Assessing operational complexity of manufacturing systems based on algorithmic complexity of key performance indicator time-series

Journal article


Alkan, B. and Bullock, S. (2020). Assessing operational complexity of manufacturing systems based on algorithmic complexity of key performance indicator time-series. Journal of the Operational Research Society. https://doi.org/10.1080/01605682.2020.1779622
AuthorsAlkan, B. and Bullock, S.
Abstract

This article presents an approach to the assessment of operational manufacturing systems complexity based on the irregularities hidden in manufacturing key performance indicator time-series by employing three complementary algorithmic complexity measures: Kolmogorov complexity, Kolmogorov complexity spectrum’s highest value and overall Kolmogorov complexity. A series of computer simulations derived from discrete manufacturing systems are used to investigate the measures’ potentiality. The results showed that the presented measures can be used in quantitatively identifying operational system complexity, thereby supporting operational shop-floor decision-making activities.

Year2020
JournalJournal of the Operational Research Society
PublisherTaylor & Francis
Digital Object Identifier (DOI)https://doi.org/10.1080/01605682.2020.1779622
Publication dates
Print03 Jul 2020
Publication process dates
Accepted04 Jun 2020
Deposited11 Feb 2021
Accepted author manuscript
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File Access Level
Open
Additional information

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the Operational Research Society on 03/07/2020, available online: http://www.tandfonline.com/10.1080/01605682.2020.1779622

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License: CC BY 4.0
File access level: Open

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