Modeling of distributed manufacturing systems (original) (raw)

Foundations and Principles of Distributed Manufacturing

The networkable device of the smart distributed manufacturing unit with mobile properties, working on the base of new principles, strongly informatising and decentralising manufacturing, has definitely stepped into the shopfloor to stay. Evolving network decision procedures, fully accepting the network nature of manufacturing, will replace the conventional, time slicing, command and control, one-time static, machine centred planning and control approaches as still mostly implemented in production control and enterprise resource planning. Fully incorporating network principles and, thus, making use of the network nature of manufacturing are the preconditions to overcome the particularities of high-frequency planning effects, as resource over-consumption and organisational hectic on the shopfloors. Cyber Physical Production Systems and the Internet of things challenge machines and equipment to become online, interconnected and interactive, which is fundamentally different from batch oriented logic of numerical control (NC) or Flexible Manufacturing Systems (FMS). More and better data will not cause more hectic, more frequent changes or more staccato revised decisions; accurate real-time data will rather install and maintain resource efficient, steady and smooth, easily manageable manufacturing progress, and enable to add more value in shorter time with far less input. First examples of implementing these principles already demonstrate astonishing results, and this is only the start. Witnessing the big players from telecommunication, hardware producers, software designers, and systems providers, and the huge innovation power behind, gives an impression that there will be intriguing novelties ahead in all branches. In distributed manufacturing, we are just at the beginning of an era of smart devices in all sectors; there might soon come up smart DM solutions, which we cannot even imagine today. Conclusions and Outlook

Autonomous Multi-Agents Architecture for Control of Manufacturing Systems

Advances in Networked Enterprises, 2000

This paper focuses on the discussions of innovative Multi-Agent approach to advanced real time control for flexible manufacturing systems. The architecture is based on the paradigm of Distributed Intelligence and Multi-Agent systems. This Multi-Agent prototype system involves the following functions: Scheduling, dispatching, monitoring and error handling. A new negotiation protocol for manufacturing system is also presented in this paper. The purpose of this protocol is to dynamically assign operations to the resources of the Manufacturing System in order to accomplish the proposed tasks. This protocol is able to deal with exceptions.

A Framework for Distributed Manufacturing Applications

2000

The new organisational structures used in world wide manufacturing systems require the development of distributed applications, which present solutions to their requirements. The work research in the distributed manufacturing control leads to emergent paradigms, such as Holonic Manufacturing Systems (HMS) and Bionic Manufacturing Systems (BMS), which translates the concepts from social organisations and biological systems to the manufacturing world. This paper present a framework for the development of distributed manufacturing applications, based in an agent-based architecture, which implements some Holonic and Bionic Manufacturing Systems concepts.

A distributed architecture for automated manufacturing systems

The International Journal of Advanced Manufacturing Technology, 1988

The concept O[ d&tributed architectures for automated manufacturing systems is presented here. A modular architecture for a logical cell-controller is proposed where shopfloor level modules are incorporated in the cell control system so as to allow active cooperation for distributed decision making and control. Two examples illustrating distributed formulations for specific planning and control are presented. These examples demonstrate the feasibility and potential for distributed architectures for automated manufacturing.

INTEGRATED AND DISTRIBUTED MANUFACTURING, A MULTI-AGENT PERSPECTIVE

2001

There has been a large and rapid evolution in terns of the paradigms and technologies to support the development of distributed manufacturing systems and real-time applications. This paper starts with a survey of the main proposals in the area based on the experience gained by the authors in various fields pertaining to manufacturing device modelling, control and supervision, industrial messaging, production management and reengineering methodology. The rational for a multi-agent approach is discussed as the available technologies to support the development of agent-based applications are summarised. Finally an implementation of controlling agents in a flexible manufacturing system is described and discussed.

A Layered Approach to Distributed Manufacturing

1999

World-wide competition forces enterprises to achieve new cooperations and arrangements with other enterprises in order to share skills, using the virtual enterprise concept. The virtual enterprise introduces the distributed manufacturing concept, which can be expanded and zoomed to other distributed layers, such as multi-site and interacting units. The development and implementation of distributed manufacturing control systems, based in new distributed manufacturing paradigms, plays a key factor in the improvement of the enterprises capacity to react to market and organisation changes. This paper gives an overview of manufacturing paradigms and describes the evolution of control architectures, from the classical approach to the distributed approaches.

Intelligent distributed production control

Journal of Intelligent Manufacturing, 2012

This editorial introduces the special issue of the Springer journal, Journal of Intelligent Manufacturing, on intelligent distributed production control. This special issue contains selected papers presented at the 13th IFAC Symposium on Information Control Problems in Manufacturing-INCOM'2009 (Bakhtadze and Dolgui 2009). The papers in this special issue were selected because of their high quality and their specific way of addressing the variety of issues dealing with intelligent distributed production control. Previous global discussions about the state of the art in intelligent distributed production control are provided, as well as exploratory guidelines for future research in this area.

Distributed Manufacturing Systems with Digital Agent

Strojniški vestnik – Journal of Mechanical Engineering

This paper presents a novel approach to implement manufacturing nodes using the combined strength of digital twins, holons, and digital agents. Manufacturing nodes are based on holon theory and present a universal manufacturing platform that consists of cyber-physical systems (CPS) with an integrated digital twin, digital agent, databases and various communication protocols. The manufacturing node network is controlled globally using the global digital twin of logistics process and locally using the local nodes and local digital agents, digital twins and information shared by the node network. The main objective of this research was to develop and test a new concept of distributed system modelling and distributed system control for easy implementation of distributed manufacturing nodes in a smart factory concept.

AOP3S: A Balanced Approach to Model Distributed Manufacturing Systems

Intelligent Systems for Manufacturing, 1998

In order to improve the competitiveness of current manufacturing enterprises, the European Committee for Standardisation, Technical Committee Advanced Manufacturing Technologies, has pointed out the interests and significance of new modelling techniques and tools, which are particularly adapted to face two fundamental points: (i) the distribution of functional, decisional and informational capabilities of the enterprise leading to the characterisation of autonomous units and (ii) the development of cooperation policies between these units. This paper briefly presents the AOP3S framework, which aims to face some important aspects ofthese requirements. AOP3S is basedon concepts mainly issued from a balanced approach embracing the Multi-Agent Systems and the CIMOSA architecture. An example is also provided.

Hybrid Production-System Control-Architecture for Smart Manufacturing

On the Move to Meaningful Internet Systems. OTM 2017 Workshops, 2018

Highly customized products with shorter life cycles characterize the market today: the smart manufacturing paradigm can answer these needs. In this latter production system context, the interaction between production resources (PRs) can be swiftly adapted to meet both the variety of customers' needs and the optimization goals. In the scientific literature, several architectural configurations have been devised so far to this aim, namely: hierarchical, heterarchical or hybrid. Whether the hierarchical and heterarchical architectures provide respectively low reactivity and a reduced vision of the optimization opportunities at production system level, the hybrid architectures can mitigate the limit of both the previous architectures. However, no hybrid architecture can ensure all PRs are aware of how orienting their behavior to achieve the optimization goal of the manufacturing system with a minimal computational effort. In this paper, a new "hybrid architecture" is proposed to meet this goal. At each order entry, this architecture allows the PRs to be dynamically grouped. Each group has a supervisor, i.e. the optimizer, that has the responsibility: 1) to monitor the tasks on all the resources, 2) to compute the optimal manufacturing parameters and 3) to provide the optimization results to the resources of the group. A software prototype was developed to test the new architecture design in a simulated flow-shop and in a simplified job shop production.