Along with the diversification of customers' demand, there is an urgent need for a business model to realize the mass customization in automobile industry. When the volume and quantity of orders from customers is changing dynamically, it is difficult for a maker to realize both productivity and a variety of customers' specification by itself. So, we propose a new collaboration between the maker and supplier in a supply chain structure about ”load leveling” to supplier. Firstly, we describe a framework about the cost structure in accordance with ”load leveling” to the supplier and estimate the increased cost. Specially, we formulate the volume about load leveling and the maker's increased cost. Next, we derive the total increased cost estimator in the supply chain and analyze it. Finally, we get the optimal load leveling with minimum increased cost and get some information about designing the supply chain structure between the maker and supplier to realize mass customization.

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Output in high-volume production facilities is limited by bottleneck machines. We propose a control mechanism by modeling workstations as agents that pull jobs from other agents based on their current WIP level and requirements. During failures, when flows of some jobs are disrupted, the agents pull alternative jobs to maintain utilization of their capacity at a high level. In this paper, we empirically demonstrate that the proposed mechanism can react to failures more appropriately than other control mechanisms using a benchmark problem of a semiconductor manufacturing process.

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We consider a discrete-type split delivery vehicle routing problem, in which delivery goods for a customer consist of a set of items, each item is required to be serviced by exactly one vehicle, and each customer is allowed to be visited more than once. In this paper, we propose a fast algorithm that constructs a set of routes one by one without any improvement procedures. The algorithm generates routes by dynamic programming based on an elaborate route evaluation function that estimates the total travel cost required to service all the remaining items by vehicles. Experimental results on real-world instances are reported.

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This paper considers the part input problem of a production system where two Flexible Transfer Lines (FTLs) consisting of an up-stream production line and a down-stream production line while operating under Just In Time (JIT) production management. The up-stream production line processes the raw material after receiving them from suppliers, and after processing them, delivers the processed product to a down-stream production line via a conveyer. In this paper, we have proposed a novel idea for a part input real time control system, known as Algorithm for Real Time Control of Part Input Systems (ARTCOPS). The algorithm is useful when FTLs are in operation under a production order that is different from the pre-decided production schedule. Simulations of virtual production systems have been carried out to verify that ARTCOPS is useful in real time control, although the production orders are different from the pre-decided production scheduling.

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Recently, manufacturing industries face various problems such as shorter product life cycle, more diversified customer needs. In this situation, it is very important to reduce lead-time of manufacturing system constructions. At the manufacturing system implementation stage, it is important to make and evaluate facility control programs for a manufacturing cell, such as ladder programs for programmable logical controllers (PLCs) rapidly. However, before the manufacturing systems are implemented, methods to evaluate the facility control programs for the equipment while mixing and synchronizing real equipment and virtual factory models on the computers have not been developed. This difficulty is caused by the complexity of the manufacturing system composed of a great variety of equipment, and stopped precise and rapid support of a manufacturing engineering process. In this paper, a manufacturing engineering environment (MEE) to support manufacturing engineering processes using simulation technologies is proposed. MEE consists of a manufacturing cell simulation environment (MCSE) and a distributed simulation environment (DSE). MCSE, which consists of a manufacturing cell simulator and a soft-wiring system, is emphatically proposed in detail. MCSE realizes making and evaluating facility control programs by using virtual factory models on computers before manufacturing systems are implemented.

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Raw materials for industrial steel-making plants need to be stored in material yards in order to satisfy various production requirements. The stored materials are supplied to production plants by belt-conveyors with multiple alternative transportation routes. The simultaneous optimization of the storage allocation and transportation routing for the raw materials yard is required for achieving production that is flexible to changes in demand. In this paper, we propose a Lagrangian decomposition and coordination approach for storage allocation and routing for a belt-conveyor transportation system to handle demand changes. The overall problem is decomposed into an allocation planning subproblem and a transportation routing subproblem. A near-optimal solution for allocation planning and transportation routing is derived by repeating each optimization of subproblems and multiplier updates. The effectiveness of the proposed approach is confirmed in numerical experiments.

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Considering the need to develop general scheduling problem solver, the recent integration of Petri Nets as modeling tools into effective optimization methods for scheduling problems is very promising. The paper addresses a Petri Net modeling and decomposition method for solving a wide variety of scheduling problems. The scheduling problems are represented as the optimal transition firing sequence problems for timed Petri Nets. The Petri Net is decomposed into several subnets in which each subproblem can be easily solved by Dijkstra' algorithm. The approach is applied to a flowshop scheduling problem. The performance of the proposed algorithm is compared with that of a simulated annealing method.

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The productivity of machine tools is significantly improved by using microcomputer based CAD/CAM systems for NC program generation. Currently, many commercial CAD/CAM packages that provide automatic NC programming have been developed and applied to various cutting processes. Many cutting processes machined by CNC machine tools. In this paper, we attempt to find an efficient solution approach to determine the best sequence of operations for a set of operations that located in asymmetrical locations and different levels. In order to find the best sequence of operations that achieves the shortest cutting tool travel path (CTTP), genetic algorithm is introduced. After the sequence is optimized, the G-codes that use to code for the travel time is created. CTTP can be formulated as a special case of the traveling salesman problem (TSP). The incorporation of genetic algorithm and TSP can be included in the commercial CAD/CAM packages to optimize the CTTP during automatic generation of NC programs.

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