Design of an electrochemical micromachining machine

Electrochemical micromachining (μECM) is a non-conventional machining process based on the phenomenon of electrolysis. μECM became an attractive area of research due to the fact that this process does not create any defective layer after machining and that there is a growing demand for better surface integrity on different micro applications including microfluidics systems, stress-free drilled holes in automotive and aerospace manufacturing with complex shapes, etc. This work presents the design of a next generation μECM machine for the automotive, aerospace, medical and metrology sectors. It has three axes of motion (X, Y, Z) and a spindle allowing the tool-electrode to rotate during machining. The linear slides for each axis use air bearings with linear DC brushless motors and 2-nm resolution encoders for ultra precise motion. The control system is based on the Power PMAC motion controller from Delta Tau. The electrolyte tank is located at the rear of the machine and allows the electrolyte to be changed quickly. This machine features two process control algorithms: fuzzy logic control and adaptive feed rate. A self-developed pulse generator has been mounted and interfaced with the machine and a wire ECM grinding device has been added. The pulse generator has the possibility to reverse the pulse polarity for on-line tool fabrication.The research reported in this paper is supported by the European Commission within the project “Minimizing Defects in Micro-Manufacturing Applications (MIDEMMA)” (FP7-2011-NMPICT- FoF-285614)

Contouring Accuracy Improvement Using an Adaptive Feedrate Planning Method for CNC Machine Tools

AbstractThe reduction of contour error plays an important role in achieving high accuracy machining. To reduce contour error, most of previous studies have focused on developing advanced control strategies. As an alternative strategy, contouring accuracy improvement using an adaptive feedrate planning method is proposed in this paper. First, a typical PID controller is adopted to build the contour error model, from which the feedrate can be scheduled in the contour error violated zones. Then, the relations between each constraint and the cutter tip feedrate are derived. After that, a linear programming model is applied to obtain the optimal feedrate profile on the sampling positions of the given tool path. Finally, illustrated examples are given to validate the feasibility and applicability of the proposed feedrate planning method. The comparison results show that the proposed method has a significant effect on improving contouring accuracy

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

Multi-objective optimisation for minimum quantity lubrication assisted milling process based on hybrid response surface methodology and multi-objective genetic algorithm

© 2019 by SAGE Publications Ltd.Parametric modelling and optimisation play an important role in choosing the best or optimal cutting conditions and parameters during machining to achieve the desirable results. However, analysis of optimisation of minimum quantity lubrication–assisted milling process has not been addressed in detail. Minimum quantity lubrication method is very effective for cost reduction and promotes green machining. Hence, this article focuses on minimum quantity lubrication–assisted milling machining parameters on AISI 1045 material surface roughness and power consumption. A novel low-cost power measurement system is developed to measure the power consumption. A predictive mathematical model is developed for surface roughness and power consumption. The effects of minimum quantity lubrication and machining parameters are examined to determine the optimum conditions with minimum surface roughness and minimum power consumption. Empirical models are developed to predict surface roughness and power of machine tool effectively and accurately using response surface methodology and multi-objective optimisation genetic algorithm. Comparison of results obtained from response surface methodology and multi-objective optimisation genetic algorithm depict that both measured and predicted values have a close agreement. This model could be helpful to select the best combination of end-milling machining parameters to save power consumption and time, consequently, increasing both productivity and profitability.Peer reviewedFinal Published versio

Agile robotic edge finishing system research

This paper describes a new project undertaken by Sandia National Laboratories to develop an agile, automated, high-precision edge finishing system. The project has a two-year duration and was initiated in October, 1994. This project involves re-designing and adding additional capabilities to an existing finishing workcell at Sandia; and developing intelligent methods for automating process definition and for controlling finishing processes. The resulting system will serve as a prototype for systems that will be deployed into highly flexible automated production lines. The production systems will be used to produce a wide variety of products with limited production quantities and quick turnaround requirements. The prototype system is designed to allow programming, process definition, fixture re-configuration, and process verification to be performed off-line for new products. CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) models of the part will be used to assist with the automated process development and process control tasks. To achieve Sandia`s performance goals, the system will be employ advanced path planning, burr prediction expert systems, automated process definition, statistical process models in a process database, and a two-level control scheme using hybrid position-force control and fuzzy logic control. In this paper, we discuss the progress and the planned system development under this project

A new versatile in-process monitoring system for milling

International audienceTool condition monitoring (TCM) systems can improve productivity and ensure workpiece quality, yet, there is a lack of reliable TCM solutions for small-batch or one-off manufacturing of industrial parts. TCM methods which include the characteristics of the cut seem to be particularly suitable for these demanding applications. In the first section of this paper, three process-based indicators have been retrieved from literature dealing with TCM. They are analysed using a cutting force model and experiments are carried out in industrial conditions. Specific transient cuttings encountered during the machining of the test part reveal the indicators to be unreliable. Consequently, in the second section, a versatile in-process monitoring method is suggested. Based on experiments carried out under a range of different cutting conditions, an adequate indicator is proposed: the relative radial eccentricity of the cutters is estimated at each instant and characterizes the tool state. It is then compared with the previous tool state in order to detect cutter breakage or chipping. Lastly, the new approach is shown to be reliable when implemented during the machining of the test part

Intelligent monitoring and control system for a friction stir welding process

A Friction Stir Welding machine is proposed and built to allow future research into the process and to provide a framework from which the application of intelligent manufacturing to industrial processes can be investigated. Initially a literature survey was conducted upon which the design of the machine could be based. The conversion of a conventional milling machine into a Friction Stir Welding machine by applying modern monitoring and control systems is then presented. Complete digital control was used to drive actuators and monitor sensors. A wireless chuck mounted monitoring system was implemented, enabling forces, torques, temperature and speed of the tool to be obtained directly from the process. Software based on a hierarchical Open Systems Architectural design, incorporating modularity, interoperability, portability and extensibility is implemented. This experimental setup is used to analyze the Friction Stir Welding process by performing data analysis using statistical methods. Three independent variables (weld speed, spindle speed and plunge depth) were varied and the independent variables (forces, torques, power, temperature, speed, etc) recorded using the implemented software. The statistical analysis includes the analysis of variants, regression analysis and the creation of surface plots. Using these results, certain linguistic rules for process control are proposed. An intelligent controller is designed and discussed, using the derived rules to improve and optimize certain aspects of the process encountered during the experimental phase of the research

New Orleans, Louisiana Paper Number: IMECE2002-MED-PPO-03 ADAPTIVE FEEDRATE SCHEDULING AND MATERIAL ENGAGEMENT ANALYSIS FOR HIGH PERFORMANCE MACHINING

ABSTRACT This paper presents a technique of feedrate scheduling by analyzing the material removal volume when a tool moves in linear, circular, or parametric curved motions. Tool motions of different types of endmilling cutters are considered in this study. By studying the relationship between the cutter geometry and the tool motion, the material removal rates of different cutters are analyzed. The adaptive feedrate scheduling can be determined to maintain a constant cutting load. The technique developed in this research can be used for tool path generation in CAD/CAM systems for 2.5D NC machining