Recently, “Industrial Internet” and “Industry 4.0”, which refer to the integration of physical industrial machinery with software, internet, along with network sensors, actuators, and other industrial components, are discussed intensively. These technologies provide decantation of manufacturing with cloud-based manufacturing system (CBMS). Since the CBMS enables distributed manufacturing between connected companies, utilization of manufacturing facilities in these companies. As a result, these companies can reduce production cost. We investigate economical effectiveness of the distributed manufacturing with simulation study for machining shop. We also summarized system requirement and issues in industrialization.

It is significant in modern manufacturing to balance efficiency in both of the productivity and energy-saving under a predetermined peak power. This study deals with a cyber-physical simulator that can evaluate in real-time a planned process operation of a manufacturing system by measuring directly a production rate and energy consumption over time. We demonstrate the applicability of the prototype of a cyber physical manufacturing simulator being developed by using a miniature flexible manufacturing line without any computational manufacturing simulation, and investigates the effectiveness of the simulator for operations of a green manufacturing system.

This paper proposes a method which is to achieve an optimal scheduling and stock allocation planning simultaneously using a combinatorial auction under mass customization system. Proposal method decides a production scheduling and material stock allocation planning to aim minimizing the delay from acceptable delivery time. A numerical example is then discussed to demonstrate its suitability in obtaining an optimal plan under negotiations between manufacturer and customers.

In sheet metal processing, reducing the waste of raw materials and managing the suitable schedule are the important factors for the efficient manufacturing. The optimal cutting layout for sheet metal is determined through nesting. On the other hand, the manufacturing sequence for all manufacturing processes is decided through scheduling. Nesting and scheduling often become a trade-off. In our previous studies, therefore, we have proposed an integrated method of nesting and scheduling. In the previous study, the operational sequence of punching process is fixed because this sequence depends on the cutting layout. However, this sequence should be considered in order to obtain more suitable schedule. In this study, therefore, we propose a scheduling method by using the genetic algorithm and dispatching rule. In this method, we decide the operational sequence of punching process by using the genetic algorithm. Then we revise the schedule by using dispatching rule. Finally, we verify the effectiveness of the proposed method through some computational experiments.

In the sheet metal processing, there are two factors that should be considered in order to enhance the manufacturing efficiency. One is nesting, and the other is scheduling. To reduce the waste of raw material, the optimal cutting layout is determined through nesting. On the other hand, the operational sequence is optimized through scheduling. The relationship between them often becomes trade-off and hence they should be considered simultaneously. In this study, we propose a nesting-scheduling method by using Coevolutionary Genetic Algorithm (CGA). First, we define a cost function as a fitness value for typical genetic algorithm to evaluate nesting and scheduling result under the common measure. Then we propose a grouping method that forms groups of gene based on the cutting layout and the processing time of punching process in order to apply the CGA. Finally, we validate the effectiveness of the proposed method through computational experiments.

In recent years, the population in need of care have grown with rapid aging of the population resulting from the decline in the birth rate. Under such situation, the demand for nursing care facilities grows increasingly. On the other hand, the shortage of care workers is recognized as a social problem. The work of nursing care is very hard both physically and mentally, hence it is required to reduce the care workload. In this study, therefore, we propose a daily planning method in order to balance the workload of care workers. In this method, we decide the starting time of care services provided to users and the assignment of care workers for each service, under the objective of minimizing gaps of workload between care workers. Finally, we validate the effectiveness of the proposed method through case studies.

This paper proposes an efficient optimization method for job shop scheduling. Optimum schedules with regard to regular objective functions such as tardiness of jobs exist in the set of active schedules. Active schedules may insert idle times when machines became idle and there are waiting jobs. This decision of inserting idle times is difficult when searching optimum schedules. In the proposed method, the job which arrives a machine earlier is set to have a higher priority value using a weight value to avoid making the machine idle long time. Furthermore, when an idle time is inserted, the time length is considered when calculating priority values of jobs. Numerical experiments show the effectiveness of the proposed method by comparing it with the method using a look-ahead parameter.

Recently, IoT (Internet of Things) technology has spread in various industry fields, and Industrie 4.0 and Industrial Internet Consortium (IIC) have worked for making new standardization policies in manufacturing industry. In our project conducted in SIP program, a tailor-made design and manufacturing system based on IoT technology has been developed for value co-creation. In this paper, the brief overview of our project is presented and constructed value co-creative smart factory for tailor-made design and manufacturing system is described.

