Insights into enterprise conceptual modeling

Anaby-Tavor, Ateret; Amid, David; Fisher, Amit; Bercovici, Avivit; Ossher, Harold; Callery, Matthew; Desmond, Michael; Krasikov, Sophia; Simmonds, Ian

doi:10.1016/j.datak.2010.10.003

Cited by 20 publications

(18 citation statements)

References 12 publications

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“…International Journal of Production Research. 2016;54 (15):4430-4447. PhD in Industrial Engineering at the University of Seville.…”

Section: Discussionmentioning

confidence: 99%

“…2 It is also known that there is a close relationship between management control through performance indicators, defining strategies and decision making. 3,4 There are different methods for the design of efficiency and effectiveness measurement and control systems, and all of them agree with defining goals and performance criteria, [5][6][7] the importance of quality of reporting, [8][9][10][11] information systems with consolidated [12][13][14] and purged database, 15,16 and well-established processes for validating results. 17 Each one of these aspects, by itself, makes up a topic of analysis of the so-called performance measurement systems.…”

Section: Introductionmentioning

confidence: 99%

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Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

Viveros

Kristjanpoller

López-Campos

et al. 2018

Quality & Reliability Eng

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This article presents a graphical tool for the monitoring of performance indicators called GAOEM (Graphical Analysis for Overall Effectiveness Management). GAOEM comprehends the main indicators of maintenance and operations management, and it constitutes an adaptation of the overall effectiveness index. GAOEM facilitates control and analysis by using specific indicators in a graphic panel, designed for industries with high investment in physical assets. It also facilitates an efficient reading and interpreting of the data, enriching the analysis, the search for phenomena of interest and improvement opportunities to support the decision making. GAOEM requires 3 categories of input data, which are interventions data, time data, and production/process data. With this information, the basic performance indicators are calculated, being these indicators fundamental for the control and monitoring of the performance level. Later, these indicators will be the basis for calculation of both partial and total performance. GAOEM can be used as a diagnosis, analysis, control and monitoring tool for the indicators of interest at a strategic level, as well as a tool for searching of phenomena typical of a specific stage of the life cycle of assets and also of those conditions resulting from improper operation and/or maintenance, identifying their root causes.

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“…International Journal of Production Research. 2016;54 (15):4430-4447. PhD in Industrial Engineering at the University of Seville.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

Viveros

Kristjanpoller

López-Campos

et al. 2018

Quality & Reliability Eng

View full text Add to dashboard Cite

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“…EM has generated a large number of methods for supporting strategic decision‐making. Enterprise models can be classified into families according to common properties and underlying structures (Anaby‐Tavor et al, ): tables (matrices)—members of this group are composed of a composite object that has part‐whole hierarchies with column objects, which in turn have part‐whole hierarchies with row objects; graphs—all the members of this group comprise edges that connect pairs of nodes; trees—models in this family have an underlying connected acyclic graph with hierarchical structure; Cartesian coordinate systems—family members have static axes where points/shapes are positioned in a plane; layer diagrams—elements are placed one above another and may be semidetached; and onion maps—diagrams in the form of concentric circles sometimes with the addition of slices.…”

Section: Identified Source Fields Of the Modeling Methodsmentioning

confidence: 99%

Modeling methods for strategy formulation in a turbulent environment

et al. 2018

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The relevance of classical strategizing methods decreases in the era of a rapidly changing world, but this set of methods can be e panded through a variety of e ible modeling techni ues from other elds. Opera ons research, enterprise modeling, nowledge engineering, and ar cial intelligence have poten al to enrich strategizing process. These disciplines have generated a large number of suppor ng methods. We provide a classi ca on of the modeling methods by the degree of formaliza on and propose a conceptual framewor for the method choice.

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“…More specifically, enterprise models can be used to study the current state of an enterprise, analyse problems with regard to the current situation, sketch potential future scenarios, design future states of the enterprise, communicate with stakeholders, manage change, etc. ( (Davies et al, 2006), (Bubenko et al, 2010), (Anaby-Tavor et al, 2010)).…”

Section: Introductionmentioning

confidence: 99%

Challenges of Modelling LandscapesPragmatics Swept Under the Carpet?

Proper

Bjekovic

2013

Proceedings of the Third International Symposium on Proceedings of the Third International Symposium on Business Modeling and S

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In enterprise modelling, a wide range of models and languages is used to support different purposes. If left uncontrolled, this can easily result in a fragmented perspective on the enterprise, its processes and IT support. On its turn, this negatively affects traceability, the ability to do crosscutting analysis, and the overall coherence of models. Different strategies are suggested to achieve model integration. They mainly address syntactic-semantics aspects of models/languages, and only to a limited extent their pragmatics. In actual use, the 'standardising' and 'integrating' effects of traditional approaches (e.g. UML, ArchiMate) erodes. This is typically manifested by the emergence of local 'dialects', 'light weight versions', as well as extensions of the standard to cover 'missing aspects'. This paper aims to create more awareness of the factors that are at play when creating integrated modelling landscapes. Relying on our ongoing research, we develop a fundamental understanding of the driving forces and challenges related to modelling and linguitic variety within modelling landscapes. In particular, the paper discusses the effect of a priori fixed languages in modelling and model integration efforts, and argues that they bring about the risk of neglecting the pragmatic richness needed across practical modelling situations.

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Insights into enterprise conceptual modeling

Cited by 20 publications

References 12 publications

Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

Modeling methods for strategy formulation in a turbulent environment

Challenges of Modelling LandscapesPragmatics Swept Under the Carpet?

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