Yoshitaka Tanimizu

Evolutional reactive scheduling for agile manufacturing systems

A predetermined production schedule is often disturbed in agile manufacturing systems, due to unscheduled disruptions, such as delays of manufacturing operations and addition of new jobs. The objective of the research is to propose a new reactive scheduling method based on the Genetic Algorithm (GA), which generates improved production schedules reactively against the disturbances. A basic reactive scheduling method was proposed in the previous research. The proposed method continuously creates new feasible production schedules, until a new production schedule satisfies the given constraint or all the manufacturing operations have started. This paper deals with a new evolutional method to improve the performance of the GA-based reactive scheduling process for adding new jobs. Several computational experiments were carried out for the delays of manufacturing operations and the addition of new jobs by using the developed prototype system for reactive scheduling, in order to verify the effectiveness of the proposed method.

Multi agent architecture for dynamic incremental process planning in the flexible manufacturing system

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer’s needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.

Real-time scheduling for holonic manufacturing systems based on estimation of future status

This paper deals with a real-time scheduling system of holonic manufacturing systems (HMSs), which were proposed by an international cooperative research consortium called The HMS Consortium for Autonomous Distributed Management and Control of the Manufacturing Systems. The scheduling system generates real-time suitable production schedules, based on decision making by individual constituents named holons and their coordination. The objective of the present research is to improve the decision-making processes of the individual holons through the use of estimation process of the future status of the HMS. Procedures are developed and implemented to the individual holons, in order to estimate the future status of the HMS by applying the simulation model of the HMS. A neural network model is proposed to represent and to simulate the decision-making process of the individual holons.

A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing

New architectures of manufacturing systems have been proposed aiming at realising more flexible control structures of manufacturing systems, which can cope with dynamic changes in volume and variety of products, and also with unscheduled disruptions. The objective of the research is to develop an integrated process planning and scheduling system, which is applicable to the holonic manufacturing systems (HMS). A basic architecture for the HMS is proposed to determine both suitable sequences of the machining equipment needed to manufacture the products and suitable production schedules for the machining equipment. In particular, procedures are developed to generate suitable production schedules and to modify the process plans based on the scheduling results.

Analysis of Kinematic Motion Deviations of Rotary Tables Based on Geometric Tolerances

Machine tools are recognized as key elements of manufacturing systems, and product quality and cost mainly depend on performances of the machine tools. Much progress has been made in the machine tool technologies, aimed at improving the performances of the machine tools from various viewpoints, such as accuracy, reliability, productivity, and flexibility. The machining accuracy is one of the most important characteristics of the machine tools. From the viewpoints of the design and the manufacturing of the machine tools and their components, one of the important issues is to clarify the relationships between the kinematic motion deviations of the machine tools and the geometric tolerances of the components, such as the guide ways and the bearings. The objectives of the present research are to establish mathematical models representing the kinematic motion deviations of the machine tools, on the basis of the geometric tolerances of the components, and to apply the models to theoretical analysis of the kinematic motion deviations of the machine tool components.

Agent-based Dynamic Process Planning and Scheduling in Flexible Manufacturing System

This paper deals with an agent-based architecture of an integrated system for process planning and scheduling for multi jobs in flexible manufacturing systems. The process plans and the schedules of the manufacturing resources and the individual jobs are generated dynamically and incrementally. The architecture does not employ a set of predefined process plans, and the process plans of the individual jobs are incrementally and real timely generated from the alternative production routes in the process plan networks. Coordination agents are proposed to generate a suitable the assignment of the job agents to the machine tool agents at each step of the negotiation.

A Study on Real-Time Scheduling for Holonic Manufacturing Systems --- Simulation for Estimation of Future Status by Individual Holons

This paper deals with a real-time scheduling system of the holonic manufacturing systems (HMS). In the previous papers, real-time scheduling processes based on the utility values have been proposed and applied to the HMS. A simulation based procedure has also been implemented to estimate the future status of HMS and to determine the utility values aiming at improving scheduling method. However, it was assumed that only one holon in the HMS carries out the estimation for the ease of the estimation process. A simulation based real-time scheduling method is newly proposed, in the paper, to improve the estimation process which enable all the holons to estimate the future status of the HMS. An estimation process is developed for the individual holons to estimate the future status of HMS through the simulation. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method.

A Study on Real-Time Scheduling for Holonic Manufacturing Systems --- Determination of Utility Values Based on Multi-agent Reinforcement Learning

This paper deals with a real-time scheduling method for holonic manufacturing systems (HMS). In the previous paper, a real-time scheduling method based on utility values has been proposed and applied to the HMS. In the proposed method, all the job holons and the resource holons firstly evaluate the utility values for the cases where the holon selects the individual candidate holons for the next machining operations. The coordination holon secondly determine a suitable combination of the resource holons and the job holons which carry out the next machining operations, based on the utility values. Multi-agent reinforcement learning is newly proposed and implemented to the job holons and the resource holons, in order to improve their capabilities for evaluating the utility values of the candidate holons. The individual job holons and resource holons evaluate the suitable utility values according to the status of the HMS, by applying the proposed learning method.

A Study on Real-time Scheduling for Holonic Manufacturing Systems - Application of Reinforcement Learning -

A real-time scheduling method based on utility values has been proposed and applied to the holonic manufacturing systems (HMS), in the previous paper. In the proposed method, all the job holons and the resource holons firstly evaluate the utility values for the cases where the holon selects all the candidate holons for the next machining operations. The coordination holon secondly determine a suitable combination of the resource holons and the job holons, based on the utility values. Reinforcement learning is newly proposed and implemented to the individual job holons and resource holons, in order to improve their capabilities for evaluating the utility values.

Modeling and Simulation of Closed-Loop Supply Chains Considering Economic Efficiency

This study proposes a basic model of closed-loop supply chains which includes not only traditional forward supply chains for the generation of products but also reverse supply chains for the reuse of products in consideration of economic efficiency for MTO (Make to Order) companies. The model consists of four model components, i.e., clients, manufacturers, suppliers, and remanufacturers. A remanufacturer is added to the previous model of forward supply chains as a new model component which collects used products from clients and provides reusable parts to manufacturers. Remanufacturers as well as manufacturers and suppliers modify their schedules and negotiate with each other in order to determine suitable prices and delivery times of products. Remanufacturers stimulate clients to discard used products to meet the demand of reusable parts. They can increase the amount of reused products and reduce wastes by creating a balance between supply and demand of reusable parts.