bluuebunny/crossref_metadata_2025_split huggingface dataset:
MAPCon: a case study in a configuration expert system
Authors: Parunak H. V. D. , Kindrick J. D. , Muralidhar K. H. 
Published: March 2010

MAPCon II is the second generation (Muralidhar and Irish, IEEE Journal on Selected Areas in Commumcctions 6(5), 869–873, 1988) of an expert system that interactively guides a user in performing off-line configuration for local area networks that use MAP, the manufacturing automation protocol. This paper describes the configuration task in general and MAPCon in particular.Though MAPCon's purpose is off-line configuration, its problem domain requires that it accomplish other reasoning objectives in addition to those commonly associated with configuration. It is in the process of being expanded into an on-line network supervisor. We develop a taxonomy of reasoning objectives and show how MAPCon combines two different kinds of reasoning to accomplish its objectives. Our experience confirms that of other researchers, and suggests that building robust, practical systems will require us to understand more clearly the interfaces among different reasoning objectives.The paper has four parts: 1. a definition of configuration and other reasoning objectives; 2. a summary of the problem domain in which MAPCon operates; 3. a description of MAPCon as the user sees it; 4. a look ‘under the hood’ to see how MAPCon combines different objectives.
OARPLAN: Generating project plans by reasoning about objects, actions and resources
Authors: Darwiche Adnan , Levitt Raymond E. , Hayes-Roth Barbara 
Published: March 2010

This paper describes OARPLAN, a prototype planning system that generates construction project plans from a description of the objects that comprise the completed facility. OARPLAN is based upon the notion that activities in a project plan can be viewed as intersections of their constituents: objects, actions and resources. Planning knowledge in OARPLAN is represented as constraints based on activity constituents and their interrelationships; the planner functions as a constraint satisfaction engine that attempts to satisfy these constraints. The goal of the OARPLAN project is to develop a planning shell for construction projects that (i) provides a natural and powerful constraint language for expressing knowledge about construction planning, and (ii) generates a facility construction plan by satisfying constraints expressed in this language.To generate its construction plan, OARPLAN must be supplied with extensive knowledge about construction objects, actions and resources, and about spatial, topological, temporal and other relations that may exist between them. We suggest that much of the knowledge required to plan the construction of a given facility can be drawn directly from a three-dimensional CAD model of the facility, and from a variety of databases currently used in design and project management software. In the prototype OARPLAN system, facility data must be input directly as frames. However, we are collaborating with database researchers to develop intelligent interfaces to such sources of planning data, so that OARPLAN will eventually be able to send high level queries to an intelligent database access system without regard for the particular CAD system in which the project was designed.We begin by explaining why classical AI planners and domain specific expert system approaches are both inadequate for the task of generating construction project plans. We describe the activity representation developed in OARPLAN and demonstrate its use in producing a plan of about 50 activities for a steel-frame building, based on spatial and topological constraints that express structural support, weather protection and safety concerns in construction planning. We conclude with a discussion of the research issues raised by our experiments with OARPLAN to date.
Evolutionary learning of novel grammars for design improvement
Authors: Gero John S. , Louis Sushil J. , Kundu Sourav 
Published: March 2010

AbstractThis paper focuses on that form of learning that relates to exploration, rather than generalization. It uses the notion of exploration as the modification of state spaces within which search and decision making occur. It demonstrates that the genetic algorithm formalism provides a computational construct to carry out this learning. The process is exemplified using a shape grammar for a beam section. A new shape grammar is learned that produces a new state space for the problem. This new state space has improved characteristics.
Learning design concepts using machine learning techniques
Authors: Maher Mary Lou , Li Heng 
Published: March 2010

AbstractThe use of machine learning techniques requires the formulation of a learning problem in a particular domain. The application of machine learning techniques in a design domain requires the consideration of the representation of the learned design knowledge, that is, a target representation, as well as the content and form of the training data, or design examples. This paper examines the use of a target representation of design concepts and the application, adaptation, or generation of machine learning techniques to generate design concepts from design examples. The examples are taken from the domain of bridge design. The primary machine learning paradigm considered is concept formation.
A neural network-based machine learning approach for supporting synthesis
Authors: Ivezic Nenad , Garrett James H. 
Published: March 2010

