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 roll playing game based planning method considering both workload reduction and customers' satisfaction level. 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 maximizing the remaining hit point which is commonly used in the roll playing game. Finally, we validate the effectiveness of the proposed method through case studies.

The operators have to execute a various number of tasks and keep their skill level in the labor-intensive cell manufacturing system. However, operators can't work with the same task regularly. They forget the way of the task that is seldom assigned. Therefore, we need to consider about learning and forgetting factors of the operators. In this paper, we proposed an operator allocation and task assignment method using Depletion-Power-Integration-Latency (DPIL) model. After we perform computer experiments to adapt the DPIL model in the cell manufacturing system, we discuss the validity of the proposed method.

Given a directed bipartite graph with a finite set of items and a finite set of players, the problem discussed in this study asks to find an arc reversing strategy of the players which collects items under a budget constraint so that the total profit of the collected items is maximized. The weighted item collecting problem is viewed as a generalization of an integrated circuit design problem, and it is also a variant of 0-1 knapsack problems in graphs. A heuristic algorithm based on the simulated annealing is designed for the weighted item collecting problem, and numerical experiments are conducted to demonstrate the heuristic performance.

In this study, an algorithm is developed in order to generate the order of parts to assemble in assembly process for minimization of operation difficulty. The algorithm is based on Particle Swarm Optimization. Two factors generating operation difficulty are evaluated in the assembly process: status of obstacles to assemble a single part and unsteady status of semi-finished product. The factors are evaluated in the search process of this algorithm. In addition, a method is proposed to separate large scale of final product structure into small scale of semi-finished products by using matrix representing connection of parts. Finally, numerical experiment is performed to evaluate the effectiveness of the proposed algorithm by using simple structure product.

The operators have to execute a various number of tasks and keep their skill level in the labor-intensive cell manufacturing system. However, operators can't work with the same task regularly. They forget the way of the task that is seldom assigned. Therefore, we need to consider about learning and forgetting factors of the operators. In this paper, we proposed an operator allocation and task assignment method using DepletionPower-Integration-Latency (DPIL) model. After we perform computer experiments to adapt the DPIL model in the cell manufacturing system, we discuss the validity of the proposed method.

A mathematical model is developed to minimize total cost which consists of four cost factors in two-echelon supply network with product plants and retailers. Demand from retailers is assumed to be uncertain, so that robust optimization approach is applied to cope with the uncertain problem. In this paper, characteristic analysis of robust box uncertainty set is discussed.

The efficient use of energy and resources enhancing sustainability in manufacturing has become a crucial issue. We have been developing a measurement and control platform for smart green manufacturing system that can smoothly connect factory automation and manufacturing execution system. This study investigate the applicability of our developed manufacturing simulator based on the platform to electric energy capacity planning for a manufacturing system.

In this paper, we consider the guide path layout design problem considering guide path design costs and flow travel costs for automated guided vehicle (AGV) systems. A cell-based heuristics is proposed. The performances of model and heuristics are compared in the computational experiments.

In supply chain management, it is necessary to realize dynamically reconfigurable supply chains that can flexibly respond to the change to make an optimal decision-making. The game theoretical approaches have been widely used for supply chain planning which has various leader-follower relationship. In this paper, we develop an approximate solution algorithm to derive equilibrium solutions with several leader-follower relationships. The proposed algorithm is applied to pricing game and the production planning game for two manufacturers and single retailer case. The effects on the leader-follower relationship on supply chains are investigated from computational experiments.

The purpose of this paper is to present a comprehensive review of published literature investigating various methods and techniques for the automated fabrication of dental wire in orthodontics and prosthodontics applications from the past two decades. Formerly, the wire bending operation for the wire-related treatment in dentistry application was manually done in laboratory production. The traditional method is used around the world until a few innovations in the computer-aided manufacturing of the wire bending emerged to automate the orthodontics archwire bending. The application of these advancements is only focusing on the braces treatment for the lingual and labial orthodontics, while the other wire-related treatments in prosthodontics and orthodontics application are still traditionally performed in the hand-made operation. Therefore, the present study reviews the bending technique of each invention to automatically bend the wire, in an attempt to propose the idea of a flexible dentistry wire bending system. In addition, the development trend is foreseen, and the limitations are discussed.

Automatic welding machines can realize accurate welding work by computer control. However, understanding the welding status during welding operation is mainly conducted with visual inspection. It is expected that the quality of status judgment could be dramatically improved if welding information during operation is acquired by various sensors and the obtained information is displayed to the operator in real time when needed. This study builds a digital model of welding machine which integrates with sensor data. Furthermore, the study prepares a prototype desktop model, which corresponds to an actual welding machine, and enables to visualize welding status information using AR (Augmented Reality) technology.

