Using Entropy Metrics to Analyze Information Processing Within Production Systems: The Role of Organizational Constraints

Using Entropy Metrics to Analyze Information Processing Within Production Systems: The Role of Organizational Constraints

<i>Background</i>: The literature on measuring the complexity of production systems employs the graph and information theory. This study analyzes these systems and their coordination under varying states of control, with a focus on the probability of unfavorable events and their temporal...

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Bibliographic Details
Main Authors: Frits van Merode, Henri Boersma, Fleur Tournois, Windi Winasti, Nelson Aloysio Reis de Almeida Passos, Annelies van der Ham
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Logistics
Subjects:
production systems
supply chain
information processing
temporal network
Toyota Production System
Takt
Online Access:https://www.mdpi.com/2305-6290/9/2/46
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Summary:<i>Background</i>: The literature on measuring the complexity of production systems employs the graph and information theory. This study analyzes these systems and their coordination under varying states of control, with a focus on the probability of unfavorable events and their temporal characteristics. <i>Methods</i>: Coordination systems are represented as temporal networks, using entropy and node influence metrics. Two case studies are presented: a factory operating under the principles of the Toyota Production System (TPS) with adjacent (local) coordination and andon (global) coordination and a university obstetrics clinic with only adjacent (local) coordination. <i>Results</i>: Adjacent coordination leads to zero entropy in 38.40% of all situations in the TPS example, contrasted to 76.62% in the same system with andon coordination. Degree centrality of nodes outside of zero-entropy situations exhibits higher average and maximum values in andon coordination networks, compared to those with adjacent coordination in TPS. Entropy values in the university obstetric clinic range from 0.92 to 2.23, average degrees vary between 3 and 4.08, and maximum degrees range from 7 to 9. <i>Conclusions</i>: Coordination systems modeled as temporal networks capture the evolving nature of centralizing and decentralizing coordination in production systems.
ISSN:2305-6290

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