This paper discusses the issues related to retrieval of cases in a case-based design system. The limitations of the conventional approaches are brought out, and this is followed by a description of a new approach to indexing and retrieval. This approach aims at capturing control knowledge required for retrieval from individual retrieval examples. Since this approach is based on past retrieval examples, we call it RBEX (Retrieval Based on EXamples). The proposed approach is implemented in a prototype system called CADREM. CADREM uses design methods used in solving past design problems to solve new problems. This is closer to the derivational analogy approach rather than the more common transformational analogy. CADREM has been tried in the domain of conceptual structural design of buildings. Sample outputs from CADREM are also included.

This paper gives a theoretical foundation and implementation details of data and control structures in a diagnostic expert system with adaptive uncertainty management. The considered problem covers a class of expert systems and the application domain in which the operating personnel actively monitor and control the outcome of an industrial manufacturing process. Based on subjective ranking of the latent fault in the final output product, the operator queries the expert system for a recommended corrective action. Subsequent successful or unsuccessful corrective actions consistently modify confidence measures of all corrective recommendations from the same fault set, according to the embedded analytical model. The described approach is based on the relational data representation and procedural control structures, as opposed to a more traditional declarative, production-based system.

On June 20th, 1992, a workshop entitled the “Preliminary Stages of Engineering Analysis and Modeling” was held at Carnegie Mellon University, Pittsburgh, U.S.A. The workshop was organized in conjunction with the 2nd International Conference on Artificial Intelligence in Design (AID ’92), and aimed to provide a forum for engineers and computer scientists to examine how AI techniques could be exploited effectively in assisting engineers with the preliminary stages of engineering analysis and modeling. This report has two objectives; firstly it serves as a summary of the workshop and secondly it introduces four of the workshop papers that have been rewritten and extended for this issue.

The knowledge used in the design of engineering systems includes: understanding systems and their components, and the understanding implications of design decisions on other decisions and further problem decomposition This paper presents design as a process and then characterizes the knowledge used in synthesizing design alternatives. A knowledge based approach to design synthesis is proposed, followed by a description of the implementation of a domain independent synthesis framework. The implementation is further illustrated by an example application to structural design.

Modifiable combining functions are a synthesis of two common approaches to combining evidence. They offer many of the advantages of these approaches and avoid some disadvantages. Because they facilitate the acquisition, representation, explanation, and modification of knowledge about combinations of evidence, they are proposed as a tool for knowledge engineers who build systems that reason under uncertainty, not as a normative theory of evidence.

SightPlan refers to several knowledge-based systems that address construction site layout. Five different versions were implemented and their components of expertise are described here. These systems are alterations of one another, differing either in the problems they solve, the problem-solving methods they apply, or the tasks they address. Because they share either control knowledge, domain concepts, or heuristics, and such knowledge is implemented in well-defined modular knowledge bases, these systems could easily re-use parts of one another. Experiments like those presented here may clarify the role played by different types of knowledge during problem solving, enabling researchers to gain a broader understanding of the generality of the domain and task knowledge that is embedded in KBSs and of the power of their systems.

A system that integrates design and planning for mechanical assemblies is presented. The system integrates neural network computing that captures designer's design concept and rule-based system to generate a task-level assembly plan automatically. The design concept is expressed by a standard pattern format representing qualitative assembly information. A neural network model together with feature-based model translates the input pattern into a preliminary boundary representation (B-rep). Based on a refinement B-rep assembly representation, assembly plans are generated for practical use in a single-robot assembly workcell. A feasible assembly plan that minimizes tool changes and subassembly reorientations is generated from the system. A robust part collision detection algorithm to generate the precedence relationships among the assembly's components is included in the system. By contrast with many assembly planning systems that used a prolonged question-and-answering session or required knowledge beyond what is typically available in the design database, an automated assembly planning system presented here draws input relationships directly from the conceptual design and the geometry of the assembly. The system developed under this study extracts all reasoning information from the product model and permits the components to be assembled in a multitude of directions. Several experiments illustrate the effectiveness of the designed assembly planning system.

Concurrent engineering is often viewed either from a technical point of view—that is, as a problem that can be solved by creating and integrating computer-based tools—or from an organizational point of view—that is, as a problem that can be solved by creating and reorganizing teams of designers. In this paper we argue that concurrent engineering requires both technical and organizational solutions, and we call the result concurrent design. We believe that the essence of concurrent design is the myriad of interactions that occur at the interfaces among all of the members of a design team and all their tools. Solving either the technical or organizational problems by assuming away the interactions will not solve the problems of concurrent design.

In this paper we present two case studies of concurrent design in practice that have changed our assumptions about design and which have changed our research agenda. We also present the evolution of concurrent design research at the Carnegie Mellon Engineering Design Research Center. In our research, we have designed, manufactured, and used our own tools as well as observed their use by others—where the tools include mobile computers, design analysis programs, and information organization tools. Through this process, we have learned about design education and design practice, and we have uncovered new issues for design research. We see the interactions among design research, practice, and education as essential to understanding concurrent design.

The geometric dimensioning and tolerancing (GD&T) specifications of a design are directly associated with its performance and functional requirements. They also govern the manufacturing and quality control processes needed to achieve those requirements. This paper reviews recent work in geometric tolerance representation and reasoning and presents a generic and uniform graph-based representation scheme, called the Tolerance Network, to represent GD&T specifications across a part or assembly. The network can accommodate GD&T specifications related to the function, behavior, manufacturing, and inspection requirements embedded in design specifications and supports the use of different types of tolerances. The network also accommodates common design practices such as the specification of overconstrained features and parts. The necessary properties of such a network are discussed that allow under- and overconstrained design specifications to be detected and analyzed.

In this paper, we show how a temporal constraint propagation technique can be embedded in the machine sequencing approach for solving the job shop scheduling problem. The temporal constraint propagation algorithm propagates the precedence constraints and machine interference constraints to reduce the search space generated by the machine sequencing approach. Further, by making use of the temporal nature of the job shop scheduling, efficient algorithms to propagate precedence constraints and machine interference constraints are developed. Experimental results reveal that embedding constraint propagation in the machine sequencing approach significantly reduces the computation time more than by just using the machine sequencing approach alone. Further, the proposed temporal constraint propagation algorithms provide an order of magnitude improvement on the computation time over the conventional constraint propagation algorithm.

Large-scale engineering projects typically involve many different types of professionals who must interact and communicate with one another. This interaction produces conflicts that need to be resolved. A framework is presented in which the rationale used in a collaborative design environment for designing an artifact is also used for conflict mitigation. The framework contains mechanisms for checking interactions and prompting hypotheses about the reasons for the interactions. These hypotheses, once verified by the designers, improve conflict resolution by assisting them in coordinating and negotiating conflicts. This, in turn, enhances communication during the design process and consequently increases productivity in the engineering industry.

Published research on design rationale (DR) goes back at least 25 years. Judging by the number of publications and the variety of application domains, there has been a significant increase in related research activities in recent years. For example, there have been other special issues on design rationale (e.g., Carrol & Moran, 1991), workshops in international conferences (e.g., Lee, 1992; Chung & Bañares–Alcántara, 1994), and the first book on design rationale has just appeared (Carrol & Moran, 1996).

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.