Automated knowledge acquisition for the surface-mount PWB assembly domain

The development of knowledge-based (or expert) systems for the surface-mount printed wiring board (PWB) assembly domain requires the understanding and regulation of several complex tasks. While the knowledge base in an expert system serves as a storehouse of knowledge primitives, its design and development is a bottleneck in the expert system development life-cycle. Therefore the development of an automated knowledge acquisition (KA) facility (or KA tool) would facilitate the implementation of expert systems for any domain. This paper describes an automated KA tool that helps to elicit and store information in domain-specific knowledge bases for surface-mount PWB assembly. A salient feature of this research is the acquisition of uncertain information.     

Robot programming system for assembly: Conceptual graph-based approach

This work develops a method for robot program synthesis. Currently, the programming task is one of the major hurdles of robotic application. Progress towards automatic synthesis of robot programs will ease industrial robot application. The proposed system provides a means towards automated (guided by knowledge) conversion of a user's request, expressed in natural language, to the appropriate conceptual model of the required task. This model incorporates the information necessary for understanding, planning, and sensory-guided performance of the required robotic task.First, we state the problem of robotic assembly and recognize its hierarchic structure as the structure of a system that builds a predesigned assembly. Next, we present and analyze the requirements of the robotic assembly domain. This analysis enables us to draw conclusions concerning the most suitable methodology for the development of a support system for assembly program synthesis and interpretation. It is the conceptual graph-based approach. Then we present the algorithm of the proposed conceptual graph-based system and show how the system synthesizes robotic assembly operations, such as valid assembly sequences and sequences of special treatments for the assembled components (including the determination of the required resources). Finally, a case study illustrates the approach developed here on a large family of multi-axisymmetric components. We also present illustrative examples of working sessions with the current implementation of the system.     

PCAAD—an object-oriented expert system for assembly of printed circuit boards

Abstract: Electronics manufacturing is the fastest growing segment of the manufacturing domain today. The rapid change in printed circuit board manufacturing has been possible with the induction of surface-mounted components and robotic assembly. The high density packaging capability of surface-mounted technology has contributed enormously to the development of new trends in printed circuit board manufacturing.
PCAAD—Printed Circuit Board Assembly Advisor—is an expert system developed to capture this new technology and its interaction with the existing through-hole-mounting technology. In building the system, rules and guidelines pertaining to assembly are formulated and incorporated into the knowledge-base. The system is built on an object-oriented paradigm. The object-oriented approach, Smalltalk-80, the object-oriented language and the hierarchical rule structure paradigm are briefly discussed. A rating system is also introduced to rank various assembly designs. PCAAD can advise whether or not to proceed with assembly with a particular assembly design, and suggests assembly modification at the early stage of design to eliminate the assembly problems in the later phase of board production.     

Expert systems in engineering design: an application for injection molding of plastic parts

The rich development environments of expert system shells provide tools for developing knowledge-based expert systems for complex tasks such as engineering design. The diverse knowledge in engineering design combines heuristics with deterministic knowledge, from multiple sources, and involves complicated, interrelated components. The hybrid capabilities in emerging expert system tools effectively address this diverse knowledge, and facilitate the rapid development of design aids by the engineering designer. A prototype expert system for injection-molded plastic parts demonstrates the utility of expert systems for design applications. The prototype is implemented in an object-oriented, rule-based environment, and incorporates solid modeling software and external material databases.     

e-CAPP: A distributed collaborative system for internet-based process planning

Advances in distributed technologies have enabled engineers to communicate more effectively, collaborate, obtain, and exchange a wide range of design resources during product development. Shared internet-based virtual environments allow experts in remote locations to analyze a virtual prototype, together and simultaneously in centers in which the product is being developed.This paper presents a system for distributed and collaborative environment which could assist manufacturing enterprises and experts in discussing, suggesting, evaluating and selecting best process plans for family of manufacturing parts. The represented e-CAPP system enables the implementation of expert knowledge in an appropriate knowledge repository. The knowledge from this repository is integrated into intra-company CAPP systems and used while generating process plans for new products. The proposed internet-based collaborative environment, dedicated to distributed process planning, is yet another step in the direction advancing of distributed manufacturing.     

