Agent-based distributed manufacturing control: A state-of-the-art survey

Abstract

a b s t r a c tManufacturing has faced significant changes during the last years, namely the move from a local economy towards a global and competitive economy, with markets demanding for highly customized products of high quality at lower costs, and with short life cycles. In this environment, manufacturing enterprises, to remain competitive, must respond closely to customer demands by improving their flexibility and agility, while maintaining their productivity and quality. Dynamic response to emergence is becoming a key issue in manufacturing field because traditional manufacturing control systems are built upon rigid control architectures, which cannot respond efficiently and effectively to dynamic change. In these circumstances, the current challenge is to develop manufacturing control systems that exhibit intelligence, robustness and adaptation to the environment changes and disturbances. The introduction of multi-agent systems and holonic manufacturing systems paradigms addresses these requirements, bringing the advantages of modularity, decentralization, autonomy, scalability and reusability. This paper surveys the literature in manufacturing control systems using distributed artificial intelligence techniques, namely multi-agent systems and holonic manufacturing systems principles. The paper also discusses the reasons for the weak adoption of these approaches by industry and points out the challenges and research opportunities for the future.

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

“…Agents are units of a software system typically characterized by autonomy, intelligence, adaptation, co-operation [37] and reactivity [38]. The reactivity is the feature that makes an agent ready for receiving external messages and responding to them in a sufficiently short time.…”

Multi-Agent System for On-demand Production Integrating Production and Quality Control

“…In the process execution, the PA agent interacts with the RA and QCA agents that are able to execute the k individual operations belonging to the process plan. At the end of one operation execution, the next operation to be executed is selected by the function represented by the timed transition t 5 , followed by the execution of the "supervises the operation execution" function represented by the timed transition t 6 . This transition can be expanded into a refined Petri nets model containing the details about the functions to supervise the execution of the operation.…”

“…In fact, the distributed nature of the multi-agent systems approaches suggests the definition of distributed control functionalities based on autonomous agents that account for the realization of efficient, flexible and robust overall plant control, exhibiting modularity adaptation and re-configurability. Several applications of multi-agent systems at factory level were reported in the literature (e.g., see [6] and [7] and the references therein).…”

Adaptive Multi-Agent System for a Washing Machine Production Line

“…In spite of the promising perspective of using MAS solutions to address the challenge of achieving adaptive production systems, only few industrial applications were reported in the literature, e.g. the application in a factory plant of Daimler Chrysler [4] and some experiences from Rockwell Automation [5] and Schneider Electric [6] (see [7] and [8] for a deeply analysis). Several reasons were the rear tub) and the operation parameters (e.g.…”