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Service Based Approach to Asset Administration Shell for Controlling Testing Processes in Manufacturing

Rehman, Hamood Ur; Chaplin, Jack C.; Zarzycki, Leszek; Mo, Fan; Jones, Mark; Ratchev, Svetan

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Authors

Hamood Ur Rehman

Leszek Zarzycki

FAN MO Fan.Mo@nottingham.ac.uk
Interdisciplinary Research Fellow in Intelligent Manufacturing Systems

Mark Jones

Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
Cripps Professor of Production Engineering & Head of Research Division



Abstract

The rise in demand for customised products and lower costs has generated the need for incorporating intelligence in production systems. Intelligence is the main driver for enabling intelligent control in production systems to meet feature, part and conditional variations. It also promotes solutions that offer higher functionalities and lower costs. The research presented in this paper focuses on integrating intelligence into testing processes within a production system. A novel method of controlling the testing functionality is presented by deploying and using the asset administration shell approach. A means of controlling the process with the asset administration shell guided by simulation is demonstrated. An architecture for controlling the execution behaviour in testing process by services is conceptualised offering a modular and low-cost solution. A validation by using an experimental use-case of leak-testing is presented.

Conference Name 10th IFAC Conference On Manufacturing Modelling, Management And Control
Conference Location Nantes, France
Start Date Jun 22, 2022
End Date Jun 24, 2022
Acceptance Date Apr 10, 2022
Online Publication Date Jun 24, 2022
Publication Date Jun 24, 2022
Deposit Date May 18, 2022
Publicly Available Date Jun 24, 2022
Publisher IFAC (International Federation of Automatic Control)
Series Title IFAC Conference On Manufacturing Modelling, Management And Control
Book Title 10th IFAC Conference On Manufacturing Modelling, Management And Control
Keywords leak testing; asset administration; low-cost industrial digitalisation and control
Public URL https://nottingham-repository.worktribe.com/output/8132955
Related Public URLs https://hub.imt-atlantique.fr/mim2022/

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