The Paradigm Shift in Smart Manufacturing System Ar-chitecture

Published

September 4, 2016

Author(s)

Yan Lu, Frank H. Riddick, Nenad Ivezic

Abstract

In response to demanding market conditions, Smart Manufacturing (SM) seeks to integrate advanced manufacturing methods, operational technologies (OT), and information and communication technologies (ICT) to drive the creation of manufacturing systems with greater capabilities in cost control and performance. A crucial differentiation of SM systems lies in their architectures, which are organized as networks of cooperating manufacturing components specialized for different functions as opposed to the previous organization characterized by rigid, hierarchically-integrated layers of application components. This "ecosystem" of manufacturing components enables SM systems that can provide heretofore unattainable levels of performance for manufacturers with respect to agility, productivity, quality and sustainability. This paper provides a study of the architectural impact of individual ICT technologies on the emerging manufacturing ecosystem that potentially eliminates the need to design manufacturing systems based on the hierarchical levels of the legacy ISA 95 model. Additionally, we propose a service-oriented SM system architecture that leverages the benefits of ICT and the safety and security requirements from the OT domain. Key challenges of implementing such architecture are also presented.

Proceedings Title

Proceedings of APMS 2016

Conference Dates

September 3-7, 2016

Conference Location

Iguassu Falls, AZ, US

Conference Title

International Conference on Advances in Production Management Systems 2016

Pub Type

Conferences

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Keywords

system architecture, smart manufacturing, cyber physical production system, service oriented architecture

Citation

Lu, Y. , Riddick, F. and Ivezic, N. (2016), The Paradigm Shift in Smart Manufacturing System Ar-chitecture, Proceedings of APMS 2016, Iguassu Falls, AZ, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=920863 (Accessed April 24, 2024)