Validation of highly reliable, real-time knowledge-based systems

Knowledge-based systems have the potential to greatly increase the capabilities of future aircraft and spacecraft and to significantly reduce support manpower needed for the space station and other space missions. However, a credible validation methodology must be developed before knowledge-based systems can be used for life- or mission-critical applications. Experience with conventional software has shown that the use of good software engineering techniques and static analysis tools can greatly reduce the time needed for testing and simulation of a system. Since exhaustive testing is infeasible, reliability must be built into the software during the design and implementation phases. Unfortunately, many of the software engineering techniques and tools used for conventional software are of little use in the development of knowledge-based systems. Therefore, research at Langley is focused on developing a set of guidelines, methods, and prototype validation tools for building highly reliable, knowledge-based systems. The use of a comprehensive methodology for building highly reliable, knowledge-based systems should significantly decrease the time needed for testing and simulation. A proven record of delivering reliable systems at the beginning of the highly visible testing and simulation phases is crucial to the acceptance of knowledge-based systems in critical applications

The role of functional prototyping within the KADS methodology : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

Knowledge-based systems have until recent times lacked a clear and complete methodology for their construction. KADS was the result of the early 1980's project (ESPRIT-I P1098) which had the aim of developing a comprehensive, commercially viable methodology for knowledge-based system construction. KADS has subsequently proved to be one of the more popular approaches, focusing on the modelling approach to knowledge based system development. One area of the KADS methodology that has not been examined to any great depth is that of model validation. Model validation is the process of ensuring that a derived model is an accurate representation of the domain from which it has been derived from. The two approaches which have been suggested for this purpose within the KADS framework are that of protocol analysis and functional prototyping. This project seeks to apply the second of these choices, that of functional prototyping, to the model of expertise created by da Silva (1994) for model validation purposes. The problem domain is that of farm management, under an joint program of research between the Computer Science, Information Systems and Agricultural Management departments of Massey University. The project took the model of expertise and created a knowledge representation model in compliance with the selected object-oriented paradigm. After this the creation of a functional prototype in a Microsoft Windows based PC environment took place, using Kappa-PC as the application development tool. The validation took place through a demonstration session to a number of domain experts. Conclusions drawn from the experience gained through the creation and use of the prototype are presented, outlining the reasons why functional prototyping was deemed to be an appropriate method for model validation

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Acquiring Systems Knowledge with GOOI (Graphical Object-Oriented Interfaces)

Information system development, in particular expert systems and other knowledge-based approaches, require extensive human expert knowledge. Often, acquiring such knowledge is problematic with regard to efficiently acquiring the expert’s knowledge and translating this knowledge into a system usable form. Knowledge acquisition has long been viewed as the bottleneck of knowledge-based systems and more recently is being recognized as a significant issue in general information systems analysis and design. Object-oriented techniques are presented as a uniform method for overcoming translation difficulties and implementing graphical interfaces. A graphical interface provides a modeling platform that is easily understood by experts and knowledge engineers. The object-oriented base for our tool provides an additional benefit in developing implemented systems by providing a representation independent methodology that can easily be mapped into any other object-oriented based expert system or other object-oriented information systems

Requirement driven knowledge management system design to support automotive product development

Nowadays, New Product Development (NPD) has become a business priority in manufacturing companies due to international competition in terms of meeting higher and changing customer requirements, generating high profit at low cost, and maintaining sustainable development and growth. Through literature review and industrial investigations, it has been recognised that NPD is an information and knowledge intensive process. However, in current practice, enterprise knowledge is not properly managed or easily accessible. Many service providers have not followed the good practice of considering business objectives and end users’ requirements as main drivers of knowledge management system development and implementation. This doctoral thesis presents a methodology for the design and development of Knowledge Management (KM) systems to support NPD based on Enterprise Architecture Frameworks (EAFs). The project focuses on IT system specifications generation driven by business and knowledge users’ requirements in the automotive industry. Current EAFs have been developed by researchers and practitioners to help enterprises to design their information systems based on business objectives and user requirements. However, these frameworks are mainly proposed to manage information and data such as finances, resources, management and engineering documents, not for the increasingly important enterprise knowledge, especially tacit and unstructured knowledge. This project aims to extend the capabilities of the latest enterprise architecture frameworks so that not only data and information, but also enterprise knowledge can be managed. A guideline in the form of a flowchart has been developed, which provides a process that can be followed and used by system developers and implementation. The extended EAF has been implemented as easy-to-use folders for the development of a structured knowledge base. A case study in an automotive company proved that the methodology can be used to produce the functional specifications of their IT systems to include knowledge management capability. The system specification can then be used, either to assess a company’s existing information systems and direct its future system development and implementation; or to develop/implement a complete new information system from scratch

