Intelligent Machining Systems

Machining is one of the most widespread manufacturing processes and plays a critical role in industries. As a matter of fact, machine tools are often called mother machines as they are used to produce other machines and production plants. The continuous development of innovative materials and the increasing competitiveness are two of the challenges that nowadays manufacturing industries have to cope with. The increasing attention to environmental issues and the rising costs of raw materials drive the development of machining systems able to continuously monitor the ongoing process, identify eventual arising problems and adopt appropriate countermeasures to resolve or prevent these issues, leading to an overall optimization of the process. This work presents the development of intelligent machining systems based on in-process monitoring which can be implemented on production machines in order to enhance their performances. Therefore, some cases of monitoring systems developed in different fields, and for different applications, are presented in order to demonstrate the functions which can be enabled by the adoption of these systems. Design and realization of an advanced experimental machining testbed is presented in order to give an example of a machine tool retrofit aimed to enable advanced monitoring and control solutions. Finally, the implementation of a data-driven simulation of the machining process is presented. The modelling and simulation phases are presented and discussed. So, the model is applied to data collected during an experimental campaign in order to tune it. The opportunities enabled by integrating monitoring systems with simulation are presented with preliminary studies on the development of two virtual sensors for the material conformance and cutting parameter estimation during machining processes

Software Architecture and Subclassing Technique for Semiconductor Manufacturing Machines

Abstract. This paper proposed software architecture for operating an automatic semiconductor manufacturing machine. Recent machines for semiconductor process are required for high level of automation which are composed of motion control, machine vision, data acquisition and networking. These functions are executed through industrial equipments that are generally installed in a computer. The equipments occupy a great part of system resource and generate a lot of computation, so the software structure should be designed for efficiency. The proposed architecture is consisted of four layers and virtual equipments(VEs). The VEs are made by subclassing the physical equipments(PEs) and the layers are coded into thread which updates the status of VEs. Subroutines in a program refer to the pointer of VEs, and direct access to physical equipment are prohibited. The number of access (NOA) to PEs in typical industrial application was simulated for the unlimited access structure and the presented structure. The result showed that the proposed structure was more efficient than typical ones and irrespective of subroutines. This architecture was also applied to design a machine operating software and performed automatic wafer dicing

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

Initialization Requirement in Developing of Mobile Learning 'Molearn' for Biology Students Using Inquiry-based learning

Inquiry-based learning is kind of learning activities that involves students’ entire capabilities in exploring and investigating particular objects or phenomenon using critical thinking skills. Recently, information technology tangibly contributes in any education aspects, including the existence of e-learning, a widely spreading learning model in the 21st century education. This study aims at initializing needs of developing mobile learning ‘Molearn’ based on inquiry-based method. By cooperating with Biology teacher community in senior high school, ‘Molearn’ provides IT-based medium in Biology learning process

Mechanical Engineering

The book substantially offers the latest progresses about the important topics of the "Mechanical Engineering" to readers. It includes twenty-eight excellent studies prepared using state-of-art methodologies by professional researchers from different countries. The sections in the book comprise of the following titles: power transmission system, manufacturing processes and system analysis, thermo-fluid systems, simulations and computer applications, and new approaches in mechanical engineering education and organization systems

Control of the interaction of a gantry robot end effector with the environment by the adaptive behaviour of its joint drive actuators

The thesis examines a way in which the performance of the robot electric actuators can be precisely and accurately force controlled where there is a need for maintaining a stable specified contact force with an external environment. It describes the advantages of the proposed research, which eliminates the need for any external sensors and solely depends on the precise torque control of electric motors. The aim of the research is thus the development of a software based control system and then a proposal for possible inclusion of this control philosophy in existing range of automated manufacturing techniques.The primary aim of the research is to introduce force controlled behaviour in the electric actuators when the robot interacts with the environment, by measuring and controlling the contact forces between them. A software control system is developed and implemented on a robot gantry manipulator to follow two dimensional contours without the explicit geometrical knowledge of those contours. The torque signatures from the electric actuators are monitored and maintained within a desired force band. The secondary aim is the optimal design of the software controller structure. Experiments are performed and the mathematical model is validated against conventional Proportional Integral Derivative (PID) control. Fuzzy control is introduced in the software architecture to incorporate a sophisticated control. Investigation is carried out with the combination of PID and Fuzzy logic which depend on the geometrical complexity of the external environment to achieve the expected results

Cal Poly Supermileage Electric Vehicle Drivetrain and Motor Control Design

The Cal Poly Supermileage Vehicle team is a multidisciplinary club that designs and builds high efficiency vehicles to compete internationally at Shell Eco-Marathon (SEM). Cal Poly Supermileage Club has been competing in the internal combustion engine (ICE) category of the competition since 2007. The club has decided it is time to expand their competition goals and enter their first battery electric prototype vehicle. To this end, a yearlong senior design project was presented to this team of engineers giving us the opportunity to design an electric powertrain with a custom motor controller. This system has been integrated into Ventus, the 2017 Supermileage competition car, bringing it back to life as E-Ventus for future competitions. The scope of this project includes sizing a motor, designing the drivetrain, programing the motor driver, building a custom motor controller, and finally mounting all these components into the chassis. The main considerations in this design are the energy efficiency measured in distance per power used (mi/kWh) and the whole system reliability. Driven train system reliability has been defined as the car starts the first time every time and can complete two competition runs of 6.3 miles each without mechanical or electrical failure. Drivetrain weight target was less than 25 pounds, and the finished system came in at 20 lbs 4 oz. Due to the design difficulties of the custom controller, three iterations were able to be produced by the end of this project, but there will need to be further iterations to complete the controller. Because of these difficulties our sponsor, Will Sirski, and club advisor, Dr. Mello, have agreed that providing the club with a working mechanical powertrain, powertrain data from the club chassis dynamometer using the programmed TI evaluation motor controller board, and providing board layout for the third iteration design for the custom controller satisfy their requirements for this project