On agent-based decentralized and integrated scheduling for small-scale manufacturing

Abstract

Small-scale manufacturing often relies on flexible production systems that can cope with frequent changes of products and equipment. Transports are a significant part of the production flow, especially in the domain of large and heavy workpieces that requires explicit planning to avoid unnecessary delays. This contribution takes a detailed look at how to create feasible integrated schedules within a decentralised or even heterarchical architecture and which information the agents have to exchange. These schedules incorporate constraints such as the blocking-constraint. They also consider dynamic setup and operation durations while finding a good-enough solution. The proposed agent-based solution applies to a wide variety of scheduling problems and reveals positive properties in terms of scalability and reconfigurability.

A Classification of Data Structures for Process Analysis in Internal Logistics

“…The processes, on the other hand, generate data which is subsequently stored and further transferred by these systems [2]. During recent years, a wide range of process types has been adapted to this digital connection, often referred to as Industry 4.0 [3]. This development yields the potential for new types of process analysis, which are the result of recent advances in the field of data science.…”

A Secure Multi-Agent-Based Decision Model Using a Consensus Mechanism for Intelligent Manufacturing Tasks

“…For modeling supply chain dynamics with agents' decision-making, multi-agent approaches have been proposed in [16,17]. To address a variety of scheduling problems within a decentralized and hierarchical architecture, agents based model has been proposed in [18]; these schedules include constraints such as the blocking constraint. A multiagent model to share distributed manufacturing resources has been proposed in [19].…”

An approach for joint scheduling of production and predictive maintenance activities

“…They have shown their effectiveness regarding scheduling problems. Therefore, they have been widely accepted in applications for production and/or maintenance scheduling [29], [38]- [41], [42], [29] as the autonomous, distributed and dynamic nature of the agents fits the requirements to design complex, flexible, robust and dynamic manufacturing scheduling methods [43]. An agent is a software entity that has a knowledge base, a reasoning process, and an explicit model of the problem to solve.…”

“…However, there was no generic protocol for task announcements, auctions and validation decisions [49]. CNP has demonstrated its ability to test various scheduling strategies [50] and to schedule decentralized and integrated manufacturing systems [38]. Among the MASs based on CNP, SCEP (Supervisor, Customers, Environment and Producers) framework allows to deal with flexible manufacturing routings and different machine structures and it can associate different objectives and constraints to the agents [50].…”

“…In this work, we propose a new MAS framework called SCEMP (Supervisor, Customers, Environment, Maintainers and Producers), inspired by SCEP. Like in [38], SCEMP considers decentralized manufacturing systems that can be made of networked companies but, in SCEMP, new maintainer agents are added and the predictive maintenance strategy is implemented. The producers, considered as production resources (e.g.…”