A purely object-oriented approach for rule-based paradigms

In this paper, I describe an approach for rule-based systems exploiting a purely object-oriented approach. The innovative idea is to consider a new kind of relation between knowledge objects which are believed to model implication relations of production rules. A knowledge base consisting of such objects can be conveniently represented as a Marker Propagating Graph (MPG), which provides rule-based-like representation features. The inference is seen as a marking propagation through the graph. This approach preserves the best of both the object orientation features and expert system functionality. This experimental study concerns the design and the implementation of a medical system for automatic interpretation of biological tests in Preventive Medicine Centers. Because the use of such a system is planned for many years, the possibilities for its future extensions are seriously considered. This would not be possible without a good appreciation of object orientation features.     

A structural equation modeling approach to generate explanations for induced rules

The performance of an expert system depends on the quality and validity of the domain-specific knowledge built into the system. In most cases, however, domain knowledge (e.g. stock market behavior knowledge) is unstructured and differs from one domain expert to another. So, in order to acquire domain knowledge, expert system developers often take an induction approach in which a set of general rules is constructed from past examples. Expert systems based upon the induced rules were reported to perform quite well in the hold-out sample test.

However, these systems hardly provide users with an explanation which would clarify the results of a reasoning process. For this reason, users would remain unsure about whether to accept the system conclusion or not. This paper presents an approach in which explanations about the induced rules are constructed. Our approach applies the structural equation model to the quantitative data, the qualitative format of which was originally used in rule induction. This approach was implemented with Korean stock market data to show that a plausible explanation about the induced rule can be constructed.     

Automated Integration of External Databases: A Knowledge-Based Approach to Enhancing Rule-Based Expert Systems

Expert system applications in the biomedical domain have long been hampered by the difficulty inherent in maintaining and extending large knowledge bases. We have developed a knowledge-based method for automatically augmenting such knowledge bases. The method consists of automatically integrating data contained in commercially available, external, online databases with data contained in an expert system's knowledge base. We have built a prototype system, named DBX, using this technique to augment an expert system's knowledge base as a decision support aid and as a bibliographic retrieval tool. In this paper, we describe this prototype system in detail, illustrate its use, and discuss the lessons we have learned in its implementation.     

Quantitative knowledge based approach for preliminary design of tall buildings

A knowledge based expert system for the preliminary design of tall buildings has been developed. The system implementation is based on the integration of symbolic and numerical processing. A domain independent shell has been employed in the expert system development and verification. The rule based knowledge base of the system includes a set of IF/THEN rules that provide the inference mechanism with the information needed in the judgemental process. A numerical algorithm is introduced to help quantify the decision making process by relating the confidence factors for each possible solution to a numerical quantity defined as the virtual number of stories. The judgemental process is coupled with the numerical algorithm through the external program facility provided in the expert system development shell.     

Learning expert systems by being corrected

This paper describes a new method of knowledge acquisition for expert systems. A program, KABCO, interacts with a domain expert and learns how to make examples of a concept. This is done by displaying examples based upon KABCO's partial knowledge of the domain and accepting corrections from the expert. When the expert judges that KABCO has learnt the domain completely a large number of examples are generated and given to a standard machine learning program that learns the actual expert system rules. KABCO vastly eases the task of constructing an expert system using machine learning programs because it allows expert system rule bases to be learnt from a mixture of general (rules) and specific (examples) information. At present KABCO can only be used for classification domains but work is proceedings to extend it to be useful for other domains. KABCO learns disjunctive concepts (represented by frames) by modifying an internal knowledge base to remain consistent with all the corrections that have been entered by the expert. KABCO's incremental learning uses the deductive processes of modification, exclusion, subsumption and generalization. The present implementation is primitive, especially the user interface, but work is proceeding to make KABCO a much more advanced knowledge engineering tool.     

