Design of expert systems for integrated production automation

An approach to the design of expert systems for integrated production automation is presented. The major components in an integrated manufacturing system consist of corporate planning, marketing planning, research and development, engineering design, production planning, manufacturing, warehousing, and product distribution. These components are linked by management information flow, technology information flow, as well as materials flow. An intelligent computer is used to integrate information flow and to control materials flow. This paper discusses characteristics of the future factory, elements of knowledge based systems, and the design of computer based expert systems for production planning, for engineering design, and for integrated manufacturing.     

Expert systems and forecasting

Many business organizations are using expert systems for their business decisions. An expert system is a computer program that applies the knowledge of an expert to problem-solving. Forecasting is one of the quantitative tools businesses use for planning and decision-making. However, many business executives are not equipped to use the appropriate forecasting techniques. An expert system could be easily developed to help executives in forecasting.     

XML-Based Modeling of Corporate Memory

Analytical knowledge is distributed among domain experts, analysts, and data-storage systems. Extracting such knowledge from databases is of interest to corporations. The traditional top-down development of corporate memory is not appropriate for modern organizations because of the distributed nature of information. This paper proposes models of analytical knowledge and new ways of developing corporate memory by using an extensible markup language (XML). It aims at efficient exploration of useful knowledge by mining the Web. The proposed approach of modeling analytical knowledge is explicit and sharable. The concepts introduced in the paper have been demonstrated with a manufacturing case study.     

Integrated knowledge-based Petri net intelligent flexible assembly planning

Automatic assembly planning is recognized as an important tool for reducing manufacturing costs in concurrent product and process development. A novel knowledge-based Petri net (KBPN) is defined, based on the incorporation of expert systems into the usual Petri nets, and used for a unified assembly knowledge representation scheme. A KBPN-approach integrated with a sequence generation algorithm is proposed for the modeling, planning, simulation, analysis and evaluation of the flexible assembly system (FAS). The developed KBPN-based assembly planning system (KAPS) can automatically adjust the deviations between the theoretical planning parameters and the process parameters of real assembly operations to guarantee the best strategies and plans (sequences) for flexible assembly. The research findings are exemplified with a simple assembly to show the effectiveness of the method.     

AVERTING DEVELOPMENT PROBLEMS

A survey of 83 knowledge engineers reveals that most potential problems in expert systems development occur during the planning phase. Furthermore, such factors as the knowledge engineers' experience and the length of development time can amplify some of these problems. This article offers suggestions as to how knowledge engineers can improve their ability to avoid major development pitfalls and encourages IS managers to focus on financial commitment and long-term planning for expert systems projects.     

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.     

On making expert systems more like experts

Abstract: Expert systems still lack the skill of an expert when it comes to providing explanations of the results of expert reasoning. This is because while such systems may implement knowledge which is sufficient to mimic the performance of an expert, they do not necessarily model the expertise upon which that performance is based. Such a model must include knowledge of that domain's terminology, knowledge of domain facts, and knowledge of problem-solving methods. The Explainable Expert Systems project has been exploring a new paradigm for expert system development that is intended to capture such missing knowledge and make it available for explanation. This paper will discuss the principles behind this paradigm and consider two systems that employ it.     

Knowledge acquisition and integration tools aiming to support managerial planning in Greek SMEs

Most existing expert systems are defined in structured task domains. However, many real-life decision tasks are novel, unstructured and consequential. To support these tasks, expert systems are needed which provide an integrated environment capable of capturing new knowledge by updating the existing knowledge base. This paper describes the incremental development process of an expert system, from the initial gathering of data up to the development of knowledge acquisition tools and knowledge integration methodologies. The expert system developed addresses managerial planning tasks of Greek small-to-medium sized enterprises (SMEs). The manager sets values for parameters specifying environmental and company characteristics. The expert system responds with suggestions on feasible tactics, objectives and strategies. To cope with the changes of planning situations and also to improve the integrity of the knowledge base as the manager gains experience, knowledge acquisition tools have been introduced. These knowledge acquisition tools, which are manipulated directly by the manager, provide the system with additional knowledge and validate the knowledge already embedded in the knowledge base.     

