CoMM: a consensus algorithm for multi-agent-based manufacturing system to deal with perturbation

Abstract

The emergence of Cyber Physical System has dramatically impacted the use of traditionally centralized control system in responding to unexpected events. Rush order is quite common unexpected event in the current dynamic market characteristics and has significant perturbing ability to a centrally predictive schedule. This paper is aimed to propose a Consensus algorithm for Multi-agent based Manufacturing system (CoMM) to control the rush order and henceforth minimize a makespan. Consensus is an algorithmic procedure applied in control theory which allows convergence of state between locally autonomous agents collaborating for their common goal. Leader-Follower communication approach was used among the multi-agent to deal with the perturbing event. Each agent decides when to broadcast its state to neighbor agents and the controlling decision depends on the behavior of this state. The consensus algorithm is initially modeled by networking all contributing agents. After this, it is validated with simulation experiment based on academic full-sized application platform called TRACILOGIS platform. The results showed that the consensus algorithm has significantly minimized the impact of rush order on makespan of manufacturing orders launched on a system.

Multicriteria decision-making method for scheduling problem based on smart batches and their quality prediction capability

“…This second option is supported by recent developments concerning hybrid control architectures. Most recent studies (such as Pach et al, 2014;Barbosa et al, 2015;Indriago et al, 2016;Quintanilla et al, 2016;Jimenez J. F. et al, 2017;Zimmermann et al, 2017;Valckenaers P., 2018;Mezgebe et al, 2019) have already proven the adequacy of such architectures to address resilience and adaptability issues for production flows. In their work, Zimmermann et al (2017) proposed a hybrid architecture based on the product driven system concept, where an instance of the quality prediction NN model would be embedded on each product or batch, assuming that an optimized schedule was provided to workstations.…”

“…To model and implement this hybrid architecture, many collective decision-making approaches executed in multi-agent systems have been introduced. Some of them are inspired by social attitudes such as consensus (Mezgebe et al, 2019) and majority voting (Pitt et al, 2006), or from the domain of game theory (Parsons and Wooldridge, 2002). Others seek to imitate biological behaviors such as swarm robotics (Schmickl et al, 2009), bee swarms (Teodorovic, 2003), and ant colonies (Xiang and Lee, 2008).…”

“…Motivated by the framework of Industry 4.0, the current focus is mainly on the second path. In the existing requirement for dynamic decision, the distribution of decisional ability to enable the system's self-adaptation to changing situations is seen as a great improvement vector for real-time problem-solving and adaptability enhancement (Mezgebe et al, 2019). However, such systems suffer from the phenomenon of social myopia, where decisional entities in distributed reactive decision-making cannot balance their local objectives with the system's global objective (Rey et al, 2014).…”

Multi-agent based manufacturing: current trends and challenges

“…It takes into account dynamic tasks arrivals. Mezgebe et al [40] : Algorithm for multiagent-based manufacturing system Consensus algorithm for multi agent based manufacturing system (CoMM) -to control rush order and minimize a makespan. consensus.…”

Design and management of digital manufacturing and assembly systems in the Industry 4.0 era

“…Mezgebe et al [72] propose a consensus algorithm for multi-agent-based manufacturing system to control the rush order and henceforth minimize a makespan of Cyber Physical System. Consensus is an algorithmic procedure applied in control theory which allows convergence of state between locally autonomous agents collaborating for their common goal.…”