Shape annealing, a computational design method applied to structural design, has been extended to the design of traditional and innovative three-dimensional domes that incorporate the design goals of efficiency, economy, utility, and elegance. In contrast to deterministic structural optimization methods, shape annealing, a stochastic method, uses lateral exploration to generate multiple designs of similar quality that form a structural language of solutions. Structural languages can serve to enhance designer creativity by presenting multiple, spatially innovative, yet functional design solutions while also providing insight into the interaction between structural form and the trade-offs involved in multi-objective design. The style of the structures within a language is a product of the shape grammar that defines the allowable structural forms and the optimization model that provides a functional measure of the generated forms to determine the desirable designs. This paper presents an application of geodesic dome patterns that have been embodied in a shape grammar to define a structural language of domes. Within this language of domes, different dome styles are generated by changing the optimization model for dome design to include the design goals of maximum enclosure space, minimum surface area, minimum number of distinct cross-sectional areas, and visual uniformity. The strengths of the method that will be shown are 1) the generation of both conventional domes similar to shape optimization results and spatially innovative domes, 2) the generation of design alternatives within a defined design style, and 3) the generation of different design styles by modifying the language semantics provided by the optimization model.

A design is a plan containing guidelines to build and understand an artifact. Generally, this plan is constructed by a team of designers with different tasks, but sharing a common objective, that is, to create a high-quality, low-cost integrated artifact. Active Design Documents (ADDs) are powerful tools for cooperative design because they account for revealing the rationale among design participants while assisting each of them in their own. Design rationale capture and retrieval are critical issues on building documentation assistant tools. In this paper, we propose to achieve more efficient and effective delivery of design and designers intent by resorting to rhetorical means. The wealth of knowledge kept in ADD’s knowledge bases is organized into high-level Rhetorical Structure Theory (RST) schema and mapped onto input and output screen configurations that gear the interaction between systems and users. We illustrate the effects of such an organization with evidences from an implemented version of ADD for the domain of offshore platform.

Linkage-type mechanisms have numerous applications in industry especially for automation Unfortunately, they are less popular due to lack of proper design tools. This paper describes our efforts to remove the technological barrier in mechanisms design automation. Although the ideas presented apply to automation of mechanisms design in general, the paper discusses the development of an expert system for a particular sub-set of mechanisms called Dwell mechanisms.

Many essential and desirable motion characteristics of mechanisms are so implicit that they are difficult to control by analytical methods. By systematically and extensively studying the entire motion characteristics of hundreds of linkages, a comprehensive classification system and heuristics were developed. This qualitative classification scheme led to a finite set of linkage models that cover the entire design space in the sense that any possible design falls under one or more of the models. Our system, called Dwell-Expert, incorporates this design expertise to select the best linkage model for a given set of design specifications and to compare that model against alternatives. The new design methodology and its implementation in AGNESS (A Generalized Network-based Expert System Shell) are explained. A design example is also presented. Our system can reduce even an experienced designer’s initial-design time from a day or more to a minute or less, assuming specifications have already been formulated. Such results motivate extension of this design methodology to other areas of mechanical design and engineering design in general.

An expert system for the preliminary design of ships developed. The design process is understood as determining design variables and the relationships among design parameters. The relationships among the elements of design knowledge are represented by a network model. The object-oriented knowledge representations are introduced in the computer system to manipulate design variables such as the principle particulars of a ship in the network model. The expert system based on the above concept provides the following functions: (1) flexibility for building a model and easy modification of the model; (2) effective diagnosis of the design process by using rule-based knowledge representations; (3) hybrid function with both symbolic treatment of the design knowledge and numerical computations by coupling the systems programmed in LISP and FORTRAN and (4) a supporting method for determination of the design variables.

Finally the system's validity and effectiveness is ascertained by applying it to the preliminary design of a bulk carrier ship.

Using the theory of fuzzy sets, this paper develops a fuzzy logic reasoning system as an augmentation to a rule-based expert system to deal with fuzzy information. First, fuzzy set theorems and fuzzy logic principles are briefly reviewed and organized to form a basis for the proposed fuzzy logic system. These theorems and principles are then extended for reasoning based on knowledge base with fuzzy production rules. When an expert system is augmented with the fuzzy logic system, the inference capability of the expert system is greatly expanded; and the establishment of a rule-based knowledge base becomes much easier and more economical. Interpretations of the system’s power and possible future research directions conclude the paper.

A methodology for studying and understanding the process of design, and ultimately for developing a computational theory of design is presented. In particular, the role of formalization in such an investigation is set out. This is done by first presenting the background to and development of computational search as a widely adopted problem solving paradigm in artificial intelligence research. It is then suggested why computational search provides an inadequate characterization of the design process and an alternative, that design is an exploration process is proposed. By developing certain ideas first put forward by Simon the authors seek to explain why this view is taken and how it forms a central part of their Artificial Intelligence in Design research programme. It is hoped to (eventually) develop a computational theory of design. The radically incomplete nature of this work necessarily prevents the authors from answering the question posed by the title of the paper but the title does provide a good focus for their efforts.

This article discusses the issues that arise in the design and implementation of expert systems. These issues include: task selection; the stages of development of expert system projects; knowledge acquisition; languages and tools; development and run-time environments; and organizational and institutional issues. The article closes with some speculation about the future development of expert systems.

A blackboard based intelligent control system has been developed for a family of complex non-equilibrium materials processes. The system is being tested in the laboratory for control of a particular high risk, high value-added step in the manufacture of carbon-carbon composites. The system uses knowledge based methods in several fundamental ways to fill gaps left by control theory and process models. Most notable of these are (1) inferring from indirect measurements and history the process state at multiple, changing levels of abstraction, (2) anticipating problems and planning actions to reach goal (end of process) states, (3) selecting, executing and interpreting approximate models to predict process progression and (4) changing control objectives as the physical situation changes. The system has been demonstrated to substantially reduce processing time.

