Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing syst...

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Main Authors: Smart, J, Calinescu, A, Huatuco, L
Format: Journal article
Language:English
Published: 2013
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author Smart, J
Calinescu, A
Huatuco, L
author_facet Smart, J
Calinescu, A
Huatuco, L
author_sort Smart, J
collection OXFORD
description This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facility's schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described. © 2013 Taylor and Francis.
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spelling oxford-uuid:fbd06177-c5ad-4196-b681-da53a51757b12022-03-27T13:16:31ZExtending the information-theoretic measures of the dynamic complexity of manufacturing systemsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:fbd06177-c5ad-4196-b681-da53a51757b1EnglishSymplectic Elements at Oxford2013Smart, JCalinescu, AHuatuco, LThis paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facility's schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described. © 2013 Taylor and Francis.
spellingShingle Smart, J
Calinescu, A
Huatuco, L
Extending the information-theoretic measures of the dynamic complexity of manufacturing systems
title Extending the information-theoretic measures of the dynamic complexity of manufacturing systems
title_full Extending the information-theoretic measures of the dynamic complexity of manufacturing systems
title_fullStr Extending the information-theoretic measures of the dynamic complexity of manufacturing systems
title_full_unstemmed Extending the information-theoretic measures of the dynamic complexity of manufacturing systems
title_short Extending the information-theoretic measures of the dynamic complexity of manufacturing systems
title_sort extending the information theoretic measures of the dynamic complexity of manufacturing systems
work_keys_str_mv AT smartj extendingtheinformationtheoreticmeasuresofthedynamiccomplexityofmanufacturingsystems
AT calinescua extendingtheinformationtheoreticmeasuresofthedynamiccomplexityofmanufacturingsystems
AT huatucol extendingtheinformationtheoreticmeasuresofthedynamiccomplexityofmanufacturingsystems