HypEs: an architecture for hypermedia-enabled expert systems

Expert systems and hypermedia constitute two important technologies for organizations to create, store, and manage information products. The purpose of our research is to develop an architectural blueprint for the construction of hypermedia-enabled expert systems. We propose an architecture termed HypEs (Hypermedia-enabled Expert System) for the development of media-rich expert systems. The integration of hypermedia technologies and expert systems can provide significant potential benefits by enabling the storage and manipulation of non-textual knowledge, enhancing the effectiveness of both knowledge acquisition from the sources of expertise and knowledge transfer to non-expert users. An experimental analysis that contrasts the hypermedia-enabled and text-restricted expert systems provides results that underscore the usefulness of hypermedia techniques in enhancing the effectiveness of expert systems in practical applications.     

Seeding, Evolutionary Growth and Reseeding: Constructing, Capturing and Evolving Knowledge in Domain-Oriented Design Environments

We live in a world characterized by evolution—that is, by ongoing processes of development, formation, and growth in both natural and human-created systems. Biology tells us that complex, natural systems are not created all at once but must instead evolve over time. We are becoming increasingly aware that evolutionary processes are ubiquitous and critical for technological innovations as well. This is particularly true for complex software systems because these systems do not necessarily exist in a technological context alone but instead are embedded within dynamic human organizations.The Center for LifeLong Learning and Design (L3D) at the University of Colorado has been involved in research on software design and other design domains for more than a decade. We understand software design as an evolutionary process in which system requirements and functionality are determined through an iterative process of collaboration among multiple stakeholders, rather than being completely specified before system development occurs. Our research focuses on the following claims about software systems embedded within dynamic human organizations: (1) they must evolve because they cannot be completely designed prior to use, (2) they must evolve to some extent at the hands of the users, and (3) they must be designed for evolution.Our theoretical work builds upon our existing knowledge of design processes and focuses on a software process model and architecture specifically for systems that must evolve. Our theories are instantiated and assessed through the development and evolution of domain-oriented design environments (DODEs)—software systems that support design activities within particular domains and that are built specifically to evolve.     

The role of expertise research and human factors in capturing, explaining, and producing superior performance

OBJECTIVES: The goal of this article is to identify some of the major trends and findings in expertise research and their connections to human factors. BACKGROUND: Progress in the study of superior human performance has come from improved methods of measuring expertise and the development of better tools for revealing the mechanisms that support expert performance, such as protocol analysis and eye tracking. METHODS: We review some of the challenges of capturing superior human performance in the laboratory and the means by which the expert performance approach may overcome such challenges. We then discuss applications of the expert performance approach to a handful of domains that have long been of interest to human factors researchers. RESULTS: Experts depend heavily on domain-specific knowledge for superior performance, and such knowledge enables the expert to anticipate and prepare for future actions more efficiently. Training programs designed to focus learners' attention on task-related knowledge and skills critical to expert performance have shown promise in facilitating skill acquisition among nonexperts and in reducing errors by experts on representative tasks. CONCLUSIONS: Although significant challenges remain, there is encouraging progress in domains such as sports, aviation, and medicine in understanding some of the mechanisms underlying human expertise and in structuring training and tools to improve skilled performance. APPLICATIONS: Knowledge engineering techniques can capture expert knowledge and preserve it for organizations and for the development of expert systems. Understanding the mechanisms that underlie expert performance may provide insights into the structuring of better training programs for improvingskill and in designing systems to support professional expertise.     

