A novel throughput control algorithm for semi-heterarchical industry 4.0 architecture

Silvestro Vespoli (), Guido Guizzi (), Elisa Gebennini () and Andrea Grassi ()
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Silvestro Vespoli: Università degli Studi di Napoli Federico II
Guido Guizzi: Università degli Studi di Napoli Federico II
Elisa Gebennini: Universitas Mercatorum
Andrea Grassi: Università degli Studi di Napoli Federico II

Annals of Operations Research, 2022, vol. 310, issue 1, No 9, 221 pages

Abstract: Abstract Modern market scenarios are imposing a radical change in the production concept, driving companies’ attention to customer satisfaction through increased product customization and quick response strategies to maintain competitiveness. At the same time, the growing development of Industry 4.0 technologies made possible the creation of new manufacturing paradigms in which an increased level of autonomy is one of the key concepts to consider. Taking the advantage from the recent development around the semi-heterarchical architecture, this work proposes a first model for the throughput control of a production system managed by such an architecture. A cascade control algorithm is proposed considering work-in-progress (WIP) as the primary control lever for achieving a specific throughput target. It is composed of an optimal control law based on an analytical model of the considered production system, and of a secondary proportional-integral-derivative controller capable of performing an additional control action that addresses the error raised by the theoretical model’s. The proposed throughput control algorithm has been tested in different simulated scenarios, and the results showed that the combination of the control actions made it possible to have continuous adjustment of the WIP of the controlled production system, maintaining it at the minimum value required to achieve the requested throughput with nearly zero errors.

Keywords: Industry 4.0; Decentralized production control; Mass customization; Dynamic production control; Optimal control (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-021-04184-z

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