Knowledge-based approach and system for assembly-oriented design,Part II: the system implementation

Assembly is one of the most important stages for product development. Assembly-oriented design (AOD) is a new approach to designing assemblies, which uses a number of design and analysis tools to help the designer plan out and analyze candidate assembly schemes prior to having detailed knowledge of the geometry of the parts. Using this approach, many assembly schemes can be inexpensively evaluated for their ability to deliver the important characteristics of the final product. This research proposes a knowledge-based approach and develops an expert design system to support top-down design for assembled products. The presentation of research report is divided into two parts: the knowledge-based approach (Part I) and the knowledge-based expert design system (Part II). This paper is the second part of the report (Part II). It will focus on the development of knowledge-based expert design system for assembly oriented design. The knowledge-based assembly oriented design system, i.e., the assembly oriented design expert system (AODES) is constructed to integrate assembly modeling and design, assembly planning, assemblability analysis and evaluation within a concurrent engineering environment. This intelligent system is implemented by integrating object-oriented representation, constraint-based modeling, rule-based reasoning, truth maintenance, and interfacing to database management system and CAD module, in which fuzzy logic based knowledge representation and inference technique are also applied to deal with uncertain data and knowledge in the design process. The developed system differs from the existing systems adopting part-first bottom-up modeling technique, in which a comprehensive intelligent framework is used for assembly modeling and design in a top-down manner from the conceptual level to the detailed level. It is able to help obtain better design ideas, provide users with suggestions so as to create and improve a design, and therefore give users the possibility to assess and reduce the total production cost at an early stage during the design process. Through the use of the system, the concurrent engineering knowledge can be effectively incorporated into the assembly design process in an integrated manner. A case assembly design shows that the intelligent modeling and design system is feasible.     

支持异地协同产品设计的知识服务模型

提出基于XML元语言，以统一的信息化格式描述设计知识，使用Java技术构建了支持多专家协同设计的基本框架，将各类设计服务封装为Web服务的形式，实现了一种Web使能的知识服务模型(Web-KSS)，并应用该模型实现了支持成套电器产品设计的知识服务系统。     

一种基于规则的双层四边通道布线专家系统原型

四边通道布线问题(switchbox routing problem)是VLSI布图设计(layout)中的一个关键问题。从计算的观点看,它是一个NP-hard问题。因此,基于知识的方法是解决这一问题的有效方法。 本文中,提出了一种以PROLOG为核心的基于规则的双层四边通道布线专家系统的原型(prototype)。它能把人类布线专家的规划、推理能力及布线经验同计算机的高速数据处理能力有机地结合起来,从而取得较高的布线效率和布通率。     

An integrated system for knowledge sharing among heterogeneous knowledge derivation systems

Solving problems in a complex application domain often requires a seamles integration of some existing knowledge derivation systems which have been independently developed for solving subproblems using different inferencing schemes. This paper presents the design and implementation of an Integrated Knowledge Derivation System (IKDS) which allows the user to query against a global database containing data derivable by the rules and constraints of a number of cooperative heterogeneous systems. The global knowledge representation scheme, the global knowledge manipulation language and the global knowledge processing mechanism of IKDS are described in detail. For global knowledge representation, the dynamic aspects of knowledge such as derivational relationships and restrictive dependencies among data items are modeled by a Function Graph to uniformly represent the capabilities (or knowledge) of the rule-based systems, while the usual static aspects such as data items and their structural interrelationships are modeled by an object-oriented model. For knowledge manipulation, three types of high-level, exploratory queries are introduced to allow the user to query the global knowledge base. For deriving the best global answers for queries, the global knowledge processing mechanism allows the rules and constraints in different component systems to be indiscriminately exploited despite the incompatibilities in their inferencing mechanisms and interpretation schemes. Several key algorithms required for the knowledge processing mechanism are described in this paper. The main advantage of this integration approach is that rules and constraints can in effect be shared among heterogeneous rule-based systems so that they can freely exchange their data and operate as parts of a single system. IKDS achieves the integration at the rule level instead of at the system level. It has been implemented in C running in a network of heterogenous component systems which contain three independently developed expert systems with different rule formats and inferencing mechanisms.Database Systems Research and Development Center, Department of Computer Information Sciences, Department of Electrical Engineering, University of Florida     

Case-based reasoning and adaptation in hydraulic production machine design

Case-based reasoning (CBR) can support hydraulic circuit design. Existing expert systems for hydraulic system design use production rules as its source of knowledge. However, this leads to problems of knowledge acquisition and knowledge base maintenance. This paper describes the application of CBR to hydraulic circuit design for production machines, which helps solving problems using past experience. A technique Case-based adaptation (CBA) is implemented in the adaptation stage of CBR so that adaptation becomes much easier. A prototype system has been developed to verify the usefulness of CBR and CBA in hydraulic production machines.     

