5 research outputs found
Assembly Line
An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line
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Object-oriented analysis and design of computational intelligence systems
Machine learning from data, neuro-fuzzy information processing, approximate reasoning and genetic and evolutionary computation are all aspects of computational intelligence (also called soft computing methods). Soft computing methods differ from conventional computing in that they are tolerant of imprecision, uncertainty and partial truths. These characteristics can be exploited to achieve tractability, robustness and low solution costs when the solution to a complex (in machine terms) problem is required. The principal constituents of soft computing include: Neural Networks, Fuzzy Logic and Probabilistic Reasoning Systems. Genetic Algorithms (GAs), Evolutionary Algorithms, Chaos Theory', Complexity Theory and parts of Learning Theory all come under Probabilistic Reasoning Systems. Hybrid systems can be designed incorporating 2 or more aspects of soft computing that are more powerful than any of the components used in a stand alone fashion. A unified framework is needed to implement and manipulate such systems. Such a framework will allow for easy visualisation of the underlying concepts and easy modification of the resulting computer models. In this thesis, an investigation of the major aspects of computational intelligence has been carried out. The main emphasis has been placed on developing an object-oriented framework for architecting computational intelligence systems. Object models for Neural Networks, Fuzzy Logic Systems and Evolutionary Computation systems have been developed. Software has been written in C++ to realise sample implementations of the various systems. Finally, practical applications and the results of using the Neural Networks, Fuzzy Logic systems and Genetic Algorithms developed in solving real world problems are presented. A consistent notation based on the Object Modelling Technique (OMT) is used throughout the thesis to describe the software architectures from which the computer implementation models have been derived