Assessing operational complexity of manufacturing systems based on algorithmic complexity of key performance indicator time-series. Issue 10 (3rd October 2021)

• Record Type: Journal Article
• Authors: Alkan, Bugra; Bullock, Seth
• Is Part Of: Journal of the Operational Research Society. Volume 72:Issue 10(2021)
• Page Start: 2241
• Page End: 2255
• Publication Date: 2021-10-03
• Subjects: Manufacturing systems -- complexity -- KPI -- Kolmogorov complexity -- operations research -- discrete event simulations; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2020.1779622
• Languages: English
• ISSNs: 0160-5682

Abstract

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.