Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems

Fayoumi, Amjad (2016) Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems. Computers in Industry, 80. pp. 54-68. ISSN 0166-3615

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Rapid changes in the open manufacturing environment are imminent due to the increase of customer demand, global competition, and digital fusion. This has exponentially increased both complexity and uncertainty in the manufacturing landscape, creating serious challenges for competitive enterprises. For enterprises to remain competitive, analysing manufacturing activities and designing systems to address emergent needs, in a timely and efficient manner, is understood to be crucial. However, existing analysis and design approaches adopt a narrow diagnostic focus on either managerial or engineering aspects and neglect to consider the holistic complex behaviour of enterprises in a collaborative manufacturing network (CMN). It has been suggested that reflecting upon ecosystem theory may bring a better understanding of how to analyse the CMN. The research presented in this paper draws on a theoretical discussion with aim to demonstrate a facilitating approach to those analysis and design tasks. This approach was later operationalised using enterprise modelling (EM) techniques in a novel, developed framework that enhanced systematic analysis, design, and business-IT alignment. It is expected that this research view is opening a new field of investigation.

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Journal Article
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Computers in Industry
Additional Information:
This is the author’s version of a work that was accepted for publication in Computers in Industry. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers in Industry, 80, 2016 DOI: 10.1016/j.compind.2016.04.003
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06 Jul 2017 08:10
Last Modified:
22 Nov 2022 04:47