140,629 research outputs found

    Reference Modelling in Support of M&S—Foundations and Applications

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    Whether by design or by practice, systems engineering (SE) processes are used more and more often in Modeling and Simulation (M&S). While the two disciplines are very close, there are some differences that must be taken into account in order to successfully reuse practices from one community to another. In this paper, we introduce the M&S System Development Framework (MS-SDF) that unifies SE and M&S processes. The MS-SDF comprises the SE processes of requirements capture, conceptual modelling, and verification and validation (V&V), and extends them to M&S. We use model theory as a deductive apparatus in order to develop the MS-SDF. We discuss the benefits of the MS-SDF especially in the selection between federation development and multi-model approaches and the design of composable models and simulations. Lastly, a real life application example of the framework is provided

    Requirements modelling and formal analysis using graph operations

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    The increasing complexity of enterprise systems requires a more advanced analysis of the representation of services expected than is currently possible. Consequently, the specification stage, which could be facilitated by formal verification, becomes very important to the system life-cycle. This paper presents a formal modelling approach, which may be used in order to better represent the reality of the system and to verify the awaited or existing system’s properties, taking into account the environmental characteristics. For that, we firstly propose a formalization process based upon properties specification, and secondly we use Conceptual Graphs operations to develop reasoning mechanisms of verifying requirements statements. The graphic visualization of these reasoning enables us to correctly capture the system specifications by making it easier to determine if desired properties hold. It is applied to the field of Enterprise modelling

    A comparative study of multiple-criteria decision-making methods under stochastic inputs

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    This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

    Knowledge modelling with the open source tool myCBR

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    Building knowledge intensive Case-Based Reasoning applications requires tools that support this on-going process between domain experts and knowledge engineers. In this paper we will introduce how the open source tool myCBR 3 allows for flexible knowledge elicitation and formalisation form CBR and non CBR experts. We detail on myCBR 3 's versatile approach to similarity modelling and will give an overview of the Knowledge Engineering workbench, providing the tools for the modelling process. We underline our presentation with three case studies of knowledge modelling for technical diagnosis and recommendation systems using myCBR 3

    Construct redundancy in process modelling grammars: Improving the explanatory power of ontological analysis

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    Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature

    Continuous maintenance and the future – Foundations and technological challenges

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    High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

    Capability driven development: an approach to designing digital enterprises

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s12599-014-0362-0[EN] The need for organizations to operate in changing environments is addressed by proposing an approach that integrates organizational development with information system (IS) development taking into account changes in the application context of the solution. This is referred to as Capability Driven Development (CDD). A meta-model representing business and IS designs consisting of goals, key performance indicators, capabilities, context and capability delivery patterns, is being proposed. The use of the meta-model is validated in three industrial case studies as part of an ongoing collaboration project, whereas one case is presented in the paper. Issues related to the use of the CDD approach, namely, CDD methodology and tool support are also discussed.This work has been partially supported by the EU-FP7 funded project no: 611351 CaaS - Capability as a Service in Digital Enterprises.Berzisa, S.; Bravos, G.; Cardona Gonzalez, T.; Czubayko, U.; España, S.; Grabis, J.; Henkel, M.... (2015). Capability driven development: an approach to designing digital enterprises. Business and Information Systems Engineering. 57(1):15-25. https://doi.org/10.1007/s12599-014-0362-0S1525571ArchiMate (2013) An enterprise modeling language from the Open Group. http://www.opengroup.org/archimate/ . Accessed 3 Dec 2014Asadi M, Ramsin R (2008) MDA-based methodologies: an analytical survey. In: Proceedings Model driven architecture – foundations and applications (ECMDA-FA 2008), LNCS 5095, pp 419–431Barney JB (1991) Firm resources and sustained competitive advantage. 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