioni meccaniche (e.g. fresatura), che includono sistemi complessi quali, ad esempio, macchine a 5 assi e, tipicamente, robot industriali, il cui utilizzo varia a seconda dell’impiego. Oltre alle specifiche problematiche delle lavorazioni, si deve anche considerare l’interazione macchina-robot per permettere un’efficiente capacità e gestione dell’intero impianto. La complessità di questo scenario può evidenziare sia specifiche problematiche inerenti alle lavorazioni (e.g. vibrazioni) sia inefficienze più generali che riguardano l’impianto produttivo (e.g. asservimento delle macchine con robot, consumo energetico). Vista la vastità della tematica, il progetto si è suddiviso in due parti, lo studio e sviluppo di due specifici dispositivi meccatronici, basati sull’impiego di attuatori piezoelettrici, che puntano principalmente alla compensazione di vibrazioni indotte dal processo di lavorazione, e l’integrazione di robot per l’asservimento di macchine utensili in celle robotizzate, impiegando modelli di machine learning per definire le traiettorie ed i punti di raggiungibilità del robot, al fine di migliorarne l’accuratezza del posizionamento del pezzo in diverse condizioni. In conclusione, la presente tesi vuole proporre soluzioni meccatroniche e di machine learning per incrementare le prestazioni di macchine e sistemi robotizzati convenzionali. I sistemi studiati possono essere integrati in celle robotizzate, focalizzandosi sia su problematiche specifiche delle lavorazioni in macchine operatrici sia su problematiche a livello di impianto robot-macchina. Le ricerche hanno riguardato un’approfondita valutazione dello stato dell’arte, la definizione dei modelli teorici, la progettazione funzionale e l’identificazione delle criticità del design dei prototipi, la realizzazione delle simulazioni e delle prove sperimentali e l’analisi dei risultati.The aim of this Ph.D. project is the study and development of mechatronic systems and machine learning models for machine tools and robotic applications to improve their performances. The industrial demands have imposed an ever-increasing accuracy and efficiency requirement whilst constraining the cost. In this context, this project focuses on machining processes (e.g. milling) that include complex systems such as 5-axes machine tool and industrial robots, employed for various applications. Beside the issues related to the machining process itself, the interaction between the machining centre and the robot must be considered for the complete industrial plant’s improvement. This scenario´s complexity depicts both specific machining problematics (e.g. vibrations) and more general issues related to the complete plant, such as machine tending with an industrial robot and energy consumption. Regarding the immensity of this area, this project is divided in two parts, the study and development of two mechatronic devices, based on piezoelectric stack actuators, for the active vibration control during the machining process, and the robot machine tending within the robotic cell, employing machine learning schemes for the trajectory definition and robot reachability to improve the corresponding positioning accuracy. In conclusion, this thesis aims to provide a set of solutions, based on mechatronic devices and machine learning schemes, to improve the conventional machining centre and the robotic systems performances. The studied systems can be integrated within a robotic cell, focusing on issues related to the specific machining process and to the interaction between robot-machining centre. This research required a thorough study of the state-of-the-art, the formulation of theoretical models, the functional design development, the identification of the critical aspects in the prototype designs, the simulation and experimental campaigns, and the analysis of the obtained results

    A CAD/CAM concept for High Speed Cutting compatible rough machining in die, mould and pattern manufacturing

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    Die, mould and pattern manufacturing plays a central role in the production of capital and consumer goods. Ever-shorter product life cycles and the expanding diversity of features require continued cuts in production lead times. Recently, these developments in the market, accompanied by a simultaneous demand for improved quality at a lower cost, are becoming clearly noticeable. Along with the streamlining of organizational structures and advanced technological developments, it is above all the introduction of CAD/CAM software that offers great potential for reducing lead times for components with free surfaces. The role of milling in the integrated process chain of die, mould and pattern manufacturing is steadily gaining importance. This is due to the ongoing further development of milling-machine technology, the cutting tools and their coatings, and of the CAD /CAM systems themselves. Generally speaking, the milling process is divided into the operations of roughing and finishing. For rough milling, efficient machining means high stock-removal rates together with close contour approximation and low tool wear. Rough milling is normally carried out layer by layer, i.e. in a 2.SD machining operation with constant depth per cut because the rate of material removal and process reliability are usually highest when this method is used. High-speed cutting (HSC), which has been the subject of extensive university research for far more than ten years, has meanwhile become established as a finishing process in many companies. However, the application of HSC demands the observance of geometric and, above all, technological constraints. A considerable degree of optimization can be achieved when these constraints are applied to rough milling. In the integrated process chain, the CAD/CAM system performs the task of calculating NC programs based on CAD data which meet the requirements posed by rough and finish machining operations. While general interest was focused on the development of CAM strategies for HSC finish machining, advanced development of technology-oriented CAM modules for upstream roughing operations was neglected. The paper at hand deals with the development of a CAM module for rough-machining complex components in die, mould and pattern manufacturing. It provides an insight into the process-technological demands made on HSC operations and their application in rough machining, from which guidelines and requirements on technologically oriented NC functions for CAM software were derived. These encompass both the complete development of an interactive, dialogue-based user guidance function and the algorithmic conversion of the calculation routines. The concept at hand was almost entirely implemented and integrated in the CAD/CAM system developed by Tebis AG, Germany, which was conceived especially for die, mould and pattern manufacturing and is scheduled for introduction to the free market starting in April 2001
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