Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Fabricate 2014

FABRICATE is an international peer reviewed conference that takes place every three years with a supporting publication on the theme of Digital Fabrication. Discussing the progressive integration of digital design with manufacturing processes, and its impact on design and making in the 21st century, FABRICATE brings together pioneers in design and making within architecture, construction, engineering, manufacturing, materials technology and computation. Discussion on key themes includes: how digital fabrication technologies are enabling new creative and construction opportunities from component to building scales, the difficult gap that exists between digital modelling and its realisation, material performance and manipulation, off-site and on-site construction, interdisciplinary education, economic and sustainable contexts. FABRICATE features cutting-edge built work from both academia and practice, making it a unique event that attracts delegates from all over the worl

A Short Review on 4D Printing

Additive Manufacturing can be described as a process to build 3D objects by adding layer-upon-layer of material, the material traditionally being plastics, metals or ceramics, however ‘smart’ materials are now in use. Nowadays, the term “3D Printing” has become a much-used synonym for additive manufacturing. The use of computing, 3D solid modeling applications, layering materials and machine equipment is common to majority of additive manufacturing technologies. Advancing from this 3D printing technology, is an emerging trend for what is being termed “4D printing”. 4D printing places dependency on smart materials, the functionality of additive manufacturing machines and in ingenious design processes. Although many developments have been made, limitations are still very much in existence, particularly with regards to function and application. The objective of this short review is to discuss the developments, challenges and outlook for 4D printing technology. The review revealed that 4D printing technology has application potential but further research work will be vital for the future success of 4D printing

Cold Micro Metal Forming

This open access book contains the research report of the Collaborative Research Center “Micro Cold Forming” (SFB 747) of the University of Bremen, Germany. The topical research focus lies on new methods and processes for a mastered mass production of micro parts which are smaller than 1mm (by forming in batch size higher than one million). The target audience primarily comprises research experts and practitioners in production engineering, but the book may also be of interest to graduate students alike

Prediction of Robot Execution Failures Using Neural Networks

In recent years, the industrial robotic systems are designed with abilities to adapt and to learn in a structured or unstructured environment. They are able to predict and to react to the undesirable and uncontrollable disturbances which frequently interfere in mission accomplishment. In order to prevent system failure and/or unwanted robot behaviour, various techniques have been addressed. In this study, a novel approach based on the neural networks (NNs) is employed for prediction of robot execution failures. The training and testing dataset used in the experiment consists of forces and torques memorized immediately after the real robot failed in assignment execution. Two types of networks are utilized in order to find best prediction method - recurrent NNs and feedforward NNs. Moreover, we investigated 24 neural architectures implemented in Matlab software package. The experimental results confirm that this approach can be successfully applied to the failures prediction problem, and that the NNs outperform other artificial intelligence techniques in this domain. To further validate a novel method, real world experiments are conducted on a Khepera II mobile robot in an indoor structured environment. The obtained results for trajectory tracking problem proved usefulness and the applicability of the proposed solution

Neural Extended Kalman Filter for State Estimation of Automated Guided Vehicle in Manufacturing Environment

To navigate autonomously in a manufacturing environment Automated Guided Vehicle (AGV) needs the ability to infer its pose. This paper presents the implementation of the Extended Kalman Filter (EKF) coupled with a feedforward neural network for the Visual Simultaneous Localization and Mapping (VSLAM). The neural extended Kalman filter (NEKF) is applied on-line to model error between real and estimated robot motion. Implementation of the NEKF is achieved by using mobile robot, an experimental environment and a simple camera. By introducing neural network into the EKF estimation procedure, the quality of performance can be improved

Proceedings of the 9th fib International PhD Symposium in Civil Engineering : Karlsruhe Institute of Technology (KIT), 22 - 25 July 2012, Karlsruhe, Germany

The fib International PhD Symposium in Civil Engineering is an established event in the academic calendar of doctoral students. It is held under the patronage of the International Federation for Structural Concrete (fib), one of the main international associations that disseminates knowledge about concrete and concrete structures. The 9th fib International PhD Symposium was held at the Karlsruhe Institute of Technology (KIT), Germany, from July 22 to 25, 2012