652 research outputs found

    On the decomposition of tabular knowledge systems.

    Get PDF
    Recently there has been a growing interest in the decomposition of knowledge based systems and decision tables. Much work in this area has adopted an informal approach. In this paper, we first formalize the notion of decomposition, and then we study some interesting classes of decompositions. The proposed classification can be used to formulate design goals to master the decomposition of large decision tables into smaller components. Importantly, carrying out a decomposition eliminates redundant information from the knowledge base, thereby taking away -right from the beginning- a possible source of inconsistency. This, in turn, renders subsequent verification and validation more smoothly.Knowledge; Systems;

    A tool-supported approach to inter-tabular verification.

    Get PDF
    The use of decision tables to verify KBS has been advocated several times in the V&V literature. However, one of the main drawbacks of those system is that they fail to detect anomalies which occur over rule chains. In a decision table based context this means that anomalies which occur due to interactions between tables are neglected. These anomalies are called inter-tabular anomalies. In this paper we investigate an approach that deals with inter-tabular anomalies. One of the prerequisites for the approach was that it could be used by the knowledge engineer during the development of the KBS. This requires that the anomaly check can be performed on-line. As a result, the approach partly uses heuristics where exhaustive checks would be too inefficient. All detection facilities that will be described, have been implemented in a table-based development tool called PROLOGA. The use of this tool will be briefly illustrated. In addition, some experiences in verifying large knowledge bases are discussed.

    Capture and Maintenance of Constraints in Engineering Design

    Get PDF
    The thesis investigates two domains, initially the kite domain and then part of a more demanding Rolls-Royce domain (jet engine design). Four main types of refinement rules that use the associated application conditions and domain ontology to support the maintenance of constraints are proposed. The refinement rules have been implemented in ConEditor and the extended system is known as ConEditor+. With the help of ConEditor+, the thesis demonstrates that an explicit representation of application conditions together with the corresponding constraints and the domain ontology can be used to detect inconsistencies, redundancy, subsumption and fusion, reduce the number of spurious inconsistencies and prevent the identification of inappropriate refinements of redundancy, subsumption and fusion between pairs of constraints.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Product Configuration with Bayesian Network

    Get PDF
    For the satisfaction of individual customer requirements, products with many options are offered in mass customization. However, in the area of ecommerce, the large number of possible product configurations can overwhelm the customer, as he or she is not supported by a human sales expert. To minimize the customer’s overload, this paper examines the combination of a knowledge-based product configurator with an upstream probabilistic recommender system to provide a quick, individual and dynamic initial orientation for the customer. The application of the approach is demonstrated using an example from engineering design

    A Survey of Languages for Specifying Dynamics: A Knowledge Engineering Perspective

    Get PDF
    A number of formal specification languages for knowledge-based systems has been developed. Characteristics for knowledge-based systems are a complex knowledge base and an inference engine which uses this knowledge to solve a given problem. Specification languages for knowledge-based systems have to cover both aspects. They have to provide the means to specify a complex and large amount of knowledge and they have to provide the means to specify the dynamic reasoning behavior of a knowledge-based system. We focus on the second aspect. For this purpose, we survey existing approaches for specifying dynamic behavior in related areas of research. In fact, we have taken approaches for the specification of information systems (Language for Conceptual Modeling and TROLL), approaches for the specification of database updates and logic programming (Transaction Logic and Dynamic Database Logic) and the generic specification framework of abstract state machine

    A Knowledge-Based Engineering System Framework for the Development of Electric Machines

