Design of knowledge-based expert systems for time-critical applications

In Memoriam: Dr. Clive L. Dym (1942–2016)

To date, knowledge-based systems ( KBS's) have been developed on an ad-hoc basis, without the benefit of quantitative tools for analysis and synthesis. If we are to approach the field of knowledge engineering systematically, we must develop performance measures to characterize the effectiveness and efficiency of knowledge systems, and thereby serve to highlight directions for improvement. When KBS's are applied to control tasks, real-time performance becomes critical. Consequently, the internal processes of knowledge-based control systems ( KBCS) must be optimized to fulfill real-time requirements. This article derives relationships between information attributes and system performance. The performance measures are applied to a knowledge-based design system ( KBDS) for the synthesis of KBCS. The performance measures reflect intuitively satisfying properties of the KBDS and provide insights into the system not possible through a straight orward inspection of the program code. This type of system can be use...

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

A coupled knowledge-based expert system for design of liquid-retaining structures

Knowledge-based Systems and Expert Systems, in particular, are expensive to build and difficult to validate and debug because of their complexity and dynamism. Therefore, it is not easy for knowledge engineer and domain expert to identify the gaps and mistakes in knowledge base. Unit testing is unable to cover validation process at all stages, in many cases manual thorough review of decision process is needed. In this paper we spot main approaches to validation and verification issue and describe a component that helps to debug a knowledge base by visualising execution of rules that derive a particular result. This component is developed for Knowledge-based Systems built on Drools Platform1 and we demonstrate application of this component in a knowledge-based engineering system for structural optical design.

A central problem for the design of knowledge-based systems is the so-called knowledge acquisition bottleneck. Knowledge acquisition is crucial for the quality and efficiency of a planned knowledge-based system. These systems are always based on one or several knowledge bases, whose contents are an influential quality factor for the system's result. For that reason, it is evident that a consistent approach to knowledge acquisition is of great importance. In relation to the problem domain the knowledge-based system is intended for, the knowledge acquisition can be highly problematic. While, for example, in technical problem domains, the access to expert knowledge can usually be achieved in an acceptable manner, the acquisition of medical knowledge for formalisation and usage in an information system is not possible without difficulty.

Response time satisfaction in a real-time knowledge-based system

Computer environments for design and designers

A knowledge-based expert system for roll pass and profile design for shape rolling of round and square bars

Design shells: A formalism for prototype refinement in knowledge-based design systems

Purpose – Guidelines for the design of knowledge-based e-learning usability systems are absent from the current recognized set of usability design heuristics and from an established evaluation methodology of e-learning system developments. Such systems can help Web designers and instructional designers design for different user needs and decide which properties are of a higher priority, thus meriting more design and development efforts. The authors aim to help students develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge. Design/methodology/approach – The authors applied Merrill ' s first principles of instruction and usability properties as pedagogical and usability design guidelines, knowledge management (KM) and hierarchical task analysis as methodological knowledge bases. The authors proposed a KM e-learning usability framework which frames our mapping of Web usability attributes to e-learning usability properties. The authors aim to investigate whether adopting Merrill ' s first principles of instruction and usability properties as knowledge-based guidelines/design factors would help learners develop higher-order thinking skills and whether this design would result in positive technology acceptance. The authors also developed a method matrix to map the selected methods of cognitive engineering to its potential uses in the KM e-learning usability framework of this paper and mapped e-learning usability tools with components in the KM e-learning usability system. Findings – Findings indicated that our design effectively helped learners to demonstrate higher-order thinking skills and positive technology acceptance, promising indications toward the design and development of knowledge-based usability frameworks and systems. Research/limitations/implications – The sample size of this paper is small. Hence, conclusions are not generalizable at this moment. Originality/Value – The authors’ contributions are twofold: First, the authors proposed a KM e-learning usability framework, which frames the mapping of KM processes to e-learning principles and usability properties. Second, the authors proposed a method matrix which maps the selected methods of cognitive engineering to its potential uses in their KM e-learning usability framework. Based on these mappings and focusing on the usability properties navigation and learning support, the authors used ICT/Web2.0 tools to present/visualize information more clearly and more sensibly/manageably to students, to help trigger new knowledge and develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge and articulate information from different perspectives throughout the KM life cycle.

The authors review and categorize the research in applications of artificial intelligence (AI) and expert systems (ES) in new product development (NPD) activities. A brief overview of NPD process and AI is presented. This is followed by a literature survey in regard to AI and ES applications in NPD, which revealed twenty four articles (twenty two applications) in the 1990–1997 period. The applications are categorized into five areas: expert decision support systems for NPD project evaluation, knowledge-based systems (KBS) for product and process design, KBS for QFD, AI support for conceptual design and AI support for group decision making in concurrent engineering. Brief review of each application is provided. The articles are also grouped by NPD stages and seven NPD core elements (competencies and abilities). Further research areas are pointed out.

Knowledge-based turbomachinery design system via a deep neural network and multi-output Gaussian process

The Internet and World Wide Web (WWW) are now evolving as an important communication technology and a major information resource provider for industry. This paper discusses the development and implementation of a knowledge-based gear design and manufacturing system over the Internet to create new integrated design and manufacturing environments. By providing access to an interactive web-based support system, any designer with a WWW browser becomes a potential user of this on-line design system. Once connected, the designer follows the system instructions and submits the necessary input data on the appropriate web pages. The server receives a request from a client and invokes a CGI (Common Gateway Interface) program that processes the information provided through the user Interface. The CGI parses the data and has the ability to remotely run the knowledge-based gear design system that integrates knowledge about all aspects of gear design and manufacturing and provides powerful reasoning and decision-making capabilities for reducing the time between gear tooth creation, detailed design and manufacturing process specification via the Internet. When the execution is completed, full specifications definition, geometry, kinematic-loads and stresses are determined through Finite Element Analysis (FEA) within ANSYS, VRML models of the gear pair and gearbox assembly including gears, shafts, bearings and housing are exported according to the designer requests and sent back to designer on the web browser. To accomplish this, a combination of HTML, JavaScript, VRML, CGI Script and C++ is used. Finally, an example on spur gear design utilizing a parallel gearbox design model configuration is discussed.

At the time being knowledge-based systems are used in almost all life aspects. The main reason for trying to use knowledge-based systems in real-time control is to reduce cognitive load on users (overload), their application proving to be important when conventional techniques have failed or are not sufficiently effective [1]. The development of automated diagnosis techniques and systems can help also to minimize downtime and maintain efficient output. This paper presents some issues of applying knowledge-based systems to real-time control systems. It describes and analyzes the main issues concerning the real-time domain and provides possible solutions, such as a set of requirements that a real-time knowledge-based system must satisfy. The paper proposes a possible architecture for applying knowledge-based techniques in real-time control systems. Finally, a way of employing knowledge-based techniques for extending the existing automatic control and monitoring system for the geothermal plant from the University of Oradea is presented.