Decentralized Manufacturing System Research Articles

409 階層分散型生産システムのためのリアクティブスケジューリングシステム

409 階層分散型生産システムのためのリアクティブスケジューリングシステム

Intelligent AGV driving toward an autonomous decentralized manufacturing system

This paper proposes two methods that give intelligence to automatically guided vehicles (AGVs). In order to drive AGVs autonomously, two types of problems need to be overcome. They are the AGV navigation problem and collision avoidance problem. The first problem has been well known since 1980s. A new method based on the feature scene recognition and acquisition is proposed. The sparse distributed memory neural network (SDM) is employed for the scene recognition and acquisition. The navigation route for the AGV is learnt by use of Q-learning depending on the recognized and acquired scenes. The second problem is described as mutual understanding of behaviors between AGVs. The method of mutual understanding is proposed by the use of Q-learning. Those two methods are combined together for driving plural AGVs autonomously to deliver raw materials between machine tools in a factory. They are incorporated into the AGVs as the machine intelligence. In experimental simulations, it is verified that the first proposed method can guide the AGV to the suitable navigation and that the second method can acquire knowledge of mutual understanding of the AGVs’ behaviors.

F-0617 階層分散型生産システムにおけるリアクティブスケジューリング : GAの適用(S42-3 生産システムにおけるソフトウェア技術(3))(S42 生産システムにおけるソフトウェア技術)

Production scheduling tasks are carried out hierarchically and concurrently, such as production scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the production schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. A rescheduling method is proposed to change the production schedules and to keep the consistency among the production schedules of the hierarchical and decentralized manufacturing systems. A prototype of distributed reactive scheduling system for the hierarchical and decentralized manufacturing systems is developed and applied to the consistency management problems in the rescheduling tasks.

Multi-Objective Modelling of Manufacturing Systems. 3rd Report. Concurrent Approach of Rescheduling on Hierarchical and Decentralized Manufacturing Systems.

Production scheduling tasks are in general carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. The objectives of the research are to establish a systematic method for supporting the rescheduling tasks and for keeping the consistency among the various layers of schedules of the hierarchical and decentralized manufacturing systems. Models for hierarchical production schedules are proposed, and rescheduling procedures are also developed based on the models. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules. A prototype of hierarchical and concurrent rescheduling system is developed and applied to the consistency management problems in the rescheduling tasks.

Decentralized Job Shop Scheduling by Recursive Propagation Method. 2nd Report. Scheduling for Hierarchical Systems.

A new type of job shop scheduling scheme is proposed in order to manage manufacturing system which has hierarchical structures. A system which consists of several system elements is identified as one independent system element and a job processed by the system elements is defined as a job for the system. Recursive propagation method, which is proposed by the authors in order to exchange information in the decentralized manufacturing system, is applied to the hierarchical job shop scheduling problem. Each system element notifies its action to the other system elements in the system and can know the change caused as a consequence of the action in the whole system. The feasibility of the methodology proposed is verified by computational simulations.

Decentralized Job Shop Scheduling by Recursive Propagation Method.

A new information exchange method named recursive propagation is proposed in order to solve job shop scheduling problems in decentralized manufacturing system. Each machine has only to notify the change of its plan to other machines which are directly influenced by the change. The effect of the change in the plan is directly fed back to the machine which notified the change. The change in the plan is notified to all the machines concerned by simple one to one communication among the machines, and the influence caused by its action can be reported to the initiator through the same communication path. The proposed method is applied to a 20×10 job shop scheduling problem, and the feasibility of this approach is verified by simulations.

1313 階層分散型生産システムのスケジューリングに関する研究(FM-3 生産システム(1))

1313 階層分散型生産システムのスケジューリングに関する研究(FM-3 生産システム(1))

AGV Autonornous Driving Based on Scene Recognition by Use of the Simplified SDM.

An intelligent material-handling system is an important part of an autonomous decentralized manufacturing system(ADMS). Especially, an automatically guided vehicle(AGV)is the core of the material-handling system. This paper reports on a method to drive the AGV autonomously in the ADMS. The new method proposed here combines the sparse distributed memory neural network(SDM)with Q-learnig(Q-L). The SDM explores and acquires feature scenes required for AGV driving. The Q-L finds a direction to take at a particular scene acquired by the SDM. Numerical simulation verifies that the SDM can extract the feature scenes necessary for driving the AGV, and that the Q-L can instruct the right direction to the AGV at each extracted scene so that the vehicle may move towards the target location.

Design of negotiation protocols for multi-agent manufacturing systems

This paper proposes new inter-agent and intra-agent negotiation mechanisms for improving the performance of multi-agent or decentralized manufacturing systems. The overall performance of this system depends on the effective interactions between agents. This research presents methods which would permit cooperation and multi-stage interactions among agents. Agents may collaborate or pre-empt other agents based on the available currency and task criticality. The objective of this research is to demonstrate the efficiency of different negotiation and collaboration schemes between agents of the same class (parts, machines, etc), and inter-class negotiations using currency metrics and pre-emption. The proposed negotiation schemes are implemented using the Swarm simulation platform.

Practical study on wireless transmission of power and information for autonomous decentralized manufacturing system

In previous papers, the authors have already introduced the idea of an autonomous decentralized manufacturing system (ADMS), in which machines receive electrical energy through wireless power transmission and also are decentrally controlled through wireless transmission of the control and feedback data. With this idea, the degree of freedom in motion control is enlarged, and the system has the capability of adaptive reconfiguration to product variation as a result. In this paper, the practical problems for realization of wireless transmission of power and information (WTPI) needed for the proposed ADMS are clarified, and the practical solutions to these problems are presented. Several industrial applications of the WTPI are also introduced.

Studies of Autonomous Decentralized Manufacturing System. 1st Report, Optimization of Single-Period Production Planning Problem by Noncooperative Game.

In this paper, a method for the decentralization of multi-stage manufacturing systems is proposed under the noncooperative game. Necessary optimality conditions and Nash equilibrium solution as optimal production plan are derived for single period production planning problem of autonomous decentralized manufactuing systems that consists of multistages. Numerical examples are solved to examine the validity of the proposed approach.

PRIAM: polite rescheduler for intelligent automated manufacturing

This paper considers the problem of rescheduling in a decentralized manufacturing system. Flexible manufacturing systems must be able to respond to unexpected disruptions; including schedule disruptions. However, when a cell controller in a decentralized system responds to a disruption, it may disrupt some other cells, because the actions taken at one cell may have some consequence at another cells. In the approach we propose, a controller at a disrupted cell tries to respond in a way which is likely to be least disruptive to other cells, through negotiation with controllers at other cells. This approach, which we call replanning, has the advantage of retaining much of the original distributed plan, while avoiding wide propagation of the disruption through the rest of the system. We apply this concept to the domain of distributed factory rescheduling, and describe PRIAM (polite rescheduler for intelligent automated manufacturing), a polite rescheduling architecture which is currently under development. Simulation results show that the use of negotiation in polite rescheduling prevents the wide propagation of disruption from an initial local disruption.