This paper presents a new concept, a ‘human-computer co-operative system’, as the next-generation knowledge-based system for application to project risk management. It first discusses the characteristics of project risks followed by the development of a common expert system for managing such risks. Then, system limitations are identified in terms of knowledge association, and a ‘human–computer co-operative system’ is proposed to overcome these limitations by explicitly incorporating human intuitive ability into the computer system. Finally, evaluations of the human–computer co-operative system are also described.

This paper describes EKSPRO, a knowledge-based system integrating a 3-D computer-aided design system for materials, heating, ventilation, lighting equipment, building codes and occupational health regulations, and design guidelines user-defined by architects and engineers. The system features an object-oriented predicate logic knowledge representation, and interfaces with calculation packages (CAD, thermal balance, illumination, daylight).

There exists a large body of Artificial Intelligence (AI) research on generating plans, i.e. linear or non-linear sequences of actions, to transform an initial world state to some desired goal state. However, much of the planning research to date has been complicated, ill-understood, and unclear. Only a few of the developers of these planners have provided a thorough description of their research products, and those descriptions that exist are usually unrealistically favorable since the range of applications for which the systems are tested is limited to those for which they were developed. As a result, it is difficult to evaluate these planners and to choose the best planner for a different domain. To make a planner applicable to different planning problems, it should be domain independent. However, one needs to know the circumstances under which a general planner works so that one can determine its suitability for a specific domain.

This paper presents criteria for evaluating AI planners; these criteria fall into three categories: (1) performance issues, (2) representational issues, and (3) communication issues. This paper also assesses four non-linear AI planners (NOAH, NONLIN, SIPE and TWEAK) based on a study of the published literature and on communication (via electronic mail, meetings and correspondence) with their developers.

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.

A generalized approach to fast interpretation of objects and their features has so far eluded researchers. In manufacturing, this interpretation can be approached from the vision point of view or from the CAD data perspective. Presently, CAD systems are widely used in several aspects of manufacturing production. It is therefore more efficient to use CAD data for object reasoning in manufacturing, especially when systems will eventually be data driven. Components can be modelled on a CAD system using various modelling techniques and the representation of their geometric information is still CAD system dependent. However, the advent of the Initial Graphics Exchange Specification (IGES) now makes it possible to represent CAD data in a neutral and standard manner.

This paper describes a scheme for recognizing and representing features for CAD data extracted using the IGES interface. The concepts developed are based on graph-based feature representation, where features are represented by a set of faces as well as their topological adjacency.

Strategies for classifying features and methods of decomposing a complicated feature into several simpler features for recognition purposes are discussed.

The study of languages of shape is rich and interesting. One can develop formal grammars whose languages are non-realizable shape (nonsense objects), as well as grammars whose languages are classes of realizable shape. This paper develops several graph-based multi-dimensional languages that are complete in the physical solids. Thus, realizable shape is a language.

An efficient locally minimum-time trajectory planning algorithm for coordinately operating multiple robots is introduced. The task of the robots is to carry a common rigid object from an initial position to a final position along a given path in three-dimensional workspace in minimum time. The number of robots in the system is arbitrary. In the proposed algorithm, the desired motion of the common object carried by the robots is used as the key to planning of the trajectories of all the non-redundant robots involved. The search method is used in the trajectory planning. The planned robot trajectories satisfy the joint velocity, acceleration and torque constraints as well as the path constraints. The other constraints such as collision-free constraints, can be easily incorporated into the trajectory planning in future research.

Recent research in the area of computer-aided engineering design has focused on the development of environments that provide effective integration of several domain specialties for complex multidisciplinary synthesis problems. The definition of communication requirements for co-operative interaction—and the subsequent establishment of a conceptual model for automating the process—are important considerations in the development of such environments. A communication model can also provide the basis for development of a knowledge engineering strategy by defining the organizational and representational requirements for domain knowledge in the automated system. This paper presents a conceptual model for communication in automated interactive design and demonstrates how the model can be employed as a knowledge engineering tool to facilitate the acquisition and organization of domain expertise. Both the process architecture and semantic modeling aspects of the communication problem are considered. An example is included which illustrates the use of the model in formulating an automated integrated engineering system in the domain of floor and equipment layout and design for industrial facilities.

We show that the usual notion of constraint propagation is but one of a number of similar inferences useful in quantitative reasoning about physical objects. These inferences are expressed formally as rules for the propagation of ‘labeled intervals’ through equations. We prove the rules' correctness and illustrate their utility for reasoning about objects (such as motors or transmissions) which assume a continuum of different states. The inferences are the basis of a ‘mechanical design compiler’, which has correctly produced detailed designs from ‘high level’ descriptions for a variety of power transmission and temperature sensing systems.

A logic-based approach for automating the processing of design standards is illustrated. This approach is composed of three steps: conceptualization, formalization and implementation. Conceptualization is referred to as the representation of the knowledge necessary for solving the problem of interest in terms of objects and relations. Formalization is referred to as the representation of the objects and relations of interest as axioms using the language of predicate calculus. And, Implementation is referred to as the representation of the axioms of interest and the strategy for manipulating axioms using the constructs of a programming language.

The paper illustrates the logic-based approach to engineering problem-solving automation by considering the portion of the AISC Specification that governs the design of axially loaded members. First, the relations of interest are identified (Conceptualization). Then, predicate calculus is used to formally represent the relations (Formalization) as axioms and to mechanically manipulate them. The checking and designing of structural components via mechanical manipulation of the axioms are illustrated in the paper. Finally, a constraint logic programming language is used to develop a computer program for automatic processing of the specification (Implementation). This program is composed of a set of rules that closely resemble the formulated axioms.

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.

This paper discusses the framework of a knowledge-based expert system environment to design aerospace structures under structural and aerodynamic constraints using ASTROS (Automated Structural Optimization program). ASTROS is a synthesis tool built around the NASTRAN finite element program. The knowledge base capabilities are discussed for synthesizing in statics, normal mode, steady and unsteady aerodynamic disciplines. A description of the two ASTROS advisor modules, the Editor/Bulk Data generator and Post-processor, is included. Experiences and issues involved in hierarchical representation of knowledge as menu options at different levels of abstraction are presented. Illustrative examples of the advisor in designing airframe structures are also included.