In recent manufacturing industry, complicated manufacturing system requires effective production scheduling method. On the other hand, the problem is complicated in the production line includes setup change and lot formation, to solve the exact solution is difficult. In this study, we propose structure analysis method to find a critical path of manufacturing schedule and apply the structure analysis method to lot reformation and machine re-allocation algorithm.

In this study, we illustrate a new practical approach to schedule the visiting routes for given stores having probabilistic maintenance demands. There are so many real situations like that. For example, an electric maintenance company has to visit the customer store in which electric equipment broke down, and to fix that. Though the maintenance company contracts with many customer stores, the stores should be visited on a certain day are a part of all stores. Besides, the company can’t know whether when and where maintenance demand occurs. This problem is defined as the probabilistic TSP(PTSP). We solve the PTSP by some meta-heuristic algorithms. An optimal allocation problem of a new maintenance base is also solved by our proposed method.

In recent years, manufacturing systems are becoming large-scale and complex more and more. Typically, they are referred to as hierarchical and decentralized manufacturing systems. To generate a suitable schedule for such systems, in this study, we propose a distributed and decentralized scheduling method by exchanging jobs between manufacturing cells. In this method, tardy jobs in a manufacturing cell are moved to another manufacturing cell repeatedly until total tardiness of all products satisfies given criteria. The effectiveness of the proposed method has been validated through computational experiments.

Layer manufacturing technique such as stereolithography is powerful tool to fabricate the 3D shape based on 3D-CAD data. The resolution of the 3D fabrication is limited by the spot size in x and y axis when we use laser to deposit the material by using the laser. As for the resolution in z axis, it is decided by the layer thickness to deposit the material. In the stereolithography by using the laser beam, the material is usually transparent. Thus it is difficult to control the solidification size in z direction, which is the direction of the beam propagation. We suggest a laser surface processing technique is investigated to improve the height resolution of layer manufacturing. In this study, make a challenge to achieve the processing on the surface with processing depth, which is lower than the layer thickness.

In recent years, the laser metal deposition (LMD) which clads layers by melting metallic powders with laser heating is expected to prevent wear or corrosion of products. An apparatus of LMD with a high power laser system is characterized by treating a wide range of large products at high speed. However it is difficult to treat thin and micro parts. In this study, an apparatus of LMD is developed with feeding metallic powder from the center of the laser head perpendicularly to the surface. As a result of cladding with Ni based SFA powder, it is possible to build up a thinner layer than 0.05mm with a narrower width than 0.4mm. And in the case of cladding with SKD11 powder, it is possible to build up a thin wall with width of 0.8mm and height of 2.4mm.

By intensification of the competition with the globalization of the production, the dynamic supply chain becomes popular. In dynamic supply chain, the company select the most suitable business partner dynamically, hence the negotiation is necessary for the business partner selection. In the previous study, it revealed that the gross profit of the whole supply chain increased when the negotiation was done based on the price and delivery date which was decided according to the stock quantity and the production schedule. However, the previous study did not consider the simultaneous negotiations with multiple customers because a breakdown of either negotiation affected the production schedule. Therefore, in this study, we propose a simultaneous negotiation framework for multiple customers. In this framework, negotiation is done based on a set of bids which is determined according to the multiple schedules. The effectiveness of the proposed framework is validated through the computational experiments.

To respond rapidly to global demand fluctuation at low cost, we need to develop the global supply chain management. In this paper, we present the optimizing method for shipping configuration from factory to distribution center. Our challenge is to reduce both assembly cost at each site and transportation cost from factory to distribution center. This technology consists of three functions: in the clustering function, it's to divide the similar order configurations into the some clusters by using the cluster analysis; in the selecting function, it's to generate the optimal shipping configuration from each cluster; in the planning function, it's to control weekly purchase order in order to balance box's order with option's order, and to create the optimal shipping configurations. We applied this technology and verified practical effectiveness of the optimal shipping configuration. As a result, our system contributes to reduce both assembly cost and transportation cost.

Environmental issues have become a serious problem in the last decade. We have been investigating a closed-loop supply chain model for reuse of used products. This study proposes a new negotiation model for further increasing the reuse of products and, thereby, reducing the waste. A simulation system of closed-loop supply chains is developed to evaluate the effectiveness of the proposed negotiation model.

This research proposes a scheduling strategy for suppliers to constantly obtain profits in global supply chains, in case where large scale disasters occasionally occur or not. Suppliers in the previous supply chain models minimize tardiness of ordered products in order to enter into a lot of contracts and reduce penalty charges for delays. A prototype of supply chain simulation system is developed to evaluate scheduling strategies of suppliers. We evaluate several scheduling strategies, such as the minimization of both the tardiness and the flow time through computational simulation in order for suppliers to find a suitable scheduling strategy in which the suppliers can manufacture the ordered products and deliver them before the occurrence of unpredictable disasters.

