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

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.

Performance Evaluation of a Production Control Architectures for Flexible Manufacturing System

“…The anarchic approach allows for greater autonomy and decision-making capabilities at the individual component level, enabling the system to handle a variety of assembly scenarios efficiently [12]. In order to improve flexibility and adaptability through the integration of automated and distributed learning capabilities, [13] suggests developing an automated learning control architecture for manufacturing systems. For the purpose of enhancing the performance of the manufacturing system.…”

Switching mechanism of dynamic hybrid control multi-agent system in manufacturing environment

“…Firms' focus on customer satisfaction is influenced by both present and future market conditions. Consequently, organizations are motivated to adopt enhanced product customization and prompt responsiveness to sustain their competitive edge [1]. Companies want adaptable production systems that may effectively employ their capacities irrespective of disruptions [2].…”

“…Automated manufacturing systems can be controlled using four different types of architectures: centralized control, hierarchical control, semi-heterarchical (or hybrid) control, and heterarchical (or decentralized) control [7,8]. There is an increasing interest in hybrid control structures that exhibit characteristics of neither centralization nor decentralization [1]. The transition from a hierarchical control structure to a heterarchical or semi-heterarchical control structure can enhance production efficiency, particularly when dealing with deviations from typical operational circumstances [7].…”

“…This study aims to outline the primary contributions pertaining to the topics above. (1) This study presents a proposed methodology for incorporating an optimization technique into the switching mechanism among hierarchical and hierarchical structures. This allows for executing the control system design in the most appropriate operating mode that meets the requirements of optimality and reactivity.…”

Generalised Performance Estimation in Novel Hybrid MPC Architectures: Modeling the CONWIP Flow-Shop System

“…Among these, Vespoli et al [32] proposed a first implementation of the aforementioned semi-heterarchical architecture for Spearman et al [25]'s controlled work-in-progress (CONWIP) flow-shop production line, taking advantage of the availability of closed form analytical models. With the aim of controlling the throughput of the supervised production line, they proposed the use of a "cascade control algorithm, composed of an optimal control law based on the analytical model from Hopp and Spearman [33], and of a secondary Proportional-Integral-Derivative (PID) controller capable of performing an additional control action that addresses the error raised by the analytical model" [34]. The proposed mechanism performs well when dealing with productive scenarios in which the assumptions at the base of the analytical model are met.…”