Because mechanical operations are performed only up to a certain precision, the geometry of parts involved in real-life products is never known precisely. But if tolerance models for specifying acceptable variations have received a substantial attention, operations on toleranced objects have not been studied extensively. That is the reason why we address in this paper the computation of the union and the intersection of toleranced simple polygons, under a simple and already known tolerance model. First, we provide a practical and efficient algorithm that stores in an implicit data structure the information necessary to answer a request for specific values of the tolerances without performing a computation from scratch. If the polygons are of sizes m and n, and s is the number of intersections between edges occurring for all the combinations of tolerance values, the preprocessed data structure takes O(s) space and the algorithm that computes a union/intersection from it takes O((n + m)log s + k' + k log k) time, where k is the number of vertices of the union/intersection and k ≤ k' ≤ s. Although the algorithm is not output sensitive, we show that the expectations of k and k' remain within a constant factor τ, a function of the input geometry. Second, we define and study the stability of union or intersection features. Third, we list interesting applications of the algorithms related to feasibility of assembly and assembly sequencing of real assemblies.

Current design practices mandate that engineering designs be evaluated based on multiple attributes, e.g., cost, power, and area. For multiattribute design problems, generation and evaluation of the Pareto optimal set guarantees the optimal design will be found, but is not practical for a large class of problems. Iterative techniques can be applied to most problems, but sacrifice optimality. In this paper, we introduce a new technique that extends the set of design problems that can be solved optimally. By first constructing an imprecise value function, the number of nondominated alternatives that must be generated is reduced. We describe an implementation based on combinatorial optimization and constraint satisfaction which achieves additional performance gains by decomposing the value function to identify dominated design-variable assignments. Test results indicate that our approach extends the set of problems that can be solved optimally.

An ongoing research effort is consolidating material and process knowledge in a critiquing system dealing with fuzzy criteria to aid designers in evaluating the incorporation of composite materials into their design. The extent of knowledge required to perform the task of evaluating composite processes and materials is often beyond the expertise of many design engineers as they lack understanding of the nature of composite material manufacturing. The system under development is known as the Composites Design and Manufacturing Critiquing System (CDMCS). The CDMCS critiques a submitted design through interaction with the user. An account of the strengths and weaknesses of the design is supplied to the user through the facilities. The current focus of the system is on process selection, but the system is generic so that other aspects of composite material manufacturing may be included. The system is implemented in Macintosh™ Common LISP. This article describes the features of the system that have been implemented. The system is currently being extended to cover more than the primary process component of the domain.

A method is proposed for creative innovative design that is in concordance with the act of knowledge integration in learning; creative innovative design is defined as a guided (creative) process for arriving at an artifact that is socially valuable (practical and needed) and original (innovative). Within the context of models of reasoning, the process of design is interpreted and analyzed with a goal of extracting the stages at which it can be consciously improved by mindful control. A language is proposed for team-oriented intra- or interdisciplinary collaborative, as well as individual design that facilitates communication, mutual understanding, and makes explicit alternative nonverbal, nonquantitative thinking processes that otherwise may remain latent. The role of motivation in innovation is briefly discussed, as well as the role of artifact valuation in a societal context. Although not central to the present discussion, computer models of design are presented as an instance of design practice captured for computer-based design support. A brief discussion highlights the application and implications of the proposed method to education and research.

This paper proposes and evaluates a neural network-based method for simulating manufacturing processes that exhibit both noncontinuous and stochastic behavior processes more conventionally modeled, using discrete-event simulation algorithms. The incentive for developing the technique is its potential for rapid execution of a simulation through parallel processing, and facilitation of the development and improvement of models particularly where there is limited theory describing the dependence between component processes. A brief introduction is provided to a radial-Gaussian neural network architecture and training process, the system adopted for the work presented in this paper. A description of the basic approach proposed for applying this technology to simulation is then described. This involves the use of a modularized neural network approach to model construction and the prediction of the occurrence of events using information retained from several previous states of the simulation. A class of earth-moving systems, comprising a push-dozer and a fleet of scrapers, is used as the basis for assessing the viability and performance of the proposed approach. A series of experiments show the neural network to be capable of both capturing the characteristic behavior and making an accurate prediction of production rates of scraper-based earth-moving systems. The paper concludes with an indication of some areas for further development and evaluation of the technique.

The conventional engineering design process consisting of three phases, synthesis, analysis and evaluation can be extended for solving rehabilitation problems by including a diagnosis phase during which abnormalities and malfunctions are identified and characterized. After diagnosis, the design objectives are clearly specified and the conventional engineering design process can begin. Different problem solving strategies, information representation, and processing are useful for the different phases of rehabilitation design. This paper describes the RETAIN knowledge-based rehabilitation design system which integrates a relational database, production rules and algorithmic functions. RETAIN diagnoses retaining wall failures and synthesizes preliminary rehabilitation designs and cost estimates. Its framework and methodology may be applied to other infrastructure components such as pavements, water and sewage networks, bridge piers and marine structures. RETAIN decomposes rehabilitation problems into influencing failure modes then identifies a set of rehabilitation strategies such that each strategy remedies one or more failure modes. Complete rehabilitation solutions are formed by searching and combining strategy components. Conceptual knowledge for design synthesis is organized in relational database tables. The paper includes an example of design synthesis with relational operations for selecting rehabilitation strategies and forming complete rehabilitation solutions.