Due to advance of ICT technologies and global manufacturing, the decentralized decision making of multi-tier supply chains for multiple retailers and manufacturers becomes more and more important to achieve cooperative and collaborative production in global supply chains. In such situations, game theoretical approaches for supply chain optimization to analyze coordination mechanism, leader-follower relationship, conflicts, and contracts for different manufacturing facilities are highly requested. In this paper, we address the classification of game theoretical supply chain planning models. Some of basic models and application modes are introduced.

Initial tool setting errors that could be generated while setting a cutting tool deteriorates machining accuracy. However, it is difficult to prevent the occurrence of tool setting errors due to the manual setting process, which may increase in accordance with the number of the control axes. This study aims at developing a novel setting errors compensation method by using an on-machine measurement device and establishing an accurate tool setting technique that is independent of workers’ skills. By using an on-machine measurement device, it is expected that the tool setting errors are compensated with high accuracy and efficiency because of automatic detection of the actual tool control point. From the conducted experiments, it is found that the proposed method has a potential for achieving ultraprecision machining by compensating the tool setting errors.

Small radius ball end mills are widely used for a lot of products such as die and mold. This paper describes a prediction model of cutting force especially for small radius end mills, because an expression of uncut chip thickness is not correct for them. Hence, a new geometric expression of an uncut chip thickness is proposed, and a new cutting force prediction model accounting the expression change of the uncut chip thickness is constructed. A feasibility of them is described in this paper.

In order to cope with diversified customers’ needs, it has been required to realize the high-mix low-volume manufacturing. A mixed-model assembly line is a type of production line for satisfy the requirement, in which several similar products are assembled sequentially in the same line. To achieve high efficiency of the mixed-model assembly line production, it is critical to determine the product sequence suitably. There have been numerous works for sequencing problem and many methods have been proposed. They, however, do not take parts delivery into consideration, and the product sequence obtained by them may result in poor efficiency due to constraints in delivering parts. This paper provides an integrated method for sequencing and parts delivery planning by formulating the integrated problem as an integer programming.

Melting snow systems to prevent vehicle slips caused by the snowy as well as icy road condition have been introduced especially in heavily snowy area of Japan. Typical snow melting systems are based on electric heating method, groundwater utilization method and underground heat exchange method. In late years, from the viewpoint of energy-saving and environmental influence reduction, underground heat utilization method using ground surface heat exchange has been investigated. However, few studies to improve system operation efficiency have been reported. This paper proposes a control method of snow melting system tested in Bandai area where much snow is expected in winter. The main feature of the proposed system is feedforward control using latest weather forecast data focusing small local area. The system description such as data acquisition via. Internet and the feedforward input generation based on the snow forecast data is presented.

This research introduces an integrated direct technique for recycling aluminium wastes or scraps instead of conventional method which it will be carried out without melting phase. This technique is characterized by fewer steps and gives benefit on low energy consumption and operating cost. In this paper, it will focus on the powder metallurgy process and Aluminium Alloy 7075 (AA7075). It reveals the performance of recycled aluminium chips on their mechanical properties and surface integrity (microstructure) by comparing them with the original aluminium one. In this research also, it is expected to reveal the possibility of this recycled aluminium chips to be used as a secondary resources as an alternative to overcome the shortage of primary resources. Analysis of the microstructure, density and microhardness were conducted to evaluate the performance of recycled AA7075. The AA7075 was added with alumina and graphite. The microstructure analysis was carried out using field emission scanning electron microscopy (FESEM), while mechanical properties have been study using Electronic Densimeter and Micro Vicker Hardness Tester. The results show that the density of recycled Al7075 is varies between with and without addition of alumina and graphite. As the temperature of sintering process increases, the density increased. The alloy’s microstructure sintered at 650^oC has the highest density which shows dense compare to sample with no addition that shows porosity. The microhardness of the samples with the addition of graphite are higher than the samples with and without alumina that range from 61.7 to 71.0 Hv.

In current manufacturing industry, the demand for long-term repeatability of robots increases. We propose new thermal error models for robot arms based on the linear expansion of links. As a result of our experiment, the behavior of our model is quantitatively consistent with the experimental data. Our model can be used for correcting thermal errors, which contribute to realizing long-term repeatability of robots.