This paper describes an application of artificial intelligence to support software reuse. We begin by discussing the characteristics of software engineering that establish dynamic reorganization as a requirement for a repository of software artifacts. We then present an experimental system that uses incremental concept formation as the basis for dynamic reorganization, and the conceptual hierarchy that was generated by the system for a set of 67 artifacts. The hierarchy is compared to a hierarchy produced manually by independent investigators, and the automatic hierarchy is evaluated in terms of retrieval efficiency and retrieval reliability. The paper ends with a discussion of three projects that share similar objectives with our work.

Design support systems need to be developed on the basis of an understanding of the human design process to be useful during design. The explicit representation of design history and rationale are of particular importance for explanation and reuse. Within the DESIRE framework for compositional modelling, a generic task model of design has been developed that clearly specifies the role of design history and design rationale within the design process. The model provides a structure to distinguish different types of design rationale, according to the functional role they play in the design process. It has been used to structure the modelling process of an example aircraft design task, which illustrates the various instances of design rationale that can be generated.

Design Expert Systems can be built using many small, cooperating, limited function expert systems called Single Function Agents (SiFAs). Using this approach we will be able to investigate and discover primitive problem-solving and interaction patterns, specific for multiagent design systems, and should gain a deeper understanding of the types of knowledge involved. This paper presents some categories of conflicts that have been studied using the SiFA approach, and makes a brief presentation of the SINE implementation of SiFAs.

The relative significance of conceptual design to basic design or detail design is widely recognized, due to its influential roles in determining the product's fundamental features and development costs. Although there are some general methodologies dealing with functions in design, virtually no commercial CAD systems can support functional design, in particular so-called synthetic phase of design. Supporting the synthetic phase of conceptual design is one of the crucial issues of CAD systems with function modeling capabilities. In this paper, we propose a computer tool called a Function-Behavior-State (FBS) Modeler to support functional design not only in the analytical phase but also in the synthetic phase. To do so, the functional decomposition knowledge and physical features in the knowledge base of the modeler, and a subsystem Qualitative Process Abduction System (QPAS) play crucial roles. Modeling scheme of function in relation with behavior and structure and design process for conceptual design in the FBS Modeler are described. The advantages of the FBS Modeler are demonstrated by presenting two examples; namely, an experiment in which designers used this tool and the design of functionally redundant machines, which is a new design methodology for highly reliable machines, as its application.

While previous work in automated process planning established plan ordering on an empirical basis alone, we derive our process plans based on the Holding-Under-Uncertainty Principle. We will introduce the principle, and we will describe the operational requirements needed to make this principle implementable in practice. The principle takes into account the form and geometric tolerances needed to locate features in deriving plan steps. Rather than just focusing on technological features, our planning strategy is controlled by the geometric relationships among features. By implementing a constraint propagation paradigm, we ensure that the tolerances accumulated in generating the part geometry remain within the tolerances specified by the design.

A general constraint-based formulation for the analysis and partial synthesis of two-dimensional truss structures is presented. This formulation is general in that it handles statically determinate and statically indeterminate trusses with pin and roller supports, and concentrated joint loads. The formulation is constraint-based in that the physical behavior of truss components is declaratively represented using constraints.

The analysis and partial synthesis of a truss structure manifest themselves in proving the satisfiability of the constraints associated with the structural components. An artificial intelligence approach called constraint logic programming is used for representing and satisfying constraints. A constraint logic programming language, called CLP(R), is used for implementing the formulation. The implemented program consists of sixteen rules. These rules are used for both the analysis and partial synthesis of truss structures. Several truss analysis and synthesis examples using the formulation are presented.

