Abstract
The transition from traditional to truly smart dynamically adaptable manufacturing demands the adoption of a high degree of autonomy within automation systems, with resultant changes in the role of the human, in both the manufacturing and logistics functions within the factory. In the context of smart manufacturing, this paper describes research towards the realization of adaptable autonomous automation systems from both the control and information perspectives. Key facets of the approach taken at WMG are described in relation to human–machine interaction, autonomous approaches to assembly and intra-logistics, integration and dynamic system-wide optimization. The progression from simple distributed behavioural components towards autonomous functional entities is described. Effective systems integration and the importance of interoperability in the realization of more distributed and autonomous automation systems are discussed, so that operational information can propagate seamlessly, eliminating the traditional boundary between operational technology and information technology systems, and as an enabler for global knowledge collection, analysis and optimization.This article is part of the theme issue ‘Towards symbiotic autonomous systems'.
Highlights
A number of trends are observable in automation from the complete automation paradigms of the 1980s2021 The Authors
This paper considers the overall concepts in a symbiotic context via consideration of a set of complimentary research activities at the University of Warwick
WMG is carrying out research in collaboration with Polytechnic Institute of Braganca using a digital twin-based optimization approach coupled with AI and decision support systems
Summary
A number of trends are observable in automation from the complete automation paradigms of the 1980s. A number of research groups are looking at the potential for self-organizing manufacturing systems [1] Such approaches are regarded as vitally important to achieve more flexible and reconfigurable manufacturing [2,3]. From a user perspective, such tools need to be pervasive, usable throughout the system lifecycle and capable of supporting the design, deployment and operational phases directly from a common engineering model, or digital twin as it has become known [11]. Such models are key enablers for lifecycle knowledge capture, configuration, optimization and reuse of modular manufacturing systems [12].
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