AbstractThe goal of machine learning for artifact synthesis is the acquisition of the relationships among form, function, and behavior properties that can be used to determine more directly form attributes that satisfy design requirements. The proposed approach to synthesis knowledge acquisition and use (SKAU) described in this paper, called NETSYN, creates a function to estimate the probability of each possible value of each design property being used in a given design context. NETSYN uses a connectionist learning approach to acquire and represent this probability estimation function and exhibits good performance when tested on an artificial design problem. This paper presents the NETSYN approach for SKAU, a preliminary test of its capability, and a discussion of issues that need to be addressed in future work.
A dynamic memory of software designs
Authors: Henderson Scott , Bailin Sidney C. 
Published: March 2010

AbstractThis 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.
On the evolution of CAE research
Authors: Dym Clive L. , Levitt Raymond E. 
Published: March 2010

AbstractLess than a decade ago it seemed that a new paradigm of engineering–called computer-aided engineering (CAE) – was emerging. This emergence was driven in part by the success of computer support for the tasks of engineering analysis and in part by a new understanding of how computational ideas largely rooted in artificial intelligence (AI) could perhaps improve the practice of engineering, especially in the area of design synthesis. However, while this “revolution” has failed to take root or flourish as a separate discipline, it has spawned research that is very different from traditional engineering research. To the extent that such CAE research is different in style and paradigm, it must also be evaluated according to different metrics. Some of the metrics that can be used are suggested, and some of the evaluation issues that remain as open questions are pointed out.
A multifaceted approach to evaluating expert systems
Authors: Adelman Leonard , Gualtieri James , Riedel Sharon L. 
Published: March 2010

AbstractA multifaceted approach to evaluating expert systems is overviewed. This approach has three facets: a technical facet, for “looking inside the black box”; an empirical facet, for assessing the system’s impact on performance; and a subjective facet, for obtaining users’ judgments about the system. Such an approach is required to test the system against the different types of criteria of interest to sponsors and users and is consistent with evolving lifecycle paradigms. Moreover, such an approach leads to the application of different evaluation methods to answer different types of evaluation questions. Different evaluation methods for each facet are overviewed.
Proof planning: A methodology for developing AI systems incorporating design issues
Authors: Lowe Helen 
Published: March 2010

AbstractIn cases where a domain theory can be successfully expressed in a logical formalism and can be used to formulate a task in that domain in mathematical terms, the task of building sound knowledge-based systems is greatly facilitated. However, it is not immediately obvious how the design aspects of such tasks, where these are an important feature of problem solving, can be incorporated in this approach. Design issues differ from search problems in that there may be several choices, each valid in some sense, but not (necessarily) equally good or equally appropriate in the current context. A case study is described in which a methodology is used based on the development of proof plans. The ability to conduct research according to the Popperian framework of hypothesis, validation, testing, and modification in response to empirical evidence – the hypothetico-deductive approach – seems essential to any rigorous scientific endeavor. It is believed that proof planning is a method which readily exploits this inherently incrementalist approach and could prove to be a powerful tool in designing AI systems.
Improving design and documentation by using partially automated synthesis
Authors: Garcia A. Cristina Bicharra , Howard H. Craig , Stefik Mark J. 
Published: March 2010

AbstractOne of the products of engineering, besides constructed artifacts, is design documentation. To understand how design participants use documentation, designers and typical documentation users were interviewed and protocols were taken of them both creating and using design documentation. The protocols were taken from realistic projects of preliminary design for heating, ventilation, and air conditioning systems (HVAC). The studies of document creation and use revealed three important issues: (1) design participants not only look up design facts; they frequently access documents to obtain information about the rationale for design decisions; (2) the design rationale that they see often is missing from the documents; and (3) design requirements change frequently over a project life cycle so that design documents are often inconsistent and out of date. Recognizing these documentation issues in design practice, a new approach was developed in which documents are no longer static records, but rather interactive design models supporting a case. The feasibility of the approach was demonstrated by constructing a running system and testing it with designers on realistic problems. The costs and benefits of creating and using documentation of design rationale also were analyzed. In particular, the active documents approach was evaluated for a routine, preliminary design in domains where community practice is widely shared and largely standardized. The approach depends on the feasibility of creating a parametric design model for the design domain.
ADES: An expert system for ATP design
Authors: Cremonini Roberto , Lamma Evelina , Mello Paola 
Published: March 2010