In solving a new design problem, the case-based reasoning paradigm provides a process model where previous experience in the form of multiple, individual design situations can be used in a new design context. Design synthesis presents challenges to current methodologies of CBR in the application of the various approaches to case memory organization, indexing, selection and transformation. The focus of this paper is on the transformation process. Multiple types of design knowledge are essential to derive a new design solution. A hybrid case-based design process model, CADSYN, is proposed to integrate specific design situations and generalized domain knowledge, where specific cases are represented as attribute-value pairs and domain knowledge is represented by generalized design concepts and constraints. Case transformation is treated as a constraint satisfaction problem, where a specific design case provides a starting point for a new design problem and constraints are used to revise the case for consistency with the new context.

New methods of configuration analysis have recently emerged that are based on development trends characteristic of many technical systems. It has been found that though the development of any system aims to increase a combination of the performance, reliability and economy, actual design changes are frequently kept to a minimum to reduce the risk of failure. However, a strategy of risk reduction commits the designer to an existing configuration and an approved set of components and materials. Therefore, it is important to analyze the configurations, components, and materials of past designs so that good aspects may be reused and poor ones changed. A good configuration produces the required performance and reliability with maximum economy. These three evaluation criteria form the core of a configuration optimization tool called KATE, where known configurations are optimized producing a set of ranked trial solutions. The authors suggest that this solution set contains valuable design knowledge that can be reused. This paper briefly introduces a generic method of configuration evaluation and then describes the use of a self-organizing neural network, the Kohonen Feature Map, to analyze solution sets by performing an initial data reduction step, producing archetype solutions, and supporting qualitative clustering.

This paper describes the task/episode accumulation model (TEA model) of non-routine mechanical design, which was developed after detailed analysis of the audio and video protocols of five mechanical designers. The model is able to explain the behavior of designers at a much finer level of detail than previous models. The key features of the model are (a) the design is constructed by incrementally refining and patching an initial conceptual design, (b) design alternatives are not considered outside the boundaries of design episodes (which are short stretches of problem solving aimed at specific goals), (c) the design process is controlled locally, primarily at the level of individual episodes. Among the implications of the model are the following: (a) CAD tools should be extended to represent the state of the design at more abstract levels, (b) CAD tools should help the designer manage constraints, and (c) CAD tools should be designed to give cognitive support to the designer.

This article gives an overview of the metallurgical database of ALADIN, an expert system that aids metallurgists in the design of new aluminum alloys. Declarative structured representations in the form of schemata are used for metallurgical data and concepts. The representation is very general, as the goal has been to create a representation for all knowledge about aluminum alloys and metallurgy relevant to the design process. The alloy database and the architecture of the microstructure database is discussed in detail. The microstructure of alloys is described by an enumeration of the types of microstructural elements present along with their characteristics.

This paper defines, develops algorithms for, and illustrates the utility in design of a class of mathematical operations. These accept as inputs a system of linear constraint equations, Ax = b, an interval matrix of values for the coefficients, A, and an interval vector of values for either x or b. They return a set of values for the “domain” of the other vector, in the sense that all combinations of the output vector values set and values for A, when inserted into the constraint equation, correspond to values for the input vector that lie within the input interval. These operations have been mostly overlooked by the interval matrix arithmetic community, but are mathematically interesting and useful in the design, for example, of structures.

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).

Design has been extensively studied by artificial intelligence researchers for many years. These studies have resulted in a large number of design tools that perform interesting tasks. Understanding the capabilities of these tools is, however, very difficult, which seriously impedes progress in the field. A better understanding of different tools can be achieved by analyzing the knowledge use of existing tools. Such an analysis of six configuration design tools is presented. This results in a model of configuration design that shows significant similarity in the tasks performed by these tools.

Collaborative design conflicts are an important type of process “exception,” that is, a real-life contingency such as a process change, execution error, or missed opportunity that leads to suboptimal performance of a collaborative process. This paper presents an integrated computational approach to collaborative process exception handling that avoids important weaknesses in current conflict management methods through the synergistic integration of conflict, workflow, and rationale technology. The approach is based upon an inclusive dependency language plus coordination services for dependency capture, process enactment, and exception handling. An initial implementation of this method called “iDCSS” is presented and challenges for future evolution of this technology are identified.