Smart electric vehicles (SEVs) with self-driving ability are likely to become a common technology in near future therefore drivers are most likely very relaxed and become inattentively participate in driving processes. However, by viewing the SEVs solely from their electromechanical computing technology perspective are not holistic enough to encapsulate them as ideal smart vehicles. In other words, the SEVs with self-reliance on driving technology alone is not good enough without pertinent involvement of the drivers. In this paper driver's speech entrainment communication between a Line Follower Mobile Robot (LFMR) was evaluated and established connection between driver's mental states and performance of the LFMR. A speech recognition system evaluated driver's speech and classified them into three different mental states which were angry, anxiety and neutral then they were manually embedded into a Basic Stamp Microcontroller (BSM) on the LFMR. The BSM randomly combined two mental states in a set of serial sequences and translated into autonomous driving performance. Finally the performance was measured based on speeds, accelerations and travel periods. The LFMR attained the highest average speeds and shortest time travels whenever angry mental state was present meanwhile anxiety produced the poorest results in all mental state combinations.

Currently, verification of building information is based on estimation of historical data. Interaction between the real-world building's indoor environment and a digital yet realistic virtual representation model of building environment is known as digital twin. Where the indoor environment represents by the air temperature, air flow, relative humidity and lighting condition while, digital virtual represent by computational fluid dynamics and luminance level. Digital twin provides the opportunity on real-time monitoring and data acquisition. For instance, employment of digital twin enables gathering, generating and visualizing the indoor environment of building of interest. All gathered data will be stored in the digital twin subsequently, any irregularities will be analyzed. While computational analysis provides visualization of the facility of interest. The integration of this simulation tools to the internet of thing (IoT) represent as a real-time twin. This paper aims to present a conceptual framework design for building information management through the employment of digital twin approach. The proposed framework will be based on the principle conservation of resources and the design for convenient building information management in a large scale. On top of that, the framework design is expected to have appropriate balance between economic, social and environment issues, leading to better utilization of real-time monitoring technology and contribute to optimization of building services

Ergonomics is an important aspect of an industry and issue plays a significant role in the effective running of a company, so this issue is to be considered seriously. The ergonomic problems will affect the workers in a negative way; this will lead to a decrease in productivity and non-achievement of the target value. The goal of this study is identifying the ergonomics management impact on workplace productivity improvement. It is evaluated the influence on the human-job interaction at the workplace and is assessed the current status of the factory through the statistical analysis based on the ergonomics management system evaluation tool. The Kano model analysis has been used to prioritize the most crucial independent factors on work-related disorders through analysis of the Attractiveness, One-dimensional and the Must-be level of satisfaction of respondent.

This study systematically analyzed life cycle CO₂ (LCCO₂) emissions of a comprehensive set of mass-produced large sedan-type vehicles. ICEV (gasoline and diesel), HEV as well as BEV and FCV were investigated following current market trends. The results show that an annual average increment of CO₂ emissions in use phase by HVAC system in Japan (assumed annual average 15 °C) is evenly 8 %. The CO₂ emissions in use phase of BEV are higher than those of HEV and FCV (applied hydrogen produced by steam reforming of LPG (on-site)) due to current thermal power dominant electricity generation mix in Japan. As the consequence of high CO₂ emissions from power supply and battery pack production, the LCCO₂ emissions of BEV equipped with 75 kWh battery pack are equivalent to those of conventional ICEV (gasoline). By reducing the battery pack capacity to 20 kWh, the LCCO₂ emissions of BEV become lower than those of ICEVs (gasoline and diesel) and FCV (on-site). In other words, it is difficult that BEV mitigates both LCCO₂ emissions and driver's range anxiety. In conclusion, HEV shows the most competitive performance in terms of LCCO₂ emissions reduction with sufficient driving range in Japan.

Driving fatigue has been identified as one of the vital contributor factor to the road accidents among the Malaysian road user. The main objective of this study was to develop a decision support system framework for improving the driving fatigue problem. The decision support system aims to provide systematic analysis and solutions to minimize the risk and the number of accidents associated with driving fatigue. Four major stages involved as the pillar in the development of decision support system; acquisition of knowledge, integration of knowledge, development of driving fatigue strain index using fuzzy logic membership function, and development of ergonomics vehicle model and decision support system for driving fatigue model. Graphical user interface was used to communicate the system with users. The decision support system is an essential system to analyse the risk factors that would contribute significantly to driving fatigue associated with driving activity. Besides, the decision support system provide solutions and recommendation to the users in order to minimize the number of road accidents in Malaysia. In future, the author will carry further analysis and validation for this system to get the reliable system before it be commercialize.

