21,898 research outputs found

    Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

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    Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector

    A framework for developing engineering design ontologies within the aerospace industry

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    This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of four phases. The first phase defines the capture of knowledge required for the framework development, followed by the ontology framework development, iterative refinement of engineering ontologies and ontology validation through case studies and experts’ opinion. The ontology-based framework is applied in the combustor and casing aerospace engineering domain. The modular ontologies developed as a result of applying the framework and are used in a case study to restructure and improve the accessibility of information on a product design information-sharing platform. Additionally, domain experts within the aerospace industry validated the strengths, benefits and limitations of the framework. Due to the modular nature of the developed ontologies, they were also employed to support other project initiatives within the case study company such as role-based computing (RBC), IT modernisation activity and knowledge management implementation across the sponsoring organisation. The major benefit of this approach is in the reduction of man-hours required for maintaining engineering design ontologies. Furthermore, this approach strengthens reuse of ontology knowledge and encourages modularity in the design and development of engineering ontologies

    Knowledge formalization in experience feedback processes : an ontology-based approach

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    Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

    Innovation and Knowledge Management : using the combined approach TRIZ-CBR in Process System Engineering

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    In this article, a TRIZ based model is proposed to support the innovation and knowledge capitalization process. This model offers a knowledge base structure, which contains several heuristics to solve problems, synthesized from a large range of domains and industries and, also, the capacity to capture, store and make available the experiences produced while solving problems

    A Framework for Life Cycle Sustainability Assessment of Road Salt Used in Winter Maintenance Operations

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    It is important to assess from a holistic perspective the sustainability of road salt widely used in winter road maintenance (WRM) operations. The importance becomes increasingly apparent in light of competing priorities faced by roadway agencies, the need for collaborative decision-making, and growing concerns over the risks that road salt poses for motor vehicles, transportation infrastructure, and the natural environment. This project introduces the concept of Life Cycle Sustainability Assessment (LCSA), which combines Life Cycle Costing, Environmental Life Cycle Assessment, and Social Life Cycle Assessment. The combination captures the features of three pillars in sustainability: economic development, environmental preservation, and social progress. With this framework, it is possible to enable more informed and balanced decisions by considering the entire life cycle of road salt and accounting for the indirect impacts of applying road salt for snow and ice control. This project proposes a LCSA framework of road salt, which examines the three branches of LCSA, their relationships in the integrated framework, and the complexities and caveats in the LCSA. While this framework is a first step in the right direction, we envision that it will be improved and enriched by continued research and may serve as a template for the LCSA of other WRM products, technologies, and practices

    An Ontology for Product-Service Systems

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    Industries are transforming their business strategy from a product-centric to a more service-centric nature by bundling products and services into integrated solutions to enhance the relationship between their customers. Since Product- Service Systems design research is currently at a rudimentary stage, the development of a robust ontology for this area would be helpful. The advantages of a standardized ontology are that it could help researchers and practitioners to communicate their views without ambiguity and thus encourage the conception and implementation of useful methods and tools. In this paper, an initial structure of a PSS ontology from the design perspective is proposed and evaluated

    Enterprise modelling : building a product lifecycle (PLM) model as a component of the integrated vision of the enterprise

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    Enterprise modelling has proved to be an efficient tool to study organisations structure and facilitate decision making. The enterprise is a complex system that is required to use its processes to generate value in a given environment (concurrent, market, suppliers and humanity). We focus on three management disciplines: Product Lifecycle Management (PLM), Supply Chain Management (SCM) and Customer Relationship Management (CRM). These business processes are so intertwined that the enterprise has to concentrate on the three to attain its economic objectives. To enhance the development of PLM, SCM and CRM models, the enterprise needs to capitalise the knowledge necessary to adapt and apply modelling techniques. Knowledge Management (KM) is a key factor to give a unified enterprise vision. Firstly, we propose an integrated enterprise model depicting the interactions between PLM, SCM, CRM and KM models. But a state of the art showed that PLM models are scarce. Most of the PLM models found depends strongly on the particular case studied and can not be used with other enterprises. After defining the most important components of the PLM vision, we propose to organise these components into a formalised way. The study of SCM and CRM models proved to be helpful to structure these components. Finally the validation methodology that is to be established in our coming research works is not only to be used with the PLM model presented in this paper but with SCM and CRM models also.Product Lifecycle Management (PLM), Enterprise modelling, Enterprise systems

    Managing the KM Trade-Off: Knowledge Centralization versus Distribution

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    KM is more an archipelago of theories and practices rather than a monolithic approach. We propose a conceptual map that organizes some major approaches to KM according to their assumptions on the nature of knowledge. The paper introduces the two major views on knowledge ­objectivist, subjectivist - and explodes each of them into two major approaches to KM: knowledge as a market, and knowledge as intellectual capital (the objectivistic perspective); knowledge as mental models, and knowledge as practice (the subjectivist perspective). We argue that the dichotomy between objective and subjective approaches is intrinsic to KM within complex organizations, as each side of the dichotomy responds to different, and often conflicting, needs: on the one hand, the need to maximize the value of knowledge through its replication; on the other hand, the need to keep knowledge appropriate to an increasingly complex and changing environment. Moreover, as a proposal for a deeper discussion, such trade-off will be suggested as the origin of other relevant KM related trade-offs that will be listed. Managing these trade-offs will be proposed as a main challenge of KM
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