Fayoumi, A ORCID: https://orcid.org/0000-0001-7418-8569, 2016. Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems. Computers in Industry, 80, pp. 54-68. ISSN 0166-3615
Preview |
Text
5576_Fayoumi.pdf - Post-print Download (1MB) | Preview |
Abstract
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.
Item Type: | Journal article |
---|---|
Publication Title: | Computers in Industry |
Creators: | Fayoumi, A. |
Publisher: | Elsevier |
Date: | August 2016 |
Volume: | 80 |
ISSN: | 0166-3615 |
Identifiers: | Number Type 10.1016/j.compind.2016.04.003 DOI |
Divisions: | Schools > School of Science and Technology |
Record created by: | Jonathan Gallacher |
Date Added: | 11 Jul 2016 14:14 |
Last Modified: | 07 Nov 2017 15:54 |
URI: | https://irep.ntu.ac.uk/id/eprint/28127 |
Actions (login required)
Edit View |
Statistics
Views
Views per month over past year
Downloads
Downloads per month over past year