Tatsuhiko Sakaguchi

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.

A Scheduling Method With Considering Nesting for Sheet Metal Processing

In sheet metal processing, several parts are cut from one sheet metal by punching process. Before punching process, layout of parts is decided by the nesting. If the parts are arranged as compactly as possible into one sheet metal, the waste of raw materials can be reduced. Therefore, the nesting is essential for optimizing the layout of parts. However, if the nesting is executed without considering the following manufacturing processes, there cause various inefficiencies all over the processes. Therefore, the nesting and the scheduling should be considered simultaneously for the efficient manufacturing. With this point of view, in this study, we propose an integrated method in terms of scheduling and nesting. Moreover, we verified the effectiveness of the proposed method through some computational experiments.Copyright

A Heuristic Approach for Integrated Nesting and Scheduling in Sheet Metal Processing

In recent years, sustainable and agile manufacturing is aimed at in many manufacturing industries. Reducing the waste of raw materials and managing the production schedule are important factors for such manufacturing. Nesting is an activity designing a cutting layout while scheduling is one managing operational procedures. Noting such nesting and scheduling in sheet metal processing, we need to consider those simultaneously for increasing the entire efficiency. This is because there often occurs a trade-off between them. To resolve such problem, we previously proposed an integrated method of nesting and scheduling. In order to enhance the scheduling ability that was insufficient in our method, this study extends the idea through a heuristic approach. Actually, we apply a local search to update the initial schedule which is decided by EDD based dispatching rule and manage it in terms of the criteria referring to the bottleneck process. Computational experiment is provided to validate the effectiveness of the proposed method.

A Meta-heuristic Approach for VRP with Simultaneous Pickup and Delivery Incorporated with Ton-Kilo Basis Saving Method

Under growing concerns with sustainable society, green or low carbon logistic optimization is becoming a keen interest to provide a plausible solution aiming at qualified service in global and competitive distribution system. As a key technology for such deployment, this chapter proposes a hybrid method of simultaneous pickup and delivery VRP aiming at rational framework available for real world applications. In its general procedure, the initial solution is derived from a modified saving method that consider the cost accounting known as Weber model or a bi-linear model of distance and weight. Then, it is updated by a modified tabu search to improve the tentative solution as much as possible. The idea is further extended to a non-linear or generalized Weber model. Numerical experiments are taken place to validate effectiveness of the proposed method through comparison.

Scheduling Based Collision Avoidance for Multitasking Machine

A scheduling based collision avoidance method for integrated or multitasking machine is proposed in this paper. This method consists of two procedures. One is the operation sequence sorting to find the most suitable machining schedule which has the least collisions during machining operation. The other is the dwell insertion to avoid the collisions which occur in the most suitable machining schedule. This method realizes the automatic generation of collision free NC program for integrated or multitasking machine. This method was implemented and applied to some computational experiments to verify the effectiveness of the proposed method. In the computational experiments, the proposed method is able to generate a collision free NC program automatically for integrated or multitasking machine.

GENETIC ALGORITHM BASED REACTIVE SCHEDULING IN MANUFACTURING SYSTEM –ADVANCED CROSSOVER METHOD FOR TARDINESS MINIMIZATION PROBLEMS–

ABSTRACT Recently, flexible scheduling systems are required to cope with dynamic changes of market requirements and manufacturing environments. A reactive scheduling method based on Genetic Algorithm (GA) was proposed, in the previous research, in order to improve an initial production schedule delayed due to unscheduled disruptions, such as delays of manufacturing processes. The objective of the research is to propose a new GA based reactive scheduling method for tardiness minimization scheduling problems, aiming at improving the disturbed production schedule efficiently and generating suitable production schedules faster than the previous reactive scheduling method. A prototype of reactive scheduling system is developed and applied to computational experiments.

A scheduling method using genetic algorithm and dispatching rule for sheet metal processing

In the sheet metal processing, nesting and scheduling are important design and operational tasks, respectively. The optimal cutting layout is determined by nesting for reducing waste of material while the optimal sequence is determined by scheduling for increasing efficiency of operational activities. Since we often encounter trade-offs regarding to their decision-making, they should be considered simultaneously. Accordingly, we previously proposed an integrated method of nesting and scheduling under a certain system boundary. In order to realize more efficient manufacturing, the punching process, which is the first process of sheet metal processing, should be considered. To work with this problem, in this study, we have extended our previous method by applying genetic algorithm for the optimization of sequence of punching process which depends on the cutting layout. Numerical experiment is provided to validate the effectiveness of the proposed method.

Deployment of Sustainable Logistics Optimization Incorporated with Modal Shift and Emission Trading on Carbon Dioxide

This chapter discusses a green logistics optimization problem associated with production method of manufacturers and green attitude of consumers. A novel hierarchical method is developed for a three-echelon logistics network to optimize the production methods with different structures regarding cost and emission of carbon dioxide (CO2) at production sites (PSs), the available collection center, the paths between members of the logistics network, and circular routes over consumers. First, the problem is aimed at minimizing either the total cost or CO2 emission through controlling prone and aversion behaviors on sustainability of each member. Then, as a promising glue to integrate these individual problems and to evaluate them on the same basis, an economic mechanism known as the emission trading rate on CO2 is introduced. Furthermore, to discuss the sustainability in a broader logistics system, the modal shift in transportation is noted. To show the significance of the proposed approach, a case study is provided to explore some prospects for green logistics in whole society based on the computational results.

Penalty Distribution Method for Scheduling Based Supply Chain Management

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain configuration is more adaptable by project based manufacturing environment characterize by the involvement of Small and Medium-sized Enterprises (SMEs). This research proposes a three echelons dynamic supply chain model where a job shop style manufacturer represents the center node being focused that will autonomously negotiates contracts with downstream client and upstream suppliers based on parameters derived from a reactive scheduling engine and an inventory management system. Furthermore a method is proposed to distribute delay penalties of previously contracted jobs to multiple new orders being negotiated simultaneously.

GA Based Reactive Scheduling for Aggregate Production Scheduling

A reactive scheduling method is one of the scheduling methods that improve an initial production schedule disturbed by environmental changes in manufacturing systems. In the previous research, Genetic Algorithm based reactive scheduling method have been proposed. In case of dealing with the aggregate production schedule, it is difficult to modify the initial schedule because of the unknown factors which occur in the manufacturing system. In this research, only part of the initial schedule is modified by setting the suitable scheduling range. Consequently, the reactive scheduling method can be applied for the aggregate production scheduling.