    Get PDF
    The new concept industry 4.0 is a great opportunity to improve the competitiveness in a global market for small-medium size electric machinery companies. The demand for electric motors have increased in the last decade especially due to applications that try to make a full transition from fuel to electricity. These applications encounter the need for tailor-made motors that must meet demanding requirements. Therefore, it is mandatory small-medium companies adopt new technologies offering customized products fulfilling the customers’ requirements according to their investment capacity. Furthermore, simplify their development process as well as to reduce computational time to achieve a feasible design in shorter periods. In addition, find ways to retain know-how that is typically kept within each designer either to retrieve it or transfer it to new designers. To support the aforementioned issue, a knowledge-based engineering (KBE) system framework for the development of electric machines is devised. The framework is encapsulated in the so-called KBV2-model comprising the standardized macro-level framework for electrical machine and the knowledge base generation process. This thesis describes this model and the integration of KBE applications with current industrial technologies such as Model-Based Systems Engineering (MBSE), Product Lifecycle Management (PLM), multiphysics and analytical design tools. This architecture provides capability to manage and automate tasks in the development process of electric machines. The author of this work has opted to develop KBE applications following the minimum viable product principle. The KBE system framework herein presented is formalized through the experience and analysis of the development and implementation of the KBE applications. From which a guideline is provided following a sequential process in order to achieve a viable KBE system. To substantiate the process a KBE system is created that supports the development of electric motors for the elevator system industry

    Development of an additive manufacturing decision support system (AMDSS)

    Get PDF
    PhD ThesisAdditive manufacturing (AM) technology describes a set of processes capable of producing 3D physical products from CAD data directly. The rapid development of AM technologies and their wide applications makes the selection of the suitable process chains and materials a difficult task. Some researchers have tackled this problem by developing selectors that should assist users in their selections. The existing selector systems have some drawbacks: (і) often being outdated even before they were completely developed because new processes and materials are evolving continuously, (іі) representing only the point of view of their developers because users were not involved in the development process and (iii) not being holistic and able to help in all AM aspects for example process chains, materials, finishing methods and machines. This work has developed an updatable decision support system that assists users in their selections regarding AM process chains, materials, finishing methods, and machines. First, the study started by analyzing the available additive manufacturing selector systems and identifying their shortcomings. Secondly, the researcher identified target specifications for the new system, investigated different possible architectures for the system, selected knowledge based system (KBS) and database (DB) architecture to work together as a versatile tool that achieves the required target specifications. Next, the first version of the system was developed. Furthermore, verification and validation processes were made to test the developed system. Three case studies were used for the validation purpose: a typical consumer razor blade and two automotive components. These case studies were manufactured using AM technologies and then a comparison between real life decisions and the developed decision support system decisions were made. In addition, a number of interviews were performed in order to obtain users’ feedback about the first developed version. As a result of the feedback and evaluation a second version of the system was developed and evaluated. The results obtained from the second evaluation suggest that the second version is more effective than the first version during the selection process. To conclude, this study has shown that using KBS and DB together is effective to develop an updatable additive manufacturing decision support system. In addition, the user involvement in the development stage of the system enhances the system performance.The Arab Academy for Science & Technology & Maritime Transport

    A new knowledge sourcing framework to support knowledge-based engineering development

    Get PDF
    New trends in Knowledge-Based Engineering (KBE) highlight the need for decoupling the automation aspect from the knowledge management side of KBE. In this direction, some authors argue that KBE is capable of effectively capturing, retaining and reusing engineering knowledge. However, there are some limitations associated with some aspects of KBE that present a barrier to deliver the knowledge sourcing process requested by the industry. To overcome some of these limitations this research proposes a new methodology for efficient knowledge capture and effective management of the complete knowledge life cycle. Current knowledge capture procedures represent one of the main constraints limiting the wide use of KBE in the industry. This is due to the extraction of knowledge from experts in high cost knowledge capture sessions. To reduce the amount of time required from experts to extract relevant knowledge, this research uses Artificial Intelligence (AI) techniques capable of generating new knowledge from company assets. Moreover the research reported here proposes the integration of AI methods and experts increasing as a result the accuracy of the predictions and the reliability of using advanced reasoning tools. The proposed knowledge sourcing framework integrates two features: (i) use of advanced data mining tools and expert knowledge to create new knowledge from raw data, (ii) adoption of a well-established and reliable methodology to systematically capture, transfer and reuse engineering knowledge. The methodology proposed in this research is validated through the development and implementation of two case studies aiming at the optimisation of wing design concepts. The results obtained in both use cases proved the extended KBE capability for fast and effective knowledge sourcing. This evidence was provided by the experts working in the development of each of the case studies through the implementation of structured quantitative and qualitative analyses

    VODRE: Visualisation of drools rules execution

    Get PDF
    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
    corecore