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  • 1
    Electronic Resource
    Electronic Resource
    A Rough-Set-Based Approach for Classification and Rule Induction (1999)
    Springer
    The international journal of advanced manufacturing technology 15 (1999), S. 438-444 
    Details
    ISSN: 1433-3015
    Keywords: Key words.Artificial intelligence; Automatic classification; Machine learning; Rough sets; Rule induction
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: The inconsistency of information about objects may be the greatest obstacle to performing inductive learning from examples. Rough sets theory provides a new mathematical tool to deal with uncertainty and vagueness. Based on rough sets theory, this paper proposes a novel approach for the classification and rule induction of inconsistent information systems. It is achieved by integrating rough sets theory with a statistics-based inductive learning algorithm. The framework of a proto-type rough-set-based classification system (RClass) is presented. Two examples are used to verify the prototype system. The results of the validation are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001700050088
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Optimising an Assembly Line Through Simulation Augmented by Genetic Algorithms (2000)
    Springer
    The international journal of advanced manufacturing technology 16 (2000), S. 220-228 
    Details
    ISSN: 1433-3015
    Keywords: Key words: Crossover; Mutation; Genetic algorithm; Elite chromosomes
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: In the paper, the influence of the size of the population, the crossover probability, the mutation probability and the number of elite chromosomes on the performance of the genetic algorithm are discussed. The results of the analysis of line through-put revealed that the line is well-balanced, and that some machines can work at a slower rate without compromising the maximum expected throughput. In addition, it was found that machine speed is not a determinant of optimum throughput. It was established that machine utilisation can be improved by another 4.3%, indicating that the machines were already well used. On the other hand, tardiness was improved by 23% by slowing down the arrival of the compressor blocks.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001700050031
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  • 3
    Electronic Resource
    Electronic Resource
    A Genetic Algorithms Enhanced Planning System for Surface Mount PCB Assembly (2000)
    Springer
    The international journal of advanced manufacturing technology 16 (2000), S. 289-296 
    Details
    ISSN: 1433-3015
    Keywords: Key words.Genetic algorithms; Multi-objective optimisation; PCB assembly planning; Surface mount technology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001700050159
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  • 4
    Electronic Resource
    Electronic Resource
    PCB assembly planning using genetic algorithms (1998)
    Springer
    The international journal of advanced manufacturing technology 14 (1998), S. 363-368 
    Details
    ISSN: 1433-3015
    Keywords: Genetic algorithms ; Optimisation ; PCB assembly planning
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Printed circuit boards (PCB) are used extensively in industry for the manufacture of electronic and electromechanical products. One of the primary concerns in the manufacture of PCBs is the determination of the optimal assembly plan. This paper presents work that leads to the development of an approach to PCB assembly planning using genetic algorithms (GAs). The approach takes into consideration component insertion priority and sequencing decision rules. A polygamy reproduction mechanism with dual mutation has been proposed and implemented. Details of the approach are described. A PCB model extracted from the literature was used for performance evaluation. Details of the evaluation are presented.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01178916
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  • 5
    Electronic Resource
    Electronic Resource
    A Prototype Genetic Algorithm-Enhanced Multi-Objective Scheduler for Manufacturing Systems (2000)
    Springer
    The international journal of advanced manufacturing technology 16 (2000), S. 131-138 
    Details
    ISSN: 1433-3015
    Keywords: Key words: Dynamic scheduling; Genetic algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: This paper describes the development of a prototype genetic algorithm-enhanced multi-objective scheduler for manufacturing systems. A framework of the prototype scheduler is proposed which accepts data input from a database or file and outputs a near-optimal schedule. A scheduling toolbox with scheduling models for job shop, flow shop and cellular manufacturing, forms part of the prototype scheduler, and the schedule builder transforms the near-optimal solution into a valid shop floor schedule. The prototype system was validated for various cases, with and without constraints and multiple objective functions, (makespan and tardiness), enforced simultaneously with constraints. In the first case, the schedule generated was comparable to those obtained by other researchers. The prototype system was also tested for its ability to handle dynamic scheduling, e.g. a rush order. The results showed that all the job orders could be rescheduled within the original makespan, even though the order of one of the jobs was doubled.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001700050018
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  • 6
    Electronic Resource
    Electronic Resource
    Adapting IDEF0 modelling to perform manufacturing diagnosis (1998)
    Springer
    The international journal of advanced manufacturing technology 14 (1998), S. 928-934 
    Details
    ISSN: 1433-3015
    Keywords: Fuzzy directed graph ; IDEF0 modelling ; Possibility theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract This paper presents the work done to adapt a system modelling methodology, ICAM DEFinition Zero (IDEF0), to perform manufacturing diagnosis. It describes the basic notions of IDEF0 modelling and the underlying principle of a novel reasoning technique, the “worst-first” search, developed for manufacturing diagnosis. The reasoning technique which was originally based on graph theory and possibility theory, has been adapted to access the information stored in an IDEF0 model. Details of a prototype IDEF0-based system for manufacturing diagnosis are presented. The results of system validation based on a manufacturing system for the production of mechanical components are reported.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01179083
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  • 7
    Electronic Resource
    Electronic Resource
    Tool condition monitoring using reflectance of chip surface and neural network (2000)
    Springer
    Journal of intelligent manufacturing 11 (2000), S. 507-514 
    Details
    ISSN: 1572-8145
    Keywords: Tool condition monitoring ; reflectance of chip surface ; neural network
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract A wide variety of tool condition monitoring techniques has been introduced in recent years. Among them, tool force monitoring, tool vibration monitoring and tool acoustics emission monitoring are the three most common indirect tool condition monitoring techniques. Using multiple intelligent sensors, these techniques are able to monitor tool condition with varying degrees of success. This paper presents a novel approach for the estimation of tool wear using the reflectance of cutting chip surface and a back propagation neural network. It postulates that the condition of a tool can be determined using the surface finish and color of a cutting chip. A series of experiments has been carried out. The experimental data obtained was used to train the back propagation neural network. Subsequently, the trained neural network was used to perform tool wear prediction. Results show that the prediction is in good agreement with the flank wear measured experimentally.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1026583821221
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  • 8
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    Integration of Response Surface Methodology with Genetic Algorithms (2001)
    Springer
    Details
    Publication Date: 2001-04-01
    Print ISSN: 0268-3768
    Electronic ISSN: 1433-3015
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Springer
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  • 9
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    Prediction of cutting forces along Pythagorean-hodograph curves (2008)
    Springer
    Details
    Publication Date: 2008-10-07
    Print ISSN: 0268-3768
    Electronic ISSN: 1433-3015
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Springer
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  • 10
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    PCB assembly planning using genetic algorithms (1998)
    Springer
    Details
    Publication Date: 1998-05-01
    Print ISSN: 0268-3768
    Electronic ISSN: 1433-3015
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Springer
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