Hierarchical skeletal plan refinement : task- and inference structures

This paper presents the task- and inference structure for skeletal plan refinement which was developed for lathe production planning, the application domain of the ARC-TEC project. Two inference structures are discussed: a global inference structure which was developed in the first phase of knowledge acquisition and a more detailed inference structure which builds on the hierarchical organization of the skeletal plans. The described models are evaluated with respect to their cognitive adequacy and their scope of application. The benefits and limitations of the KADS knowledge acquisition methodology are discussed with respect to the development of the two models

Clamping, COKAM, KADS, and OMOS : the construction and operationalization of a KADS conceptual model

For a simplified version of the clamping tool selection problem in mechanical engineering, the knowledge acquisition tool COKAM is applied to obtain an informal knowledge base and explanation structures from technical documents and previously solved cases. The output of COKAM is used to construct a three layered KADS conceptual model, which is then transformed into an operational model in the language OMOS. The OMOS formalization allows to verify the informal KADS conceptual model and to check the completeness of the domain knowledge. The results of this analysis are utilized in the next knowledge elicitation session with COKAM

Integrated knowledge acquisition from text, previously solved cases, and expert memories

Within the model-based knowledge engineering framework, an integrated knowledge acquisition method was developed for a complex real-world domain with different traces of expertise. By having an expert constructively explain the previously solved cases with more general information from other traces of expertise (text, expert memories) a model-centered knowledge base is constructed. The proposed method allows for an early knowledge verification where the relevance, sufficiency, redundancy, and consistency of knowledge are already assessed at an informal level. The early knowledge verification efficiently prepares the consecutive knowledge formalization. Through a cognitively adequate model of expertise and the explanation-oriented knowledge elicitation procedures, user friendly second generation expert systems may be developed

Integrated knowledge acquisition for lathe production planning : a picture gallery

Diese Bildergalerie veranschaulicht den Einsatz der im ARC-TEC Projekt entwickelten integrativen Wissensakquisitionsmethode. Geleitet durch ein Modell der Expertise, wird das Wissen zur Fertigungsplanung für Drehteile aus Texten, Fallsammlungen und Expertenurteilen akquiriert. Drei aufeinander abgestimmte Tools unterstützen die Erhebung, Dokumentation, Überprüfung und Formalisierung des relevanten Wissens.This picture gallery illustrates the application of the integrated knowledge acquisition procedure which was developed in the ARC-TEC project. Guided by a model of expertise, the knowledge for lathe production planning is acquired from texts, previously solved cases, and expert memories. Three coordinated tools support the elicitation, documentation, verification and formalization of the relevant knowledge

Using integrated knowledge acquisition to prepare sophisticated expert plans for their re-use in novel situations

Plans which were constructed by human experts and have been repeatedly executed to the complete satisfaction of some customer in a complex real world domain contain very valuable planning knowledge. In order to make this compiled knowledge re-usable for novel situations, a specific integrated knowledge acquisition method has been developed: First, a domain theory is established from documentation materials or texts, which is then used as the foundation for explaining how the plan achieves the planning goal. Secondly, hierarchically structured problem class definitions are obtained from the practitioners\u27 highlevel problem conceptualizations. The descriptions of these problem classes also provide operationality criteria for the various levels in the hierarchy. A skeletal plan is then constructed for each problem class with an explanation-based learning procedure. These skeletal plans consist of a sequence of general plan elements, so that each plan element can be independently refined. The skeletal plan thus accounts for the interactions between the various concrete operations of the plan at a general level. The complexity of the planning problem is thereby factored in a domain-specific way and the compiled knowledge of sophisticated expert plans can be re-used in novel situations

Integrated knowledge utilization and evolution for the conservation of corporate know-how

Insufficient consideration of knowledge evolution is a frequent cause for the failure of knowledge-based systems (KBSs) in industrial practice. Corporate know-how about the design and manufacturing of a particular product is subject to rather rapid changes, and it is hard to specify in advance exactly what information will be requested by various users. Keeping a KBS for the conservation of corporate know-how up-to-date or even enhancing its utility, thus requires the continuous monitoring of its performance, noting deficiencies, and suggestions for improvements. In the current paper, we discuss different ways in which information collected during knowledge utilization can be exploited for system evolution. We present structure-based rule and concept editors which allow for an immediate integration and formalization of new information, even by rather inexperienced users. A prototypical knowledge conservation system for crankshaft design which was developed in cooperation between the DFKI and a German company is used to illustrate and evaluate our approach

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Conserving corporate knowledge for crankshaft design

A company's technical know-how which constitutes one of its most important assets often exists only in the heads of a small number of human experts. This limits the availability of this crucial resource and puts considerable strain on the respective experts. In cooperation with a German company^1 which produces motor-powered tools and vehicles a prototypical knowledge conservation system was developed which captures an individual expert's know-how about the design of crankshafts and makes it available to the whole design team. The knowledge-based system provides explanations of previous designs and supports unexperienced designers by suggesting viable alternatives. By checking the consistency between new cases and previously stated general design constraints, the system supports a continuous evolution of the stored knowledge which thus always reflects the current state of a company's technical know-how

Reconstructive integrated explanation of lathe production plans

A Reconstructive Explanation tool has been developed and implemented within an integrated knowledge acquisition framework. This tool (RIETO) employs both a formal and an informal knowledge base to construct explanations for individual lathe production plans. RIETO adopts a reconstructive explanation approach [WickThompson92] which does not rely on the problem solving trace constructed by the inference component of the system. Instead it reconstructs possible lines of reasoning which may provide justifications for those aspects of the solution which are questioned by the user. The explanation tool can thus bring to bear all pertinent information which was captured during knowledge acquisition, even if it was not used for actually solving the problem. RIETO can answer "why?" and "why not?" questions about different aspects of the production plan, can give justifications for rules and provide all information about a particular topic (e.g. the selection of cutting materials) which is pertinent to the context in which the question is asked by the user

Techniques for organizational memory information systems

The KnowMore project aims at providing active support to humans working on knowledge-intensive tasks. To this end the knowledge available in the modeled business processes or their incarnations in specific workflows shall be used to improve information handling. We present a representation formalism for knowledge-intensive tasks and the specification of its object-oriented realization. An operational semantics is sketched by specifying the basic functionality of the Knowledge Agent which works on the knowledge intensive task representation. The Knowledge Agent uses a meta-level description of all information sources available in the Organizational Memory. We discuss the main dimensions that such a description scheme must be designed along, namely information content, structure, and context. On top of relational database management systems, we basically realize deductive object- oriented modeling with a comfortable annotation facility. The concrete knowledge descriptions are obtained by configuring the generic formalism with ontologies which describe the required modeling dimensions. To support the access to documents, data, and formal knowledge in an Organizational Memory an integrated domain ontology and thesaurus is proposed which can be constructed semi-automatically by combining document-analysis and knowledge engineering methods. Thereby the costs for up-front knowledge engineering and the need to consult domain experts can be considerably reduced. We present an automatic thesaurus generation tool and show how it can be applied to build and enhance an integrated ontology /thesaurus. A first evaluation shows that the proposed method does indeed facilitate knowledge acquisition and maintenance of an organizational memory