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Enterprise system of systems
Published in Mo Jamshidi, Systems of Systems Engineering, 2017
Enterprise engineering is a multidisciplinary approach that encompasses, balances, and synthesizes technical and nontechnical (political, economic, organizational, operational, social, and cultural) aspects of an enterprise capability.
A methodology to create a sensing, smart and sustainable manufacturing enterprise
Published in International Journal of Production Research, 2018
Dante Chavarría-Barrientos, Rafael Batres, Paul K. Wright, Arturo Molina
The Enterprise Engineering (EE) discipline aims to provide a systematic approach for designing enterprises (Kosanke, Vernadat, and Zelm 1999). The EE discipline involves the use of models that help in the analysis of existing systems and the design of high-level integrated solutions. Such a discipline also encompasses the use of modelling languages and tools to represent the requirements and solutions. To facilitate EE, Enterprise Architectures (EAs) have been proposed to guide and facilitate the design of integrated enterprises with a special focus on information system issues. Representative examples are the Zachman framework, PERA (Williams, Rathwell, and Li 1996), CIMOSA (AMICE ESPRIT Consortium 1993), ARIS (Scheer 1994) and GRAI Integrated Methodology (Doumeingts et al. 1992), which have been successfully mapped against the GERAM framework (Noran 2003). These EAs define the concepts to define enterprise systems that are consistent and easy to integrate. However, these EAs do not deal with the representation of how enterprises are effectively structured and operated (Chen, Doumeingts, and Vernadat 2008).
Algebra for Enterprise Ontology: towards analysis and synthesis of enterprise models
Published in Enterprise Information Systems, 2018
Enterprises are confronting greatly tumultuous environments with complexity, uncertainty, and dynamism. In such a context, the concept of the agility of enterprises is regarded as a key issue for success. Organizations are required to become more agile, more adaptive, and more transparent to be able to adapt rapidly and efficiently to environmental changes (Tsourveloudis and Valavanis 2002). Enterprise agility (or organizational agility) is the capability of an enterprise to sense changes in the environment and to respond efficiently and effectively to those changes. The latter is supported by better (re)design and (re)engineering of business processes and the distribution of roles and responsibilities in enterprises. Business processes have historically been well studied in the frame of business process management (BPM) with business process modeling. However, BPM has serious limitations in designing roles and responsibilities in enterprises from the perspective of systems engineering. Instead, Enterprise Engineering (EE) is an emerging research discipline that pursues better understanding and implementations from the perspective of engineering (Dietz et al. 2013). Although the scope of the emerging EE discipline includes a broader set of approaches as contextualized in (de Vries, van der Merwe, and Gerber 2015), the three major disciplines of EE are Enterprise Architecture, Enterprise Governance and Enterprise Ontology (EO). Of these, EO offers a set of notions, concepts, and a methodology on a Way of Thinking (WoT), a Way of Modeling (WoM), and a Way of Working (WoW) for understanding the construction of enterprises. The methodology, which is currently the only methodology available in EO, is called Design & Engineering Methodology for Organizations (DEMO) (Dietz 2006). In the context of enterprise agility, DEMO and other modeling principles, once they exist, may play a significant role in advancing model-based engineering of enterprises.
Enterprise modelling for interoperable and knowledge-based enterprises
Published in International Journal of Production Research, 2018
Georg Weichhart, Christian Stary, François Vernadat
Enterprise models have proved to be essential in various ways to support design, analysis and operation of manufacturing and production systems of any kind. Among these, the most relevant situations include:Business Analysis (BA) and organisational understanding, which are concerned with the elaboration of a clear understanding of the goals, objectives, organisational structure, existing processes and flows, etc., to support system description, analysis or problem diagnosis of a business entity. Business Analysis is essential for preparing IT-based automation projects as well as for business/IT alignment but also in Enterprise Engineering projects.Enterprise Engineering (EE), i.e. designing, analysing, optimising and re-engineering business entities of enterprise systems. This requires detailed requirements definition models (as provided by business analysts and end users) and precise design specification models (subject to extensive qualitative and quantitative analyses, including computer simulation). This also includes a priori performance analysis and evaluation. It ends up with implementation description models to be run in the operational environment.Enterprise Integration and Interoperability (EI and I), as discussed in the previous section, for which the modelling of material, information and control flows as well as the definition of systems interfaces are essential.Enterprise transformation and the management of change, for which a model of the ‘as-is’ state and the ‘to-be’ state are essential for planning the migration path or for communicating and explaining changes to be made.Enterprise system control, for which models are used to sequence and monitor operation execution, for instance, executing business processes by means of workflow engines nowadays and with Enterprise Operating Systems (EOS) tomorrow (Chen, Youssef, and Zacharewicz 2015).