This paper presents an expert system (called ADES, i.e. ATP Design Expert System) for the automatic design of Automatic Train Protection systems (ATP). An ATP system is a railway signalling system constituted by a set of logic circuits that control the safe movement of trains within a railway station.AI techniques proved feasible to address the particular design problem discussed: ADES is able to rapidly design good control circuits to meet operational requirements by using a well-structured, explicitly represented, in depth knowledge of Automatic Train Protection. The use of AI techniques facilitates the maintenance and extension of ADES to face new or unplanned requirements.Implementing both the expert system and its environment tools in the PROLOG language, by using meta-interpretation techniques, has led to the rapid prototyping of the overall system. Optimization techniques have also been developed to allow ADES to be efficiently executed.
Rule-based generation of exploded-views and assembly sequences
Authors: Kroll Ehud , Lenz Ehud , Wolberg John R. 
Published: March 2010

AbstractDirect planning of assembly sequences is either very complicated computationally, or requires an ‘expert’ user. This paper presents a new approach to the automatic generation of assembly plans which involves two phases. An ‘exploded’ layout of the assembled product is first found from its topological and geometric description by a graph-based procedure. Then, a knowledge-based technique is used for planning of selected assembly sequences by utilizing theoretical as well as heuristic knowledge of mechanical components and assembly processes. Besides serving the assembly planning phase, automatic generation of exploded-views could also be a most desirable feature of any computer-aided design system. An example demonstrates the application of the method to an actual product.
An attribute-space representation and algorithm for concurrent engineering
Authors: Darr Timothy P. , Birmingham William P. 
Published: March 2010

AbstractThis paper presents a novel formulation of the configuration-design problem that achieves the benefits of the concurrent engineering (CE) design paradigm. In CE, all design concerns (manufacturability, testability, etc.) are applied to an evolving design throughout the design cycle. CE identifies conflicts early on, avoids costly redesign, and leads to better products. Our formulation is based on a distributed dynamic interval constraint-satisfaction problem (DDICSP) model. Persistentcatalog agentsmap onto DDICSP variables andconstraint agentsmap onto DDICSP constraints. These agents use a set of operations and heuristics to navigate the design space to eliminate sets of designs until a solution is found. Experimental results show that an architecture where each catalog agent resides on a separate computer has performance advantages over nondistributed approaches.
Indexing and retrieval of cases in a case-based design system
Authors: Raphael B. , Kumar B. 
Published: March 2010

AbstractThis 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.
Reconstructive derivational analogy: A machine learning approach to automating redesign
Authors: Britt B.D. , Glagowski T. 
Published: March 2010

AbstractThis paper describes current research toward automating the redesign process. In redesign, a working design is altered to meet new problem specifications. This process is complicated by interactions between different parts of the design, and many researchers have addressed these issues. An overview is given of a large design tool under development, the Circuit Designer's Apprentice. This tool integrates various techniques for reengineering existing circuits so that they meet new circuit requirements. The primary focus of the paper is one particular technique being used to reengineer circuits when they cannot be transformed to meet the new problem requirements. In these cases, a design plan is automatically generated for the circuit, and then replayed to solve all or part of the new problem. This technique is based upon the derivational analogy approach to design reuse. Derivational Analogy is a machine learning algorithm in which a design plan is saved at the time of design so that it can be replayed on a new design problem. Because design plans were not saved for the circuits available to the Circuit Designer's Apprentice, an algorithm was developed that automatically reconstructs a design plan for any circuit. This algorithm, Reconstructive Derivational Analogy, is described in detail, including a quantitative analysis of the implementation of this algorithm.
From design experiences to generic mechanisms: Model-based learning in analogical design
Authors: Bhatta Sambasiva R. , Goel Ashok K. 
Published: March 2010

