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A methodology to create a sensing, smart and sustainable manufacturing enterprise
- Source :
- International Journal of Production Research. 56:584-603
- Publication Year :
- 2017
- Publisher :
- Informa UK Limited, 2017.
-
Abstract
- Next-generation manufacturing enterprises need to be sensing, smart and sustainable to be competitive: ‘sensing’ refers to context awareness at internal and external levels; ‘smart’ refers to knowledge-based organisations that adapt to changes and ‘sustainable’ refers to the ability to operate without damaging the environment, community or economy. Although technologies do exist to support the development of such enterprises, there is a need for methodologies that help in the entire enterprise engineering problem. This paper proposes a methodology, based on the principles of enterprise architecture, to design a sensing, smart and sustainable manufacturing enterprise. The methodology aims at adopting the best practices used in enterprise engineering while dealing with the relevant gaps. An analysis of the characteristics of the ‘Sensing, Smart and Sustainable Manufacturing Enterprise’ (S3-ME) is presented to understand the advantages of using the proposed methodology. The methodology comprises the instanti...
- Subjects :
- Enterprise systems engineering
0209 industrial biotechnology
Engineering
Process management
Knowledge management
business.industry
Strategy and Management
05 social sciences
Enterprise integration
02 engineering and technology
Management Science and Operations Research
Industrial and Manufacturing Engineering
Enterprise modelling
020901 industrial engineering & automation
Enterprise architecture management
Enterprise life cycle
0502 economics and business
Enterprise engineering
Enterprise information system
business
050203 business & management
Enterprise software
Subjects
Details
- ISSN :
- 1366588X and 00207543
- Volume :
- 56
- Database :
- OpenAIRE
- Journal :
- International Journal of Production Research
- Accession number :
- edsair.doi...........0296693ea4ae65bef871d0449e8e5a53
- Full Text :
- https://doi.org/10.1080/00207543.2017.1386333