Knowledge-based assistance in costing the space station DMS

The Software Cost Engineering (SCE) methodology developed over the last two decades at IBM Systems Integration Division (SID) in Houston is utilized to cost the NASA Space Station Data Management System (DMS). An ongoing project to capture this methodology, which is built on a foundation of experiences and lessons learned, has resulted in the development of an internal-use-only, PC-based prototype that integrates algorithmic tools with knowledge-based decision support assistants. This prototype Software Cost Engineering Automation Tool (SCEAT) is being employed to assist in the DMS costing exercises. At the same time, DMS costing serves as a forcing function and provides a platform for the continuing, iterative development, calibration, and validation and verification of SCEAT. The data that forms the cost engineering database is derived from more than 15 years of development of NASA Space Shuttle software, ranging from low criticality, low complexity support tools to highly complex and highly critical onboard software

Advanced piloted aircraft flight control system design methodology. Volume 2: The FCX flight control design expert system

The development of a comprehensive and electric methodology for conceptual and preliminary design of flight control systems is presented and illustrated. The methodology is focused on the design states starting with the layout of system requirements and ending when some viable competing system architectures (feedback control structures) are defined. The approach is centered on the human pilot and the aircraft as both the sources of, and the keys to the solution of, many flight control problems. The methodology relies heavily on computational procedures which are highly interactive with the design engineer. To maximize effectiveness, these techniques, as selected and modified to be used together in the methodology, form a cadre of computational tools specifically tailored for integrated flight control system preliminary design purposes. The FCX expert system as presently developed is only a limited prototype capable of supporting basic lateral-directional FCS design activities related to the design example used. FCX presently supports design of only one FCS architecture (yaw damper plus roll damper) and the rules are largely focused on Class IV (highly maneuverable) aircraft. Despite this limited scope, the major elements which appear necessary for application of knowledge-based software concepts to flight control design were assembled and thus FCX represents a prototype which can be tested, critiqued and evolved in an ongoing process of development

Knowledge Organization and Inference Engine for the WVU Face Decision Support System

The knowledge-based organization for the West Virginia University Face Decision Support System is given, along with the initial development of the associated inference engine. The knowledge base contains generic knowledge about underground coal mines that utilize continuous miners. A typical knowledge entry is given, and the inference engine methodology is explained. The engine utilizes this knowledge with data from monitoring systems and from interaction with the section foreman, to assist in making section management decisions and plans

Capture Knowledge with Object-Process Modeling - a systems engineering approach

To increase the efficiency of the product development process at Volvo Car Group, knowledge accumulation is central in the early strategy and concept phase. Within the department for Research and Development, the unit responsible for powertrain engineering desires a process to document system interfaces, in order to reuse what they do already know in new applications. This thesis presents a process how to capture systems knowledge; i.e. interactions within system structure, functions and behavior with the use of object-process oriented modeling. Included in the process is also ideas presented how to manage and maintain as well as interpret and reuse captured knowledge. During the first part of the project, literature of theory and previous empiric was explored, in order to understand principles of knowledge based development and systems engineering. To identify needs of the desired process, system engineers responsible for the complete powertrain were interviewed. Thereafter, the interpreted needs were translated to a functional analysis of the desired process. A case study was conducted at different developing units across Powertrain Engineering. The purpose was to map system knowledge with object-process methodology. The result was a mapped system architecture based on the vehicle response attribute, where captured system knowledge is connected to the development phases as well as the system responsible. The object-process oriented model of the system architecture included qualitative traceability between system requirements, decomposed functions, product structure with physical interface as well as resources defining who is owner of the system knowledge. To illustrate how to interpret and make the captured system knowledge reusable, structural relations within three systems was mapped in a domain mapping matrix, which is a matrix mapping the dependencies between two data types. In this case requirements and functions, as well as functions and hardware components