AbstractAnalogical reasoning plays an important role in design. In particular, cross-domain analogies appear to be important in innovative and creative design. However, making cross-domain analogies is hard and often requires abstractions common to the source and target domains. Recent work in case-based design suggests that generic mechanisms are one type of abstractions useful in adapting past designs. However, one important yet unexplored issue is where these generic mechanisms come from. We hypothesize that they are acquired incrementally from design experiences in familiar domains by abstraction over patterns of regularity. Three important issues in abstraction from experiences are what to abstract from an experience, how far to abstract, and what methods to use. In this short paper, we describe how structure-behavior-function models of designs in a familiar domain provide the content, and together with the problem-solving context in which learning occurs, also provide the constraints for learning generic mechanisms from design experiences. In particular, we describe the model-based learning method with a scenario of learning feedback mechanism.
Computational model for conceptual design based on extended function logic
Authors: Sturges Robert H. , O'Shaughnessy Kathleen , Kilani Mohammed I. 
Published: March 2010

AbstractFunction logic methods have been successfully used in Value Analysis (VA) and Value Engineering (VE) for several decades. This functional approach attempts to provide a common language for specialists in multiple domains. This paper describes an extension of function logic that assists in systematic identification of design functions, allocations, and their interrelations. Our approach identifies a three-level function/allocation/component information structure to represent the state of the design. We illustrate new types of links that exist between functions and the effect of these on the representation of the interrelated functions. These linkages provide new pathways for design information and function evaluation through allocation arithmetic and supported functions. A computational model of the conceptual design process is proposed based on the extended function logic design representation. An outline of the inputs, outputs and operations on form and function variables is given as a step prior to the synthesis process. We illustrate, by example, the process of translating functional representations across specialist domains. Finally, a computer-based aid to developing functional models is described.
Functional descriptions used in computer support for qualitative scheme generation—“Schemebuilder”
Authors: Bracewell R.H. , Sharpe J.E.E. 
Published: March 2010

AbstractWith increased pressures coming from global competition and requirements for greater innovation in product development, designers are hard pressed to deliver designs of higher quality and variety using a repertoire of technological options from different disciplines. This interdisciplinary product development approach has not only removed many of the traditional constraints to design but has now given designers a much wider freedom of choice as to the best solution to a design problem. The focus of this paper is a knowledge-based design environment called Schemebuilder, which is a comprehensive and integrated suite of software tools aimed at supporting the designer in the rapid development of product design models in the conceptual, through embodiment stages of design. Illustrated is the use of the software tools in the qualitative generation of alternative schemes, by application of stored working and decomposition principles in the development of a function-means tree-like information structure. With mechatronic product development as the main theme, this paper describes a closely integrated methodology that incorporates a bond graph approach to continuous-time energetic systems and high-level Petri nets for the rigorous description of discrete-time information systems. Additionally, a technique is suggested for the decomposition of free format statements of need into the rigorously defined design context and required functions, which form the starting point of the function-means development process.
Feature modeling based on design catalogues for principle conceptual design
Authors: Peien Feng , Guorong Xu , Mingjun Zhang 
Published: March 2010

AbstractThe research on new types of design knowledge bases and conceptual solution catalogues is an advanced subject of design methodology. Using the separate function as an example, this paper establishes design catalogues for principle conceptual design to realize the function, and proposes a general computer-oriented action principle design process. Upon studying the relationship of knowledge in the process, this paper represents functions of action principles in function feature models and provides computer-oriented feature models for action principle design.
Genetic algorithm synthesis of four-bar mechanisms
Authors: Roston Gerald P. , Sturges Robert H. 
Published: March 2010

AbstractThe synthesis of four-bar mechanisms is a well-understood, classical design problem. The original systematic work in this field began in the late 1800s and continues to be an active area of research. Limitations to the classical theory of four-bar synthesis potentially limit its application to certain real-world problems by virtue of the small number of precision points and unspecified order. This paper presents a numerical technique for four-bar mechanism synthesis based on genetic algorithms that removes this limitation by relaxing the accuracy of the precision points.