Artificial Intelligence in Engineering最新文献

The development and maintenance of product configuration systems is faced with increasing challenges caused by the growing complexity of the underlying knowledge bases. Effective knowledge acquisition is needed since the product and the corresponding configuration system have to be developed in parallel. In this paper, we show how to employ a standard design language (Unified Modeling Language, UML) for modeling configuration knowledge bases. The two constituent parts of the configuration model are the component model and a set of corresponding functional architectures defining which requirements can be imposed on the product. The conceptual configuration model is automatically translated into an executable logic representation. Using this representation we show how to employ model-based diagnosis techniques for debugging faulty configuration knowledge bases, detecting infeasible requirements, and for reconfiguring old configurations.

During conceptual design, a designer may wish to describe a shape vaguely, either because it is desired that the shape remains flexible or the shape has not yet been defined precisely. Maintaining the vagueness of an early idea until it is sufficiently developed is often of vital importance. However, most existing systems, mainly due to limitations in their modelling capabilities, attempt to interpret and thereby remove the vagueness at the earliest opportunity. This may lead to the loss of considerable information in original concepts or design fixation too early in the design stage. A new approach is needed to represent and maintain vague geometric information and such an approach is presented in this paper.

In this paper we describe a structured method for developing a conceptual data model by starting from a functional model expressed in a natural language. We have used the Conceptual Dependency theory for mapping natural language descriptions to conceptual dependency diagrams. We have developed algorithms to convert these conceptual dependency diagrams into unit conceptual dependency tables, which are then merged to represent the whole context of the application. We also show how transactional requirements can be incorporated into the unit conceptual dependency table, and subsequently convert the unit conceptual dependency table into a corresponding conceptual model. We have developed an augmented transition network (ATN) parser to develop conceptual dependency diagrams from natural language descriptions. A prototype system has been implemented using Oracle8i and developer platforms.

With the growing popularity of component-based design it is important to have a look at, or perhaps revisit, some of the issues in component-assembly modelling, some of which are not dealt with at all or else not resolved. This paper presents a number of conceptual issues and their possible solutions.

In this paper, we share our experience in modeling and representing design knowledge relevant for engineering design decisions. We define an object model where classes are used to capture design standards and requirements relevant to designed objects. The traditional object model is customized to the representation of design knowledge in two major ways: (1) Classes representing design objects are augmented with design validation information. (2) Associations between classes are made explicit and used to reduce the redundancy and maintain the consistency of the knowledge. We define the semantics of the resulting object model and formulate the axioms that define its consistency. The object model is defined in the context of stamping design knowledge.

This research paper discusses the core object model for architectural design, developed in the context of the IDEA+project. This project aims at developing an Integrated Design Environment for Architect designers, in which design tools and computational tests are gathered around and make use of a core object model. The object-oriented analysis method MERODE is used to develop this model. Due to the method's model-driven development, conceptual modelling is subdivided in an enterprise-modelling phase and a functionality-modelling phase. This structured approach has proven to be a firm base to the development of the envisaged model and enhances the model's integration in the design environment.

This paper presents a novel application of Taguchi method to systematically tune the weights of a radial basis function (RBF) network, which is widely used for modelling vaguely defined but smooth nonlinear functions. The main strength of this method is the well-defined and systematic statistical design procedure, which is amenable to practical implementation. To illustrate the effectiveness of the Taguchi-tuned RBF, a test platform is required. This approach is applied to a platform involving high precision motion control. The developed method then is used to tune a composite motion controller incorporating RBF-based adaptive control in a high precision motion environment. Simulation and experimental results reveal the effectiveness of a Taguchi-tuned RBF.

The use of event–condition–action (ECA) rules has transformed database systems from passive query-based data repositories to active sources of information delivery. In a similar fashion, ECA rules can be used to benefit workflow systems. In this paper, a software framework known as STEP workflow management facility is proposed in order to manage collaborative and distributed workflows and to provide interfaces to object management group-compliant product data management systems. Issues related to implementation using open standards such as CORBA are discussed. A key point underlying the framework is the flexibility it affords to users to re-configure the system according to evolving needs in collaborative product development.

In this paper, we shall be dealing with the problem of space layout planning. We present an approach based on an intermediate topological level with a dynamic space ordering (dso) heuristic. Our software ARCHiPLAN proceeds through a number of steps. First all the topologically different solutions, without presuming any precise dimension, are enumerated. Next, we may evolve in this topological solution space, and than refine some of them to form consistent geometrical solutions. For each topological solution chosen, the optimising geometrical solution is determined from a cost, useful surface or wall length. By using a dynamic space ordering heuristic in the topological level the enumeration time has been reduced.

The problem of building optimally coordinated bidding strategies for competitive suppliers in energy and spinning reserve markets is addressed based on the Monte Carlo simulation and a refined genetic algorithm (RGA). It is assumed that each supplier bids a linear energy supply function and a linear spinning reserve supply function into the energy and spinning reserve markets, respectively, and the two markets are dispatched separately to minimize customer payments. Each supplier chooses the coefficients in the linear energy and spinning reserve supply functions to maximize total benefits, subject to expectations about how rival suppliers will bid. A stochastic optimization model is first developed to describe this problem and a Monte Carlo and genetic algorithm based method is then presented to solve it. A numerical example is utilized to illustrate the essential features of the method.