Knowledge-based approach and system for assembly oriented design,Part I: the approach

Assembly is one of the most important stages for product development. Assembly-oriented design (AOD) is a new approach to designing assemblies, which uses a number of design and analysis tools to help the designer plan out and analyze candidate assembly schemes prior to having detailed knowledge of the geometry of the parts. Using this approach, many assembly schemes can be inexpensively evaluated for their ability to deliver the important characteristics of the final product. This research proposes a knowledge-based approach and develops an expert design system to support top-down design for assembled products. The presentation of research report is divided into two parts: the knowledge-based approach (Part I) and the knowledge-based expert design system (Part II). This paper is the first part of the report (Part I), which mainly proposes a knowledge-based approach and framework for intelligent assembly oriented design. The proposed approach focuses on the integration of product design, assemblability analysis and evaluation, and design for assembly with economical analysis. It differs from the existing approaches adopting the part-first bottom-up modeling technique, in which a hybrid model related to design problem-solving including function–behavior–structure model, feature-based geometric model, and parametric constraint model is used as a comprehensive intelligent framework for assembly modeling and design in a top-down manner from the conceptual level to the detailed level. Through the use of intelligent approach and framework, concurrent engineering knowledge can be effectively incorporated into the assembly design process, and a knowledge-based expert design system can be implemented.     

An expert system for setting time steps in dynamic finite element programs

An expert system, ETUDES—Expert Time integration control Using Deep and Surface Knowledge System, which addresses the determination of the timestep for time integration of linear structural dynamic equations is described. This time-step may also be applicable for a moderately nonlinear simulation of the same structure. The program also determines whether an explicit or implicit method is most efficient for the particular simulation. A production rule programming system written in OPS5 is used for the implementation of this prototype expert system. Issues relating to the expert system architecture for this application, such as knowledge representation and structure, as well as domain knowledge are discussed. The prototype is evaluated by measuring it's performance in various benchmark model problems.     

A fuzzy expert system for a service centre of spare parts

This paper presents the design of an approximate reasoning framework for an expert system prototype for a service centre of spare parts, to which customers bring failed items for repair. The design development is fundamentally based upon an analysis of a queuing model associated with the service centre system problem. This queuing model provides a prerequisite insight and the knowledge about such a service system. The building process for the framework is described in a case study utilizing the queuing model, namely, M/M/c repair systems with spares. The objective here is to aid management in determining certain decision policies and the capacities which are critical to them. Within the approximate reasoning framework, the identification and the construction of the basic rules that contain uncertain (vague, ambiguous, fuzzy) linguistic terms are described, as well as the specification of the membership functions that represent the meaning of such linguistic terms. Consistency of rules is studied in accordance with the internal relationships between system variables. Approximate Analogical Reasoning with a tree search is used as the inference engine of the expert system. Approximate reasoning results are compared with analytical results.     

A hierarchical expert system for computer process control

This paper reports on the design and implementation of an expert system for computer process control (HESCPC). The complexity of the expertise necessary for computer process control applications requires that the expert system architecture be structured into a hierarchy of classes of specialized experts. The architecture of HESCPC integrates four classes of expert systems: operator/manager companion expert class, control system algorithm design expert class, hardware expert class, and software expert class. The paper is concerned with the design and implementation of the general system architecture, an operator adviser expert for a nuclear power plant and a control system designer expert using a state space feedback approach. Although the design and implementation aspects of all experts are discussed, the emphasis is on the latter.

At this stage of the HESCPC development, the declarative knowledge represented by 423 metarules and 1261 rules is distributed on a hierarchical structure among 20 experts on different levels of the hierarchy which are able to communicate among themselves to solve difficult control problems.

Examples of control system design sessions of linear mono and multivariable systems using feedback state space approach are given. A run time of an operator-adviser data-driven expert system for a nuclear plant is also presented.     

A CAPP expert system for rotational components

This paper is a new approach in developing a computer aided process planning expert system. A system model is designed and its competence is verified. The effort involved is limited to the manufacturing of rotational components using metal cutting operations, and generative process planning is chosen over variant-group technology-process planning. The process planning domain is analyzed in terms of the problem specifications and the knowledge characteristics. This analysis is used to classify the problem and the knowledge type according to the different expert system oriented classes. The model design is guided by tips provided for the different expert system classes, as well as relevant realizations from previous works, plus experimenting programming. A prototype system with a sample knowledge base is created as a result of this programming effort.