Adaptive Sliding Mode Contouring Control Design Based on Reference Adjustment and Uncertainty Compensation for Feed Drive Systems

Industrial feed drive systems, particularly, ball-screw and lead-screw feed drives are among the dominating motion components in production and manufacturing industries. They operate around the clock at high speeds for coping with the rising production demands. Adversely, high-speed motions cause mechanical vibrations, high-energy consumption, and insufficient accuracy. Although there are many control strategies in the literature, such as sliding mode and model predictive controls, further research is necessary for precision enhancement and energy saving. This study focused on design of an adaptive sliding mode contouring control based on reference adjustment and uncertainty compensation for feed drive systems. A combined reference adjustment and uncertainty compensator for precision motion of industrial feed drive systems were designed. For feasibility of the approach, simulation using matlab was conducted, and results are compared with those of an adaptive nonlinear sliding model contouring controller. The addition of uncertainty compensator showed a substantial improvement in performance by reducing the average contour error by 85.71% and the maximum contouring error by 78.64% under low speed compared to the adaptive sliding mode contouring controller with reference adjustment. Under high speed, the addition of uncertainty compensator reduced the average and absolute maximum contour errors by 4.48% and 10.13%, respectively. The experimental verification will be done in future. Keywords:    Machine tools, Feed drive systems, contouring control, Uncertainty dynamics, Sliding mode control

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017

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

Frontiers in Ultra-Precision Machining

Ultra-precision machining is a multi-disciplinary research area that is an important branch of manufacturing technology. It targets achieving ultra-precision form or surface roughness accuracy, forming the backbone and support of today’s innovative technology industries in aerospace, semiconductors, optics, telecommunications, energy, etc. The increasing demand for components with ultra-precision accuracy has stimulated the development of ultra-precision machining technology in recent decades. Accordingly, this Special Issue includes reviews and regular research papers on the frontiers of ultra-precision machining and will serve as a platform for the communication of the latest development and innovations of ultra-precision machining technologies

Proceedings of the 4th International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME2018)

The Mechatronics Department (Accredited by National Board of Accreditation, New Delhi, India) of the G H Patel College of Engineering and Technology, Gujarat, India arranged the 4th International Conference on Innovations in Automation and Mechatronics Engineering 2018, (ICIAME 2018) on 2-3 February 2018. The papers presented during the conference were based on Automation, Optimization, Computer Aided Design and Manufacturing, Nanotechnology, Solar Energy etc and are featured in this book

FINISH-MACHINING STRATEGIES FOR BLADED DISKS

Integrally Bladed Rotors (IBRs) or Bladed Disks (Blisks) are strategic components of compressor or turbine stages of aircraft engines. Development of manufacturing techniques and materials have aided the integration of two components, blades and the disk, which were originally manufactured separately and then assembled. A single component brings great benefits such as weight reduction, which is key the in aerospace sector. IBR components bring new challenges to the manufacturing industry due to the difficult to cut materials used, paired with complex geometries which limit the access of tooling and limits various efficient cutting strategies for the finish milling operations. Instead, a point milling strategy is commonly used to achieve drawing specifications but at a cost of machining time. Therefore, finish milling is by far the most time-consuming machining operation of IBR blades. However, many efforts from industry are directed to optimize machining times through roughing operations, which are faster to implement internally within the manufacturing engineering department, and often are not affected by fixed process approvals that are in place for the last few millimetres of material removal. This includes approval from the materials department on surface integrity modifications of the final surface, and complex approval processes with the final clients. An EngD project is an ideal scenario for the development of finish machining strategies for the reasons explained above. This thesis takes a real IBR case study as a starting point and navigates through a logical path for the development of its blade finish milling operation to provide a novel industrial optimization strategy. The research question evolves as each chapter explores different aspects of this challenging industrial problem. Initially, in chapter 2, surface integrity is explored within the typical working window (range or map of parameters selected for a given experiment), due to the relevancy of the surface integrity in the finished component. This is explored through an experimental approach which concludes surface integrity is not affected in the analysed range. Instead, chatter is identified and research efforts are then directed to improve finish machining of IBR blades through the understanding and mitigation of chatter. Chapter 3 seeks to analyse tool and component dynamics and includes a brief search into literature about process damping to understand how it might play a role in chatter mitigation. A new research line is then investigated to improve finish milling of IBR blades. A very simple concept of modifying finish milling stock is developed, using a scientific method based on Finite Element Analysis (FEA) and parametrizing the blade in order to maximize natural frequencies of interest. Once an optimized blade stock geometry has been obtained, a further literature review is carried out on chatter mitigation techniques. A knowledge gap is found in the current literature regarding time domain model for Sinusoidal Variable Spindle Speed (SVSS) model for ball end mill tools. This is observed as an opportunity to do a theoretical contribution to the predominantly experimental EngD thesis. A current time domain model has been further developed to incorporate SVSS and ball end mill geometry. Finally, implementation of variable speed in industrial environment has been researched. A further knowledge gap is identified in the implementation of variable speed in commercial milling machines, as most research up to date has been realized either theoretically or in laboratory conditions. In response to this need, a new method has been developed to be able to implement variable spindle speed and variable feed straight forwardly in a wide range of commercial milling machines. To end up with, a machine characterisation has been completed in order to identify the working window to apply the Variable Spindle Speed (VSS) method, and experimental trials have been carried out to demonstrate the capability of this approach. This thesis starts presenting a case study of IBRs with the need to improve current finish machining strategies and delivers new solutions from various perspectives, complementing each other and readily available to implement in the industry environment

Mission oriented R and D and the advancement of technology: The impact of NASA contributions, volume 2

NASA contributions to the advancement of major developments in twelve selected fields of technology are presented. The twelve fields of technology discussed are: (1) cryogenics, (2) electrochemical energy conversion and storage, (3) high-temperature ceramics, (4) high-temperature metals (5) integrated circuits, (6) internal gas dynamics (7) materials machining and forming, (8) materials joining, (9) microwave systems, (10) nondestructive testing, (11) simulation, and (12) telemetry. These field were selected on the basis of both NASA and nonaerospace interest and activity

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems