Artificial cognitive architecture with self-learning and self-optimization capabilities. Case studies in micromachining processes

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de lectura : 22-09-201

Smart Monitoring of Manufacturing Systems for Automated Decision-Making: A Multi-Method Framework

Smart monitoring plays a principal role in the intelligent automation of manufacturing systems. Advanced data collection technologies, like sensors, have been widely used to facilitate real-time data collection. Computationally efficient analysis of the operating systems, however, remains relatively underdeveloped and requires more attention. Inspired by the capabilities of signal analysis and information visualization, this study proposes a multi-method framework for the smart monitoring of manufacturing systems and intelligent decision-making. The proposed framework uses the machine signals collected by noninvasive sensors for processing. For this purpose, the signals are filtered and classified to facilitate the realization of the operational status and performance measures to advise the appropriate course of managerial actions considering the detected anomalies. Numerical experiments based on real data are used to show the practicability of the developed monitoring framework. Results are supportive of the accuracy of the method. Applications of the developed approach are worthwhile research topics to research in other manufacturing environments

An integrated framework for developing generic modular reconfigurable platforms for micro manufacturing and its implementation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The continuing trends of miniaturisation, mass customisation, globalisation and wide use of the Internet have great impacts upon manufacturing in the 21st century. Micro manufacturing will play an increasingly important role in bridging the gap between the traditional precision manufacturing and the emerging technologies like MEMS/NEMS. The key requirements for micro manufacturing in this context are hybrid manufacturing capability, modularity, reconfigurability, adaptability and energy/resource efficiency. The existing design approaches tend to have narrow scope and are largely limited to individual manufacturing processes and applications. The above requirements demand a fundamentally new approach to the future applications of micro manufacturing so as to obtain producibility, predictability and productivity covering the full process chains and value chains. A novel generic modular reconfigurable platform (GMRP) is proposed in such a context. The proposed GMRP is able to offer hybrid manufacturing capabilities, modularity, reconfigurablity and adaptivity as both an individual machine tool and a micro manufacturing system, and provides a cost effective solution to high value micro manufacturing in an agile, responsive and mass customisation manner. An integrated framework has been developed to assist the design of GMRPs due to their complexity. The framework incorporates theoretical GMRP model, design support system and extension interfaces. The GMRP model covers various relevant micro manufacturing processes and machine tool elements. The design support system includes a user-friendly interface, a design engine for design process and design evaluation, together with scalable design knowledge base and database. The functionalities of the framework can also be extended through the design support system interface, the GMRP interface and the application interface, i.e. linking to external hardware and/or software modules. The design support system provides a number of tools for the analysis and evaluation of the design solutions. The kinematic simulation of machine tools can be performed using the Virtual Reality toolbox in Matlab. A module has also been developed for the multiscale modelling, simulation and results analysis in Matlab. A number of different cutting parameters can be studied and the machining performance can be subsequently evaluated using this module. The mathematical models for a non-traditional micro manufacturing process, micro EDM, have been developed with the simulation performed using FEA. Various design theories and methodologies have been studied, and the axiomatic design theory has been selected because of its great power and simplicity. It has been applied in the conceptual design of GMRP and its design support system. The implementation of the design support system is carried out using Matlab, Java and XML technologies. The proposed GMRP and framework have been evaluated through case studies and experimental results

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

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Factories of the Future

Engineering; Industrial engineering; Production engineerin

A smart micro factory design: an integrated approach

Smart factory research is paced up in the current decade due to the development of many enabling technologies and tools available to the developers. This has led to the progress of cyber physical systems in manufacturing, now coined as cyber physical production systems. The ultimate goal of this domain is to integrate underlying technologies and connect physical plants with the virtual factory in real time for improvement in product quality, process improvements, predictive maintenance, mass customization as well as mass production. The involved technology modules include sensor network, machine learning and AI, Internet of things, human machine interface, augmented reality and collaborative robotics. For the physical element in this research, a micro factory scenario is envisaged that consists of a high precision micro/nano positioning stage installed on a tabletop sized conventional machine tool, a collaborative robot for handling of micro parts and running of machine operations, other factory devices and a human worker for supervision tasks. Due to the multi-faceted technologies involved in both the virtual and physical systems, a simultaneous design strategy is followed in both domains. First, a flexure based micro positioning, 3-axis stage device is designed that can be installed on a conventional 3-axis desktop size milling machine. Secondly, a work zone is considered for effective human robot collaboration in the production area. The work zone considered as a social space is designed in a safe and secure way with the help of integrated devices, IoT and AI

A Framework for Life Cycle Cost Estimation of a Product Family at the Early Stage of Product Development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system

Factories of the Future

Engineering; Industrial engineering; Production engineerin