ICADS: Intelligent Car Audio Design System for product planning

This paper describes the development of a system, ICADS (Intelligent Car Audio Design System), that can be used to effectively support product development engineers in car audio product design. We have demonstrated the use of expert system technology and the technique of quality function deployment (QFD) in supporting car audio design planning. QFD is applied as a knowledge acquisition method in this study to support car audio design teams in the development of products in a structured way that relates market demand via engineering specifications to parts specifications. We believe that other industries can use a similar approach for developing an expert system that can support product design planning.     

Praxiserfahrungen bei der Einführung dezentraler Wissensmanagement-Lösungen

Efficient management of knowledge is a major success factor for corporations and organizations. Many corporations have started Knowledge Management initiatives with the goal to actively manage knowledge creation and flow. Apart from the necessary organizational changes they have tried to support the quest for knowledge with Knowledge-Management systems. Peer-to-peer systems offer a cost-efficient, user-friendly alternative to server-based knowledge management solutions. However, due to various reasons they have not gained significant market share. During our sales activities for Dinow, our distributed knowledge management system, we have encountered various reasons for the slow adoption of this promising technology. In addition to technological concerns, e.g. regarding security, we have found that psychological factors are very significant: the possibility of “free” information flow contradicts the rigid frameworks, policies, and procedures in most organizations. It is a common misconception that currently used technology, i.e. e-mail, protects against such unwanted information flow.     

An expert system for wide area network component configuration

Abstract: Many organizations today have an interest in communications networks, either as users of public networks or as operators of their own private networks. Thus, the management of communications networks has become an important issue in the communications industry. The network design task is fundamental to the whole notion of network management; however, with the rapid rate of change in network technology and the emergence of highly sophisticated network users, network design has become an increasingly complex problem.
The purpose of this paper is to describe a development effort which incorporates expert systems techniques to treat one aspect of the network design problem—the initial planning and design of a network prior to implementation. The research effort was concerned with developing an expert system for Amdahl Communications Products which could be used by sales engineers in designing wide area networks to meet specified customer requirements. The system treats both the topological design problem and the component configuration problem.     

Model-based remotely-sensed imagery interpretation

Abstract

We present a model-based remotely-sensed image interpretation expert system embeded in a knowledge-based geographic information system (K. BIS). The KBIS consists of four sub-systems: a pictorial data base system, an image interpretation expert system, a computer-aided planning system and a computer-aided cartographic system. The image interpretation expert system represents ecological knowledge and other expert knowledge by frames. Its reasoning process consists of a forward reasoning based on the Bayes classification of Landsat imagery, a backward reasoning using frame knowledge and reasoning using a spatial consistency model. A forest inventory study was conducted in Shaxian county, in the southern part of China, using this expert system. The results have shown a significant improvement. Building image interpretation expert systems within knowledge-based pictorial systems is very convenient and efficient because there are well-organized data, knowledge and procedures available.     

The design process of expert systems development: some concerns

Abstract: A discussion is presented of why some expert systems that organizations have developed are not successful. The concept of design process plays a very significant role at the outset of the expert system development process. This concept has not been the subject of much debate and attention in expert systems development. From the author's point of view, one of the main issues is how the designer (knowledge engineer) thinks about the design process. In general, the designer's process is influenced by the knowledge engineer's conception. This paper endeavors to disclose some of the main factors related to the knowledge engineer's conception of the design process and an attempt is made to put forward a conceptual model of the expert system design process. This conceptual model is an initial step towards a successful implementation of expert system projects.     

The development of a knowledge-based system for information systems project development consulting

The foundation for a successful software development project is a well-conceived project plan which establishes the overall framework for effective project management. Two major functions of planning an information systems development project are: 1) the selection of an appropriate development strategy; and 2) the assessment of risk associated with the development of the system. This paper describes the development of a knowledge-based expert system to assist in choosing the most appropriate development approach to use when planning an information systems development project and when assessing the risk associated with that project. The knowledge base consists of a set of rules addressing both tasks. Case examples of the use of the expert system are also given.