Synchronization emergence in manufacturing systems and its effect on logistic performance
Final Report Abstract
Production logistics often refers to a just-in-time paradigm, physics thinks about coherence: Both are forms of synchronization. The relationship between these two concepts has been little investigated. This project analyzed how synchronization from a logistics perspective is related to the one from a physics perspective, and what consequences this has for the efficiency and vulnerability of manufacturing processes. In the project, we have developed computer models that map machine cycles (takt) and material flow simultaneously. Using two parameters, the setup time p (How long does a machine need to switch to the next order?) and the interference noise f (How often do spontaneous interruptions occur, for example due to other orders?), we investigated the interaction of logistics and physics synchronization, and the effects on key performance indicators of the process. In a follow-up study, we verified the model predictions using production networks of real production processes and a comprehensive literature survey. In the parameter space (p, f ) we find four stable operating regimes that differ in their synchronization patterns and robustness. In addition, we were able to identify a large number of references in the literature for the relationship between the two types of synchronization (logistics, physics) and performance indicators and compare them with these predictions. Based on our findings, we were able to derive recommendations for the design of production systems. Companies can thus decide quantitatively whether they should tighten or deliberately loosen the cycle, in order to remain able to deliver. One example of this is that with long set-up times and few disruptions, the two types of synchronization suppress each other, whereas with short set-up times or many disruptions, they occur together. For practitioners, this means that shortening setup times or increasing the degree of disruption (e.g. through product diversity) not only changes the throughput, but also the “pattern” of the system’s dynamics.
Publications
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Opportunities for Synchronization in Manufacturing as Key Performance Indicator. Procedia CIRP, 107, 1467-1472.
Knapp, Florian; Antons, Oliver & Arlinghaus, Julia C.
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Just in time vs. all in sync: An analysis of two types of synchronization in a minimal model of machine activity in industrial production. PLOS Complex Systems, 2(2), e0000033.
Bose, Sanghita; Lesne, Annick; Arlinghaus, Julia & Hütt, Marc-Thorsten