The stress level of the worker is related with the workplace condition and satisfaction. Instead of stress level, working environment also can affect workers' performance. Basically, physical environment, work organization and psycho-social factor are the main cause of stress in the workplace. This paper is about the development environment monitoring system for the safe assembly task in manufacturing company. There are six potential useful parameter proposed in this study. The parameters include temperature, light, indoor air quality and noise. In this framework, the capturing device and signal converter are regarded as the main components. The monitoring system is proposed to capture all parameters in analogue signal and later convert it into digital signal using signal converter. At this stage, NI cDAQ-9188 is proposed to be used the signal converter in the monitoring system. The valuation test was held in ABC company at welding section. The aim of the valuation test is to know the result form the environment monitoring system is successful and compared to conventional method. It is hoped that the proposed monitoring system will benefit industry and promotes a safe working environment in industry especially in assembly task

The main goal of this study is to make a production schedule considering users' demand and improvement in production efficiency for mass customization. A proposed method using a Combinatorial Auction is applied to develop an optimal schedule in planning phase. In operational phase, a proposed method using a Single Auction approach is applied to insert additional orders quickly at idle time. To evaluate effectiveness of the proposed approaches, computer experiments are conducted.

Recently, crowdsourced manufacturing concept highly attracts. In crowdsourced manufacturing, each company shares their manufacturing resources to improve asset efficiency. To realize crowdsourced manufacturing, it is important how to make matching between resource offer and resource request which achieve high management improvement and in fair way. In this research, we propose analysis method of resource matching stability, and evaluate management effect and matching stability of some representative optimization methods. The computational results show importance of resource matching selection considering features of crowdsourced manufacturing system.

Diversification of customers’ needs has caused transition from low-mix high volume manufacturing to high-mix low-volume manufacturing. This transition has increased importance of job-shop scheduling. Because job-shop scheduling problem (JSP) is non-deterministic polynomial time hard, approximate optimization based on meta-heuristics have been actively discussed, and methods using simulated annealing (SA) have been proposed. SA has a disadvantage that good solutions cannot be obtained efficiently if the initial solution is not given appropriately. Methods for solving this problem have been proposed for JSPs aiming at minimizing makespan. In high-mix low-volume manufacturing, it is important to minimize average lead time in addition to makespan. For this reason, this research deals with development of an efficient method using SA for JSPs aiming at minimizing average lead time. A method of neighborhood limitation for reducing average lead time was developed by focusing on waiting time of operations, and an improved SA in which the neighborhood limitation method is used with a given probability was proposed. Effectiveness of the proposed method was shown by numerical examples.

In this paper, we study “caging-based grasping,” a new method for robotic manipulation. This method enables manipulators to grasp objects simply using position control, not force control. In our previous study, the target of caging-based grasping is limited to rigid objects. However, there is much demand for grasping deformable objects in the real world. The purpose of this paper is to extend caging-based grasping to deformable objects. We formulate caging-based grasping of deformable objects, derive concrete conditions for grasp synthesis, and validate this method through experiments.

This paper describes a data assimilation (DA) method for model state parameters in lifecycle simulation (LCS). DA is a self-adjustment method to decrease differences between a simulation and observed data from an actual-system by conforming the model parameters to the observations at appropriate time intervals. The proposed method applies DA to LCS for supporting product lifecycle management in terms material flow in the lifecycle. A case study on a lifecycle of a photovoltaic panel reuse business shows that the DA mechanism successfully merge observed data into material flow in a LCS model, and sequentially revise the simulation estimations.

In this report, we introduce application examples using AM(Additive Manufacturing )equipment. In the case of education, from measurement using 3D scanner We introduced an example of modeling. It is effective for texture expression. As examples of research, trial manufacture of stationery considering UD(universal design), Trial of complex modeling, observation monitoring system with a thermostatic chamber. Introduced. We are planning to announce the findings obtained from these results.

Energy efficiency in manufacturing processes has been an important objective because environmental impacts in industries have become severe problem in world wide. As additive manufacturing technologies are adopted to commercial-scale production, energy consumption in additive manufacturing processes becomes more important to reduce environmental impacts of the products. There is a need for the basic data acquisition to estimate environmental load of additive manufacturing facilities. In this paper, we propose the concept of web-based environmental load data acquisition and analysis system in distributed additive manufacturing facilities. Then, we discuss test results of monitoring and analysis example by using FDM type additive manufacturing facility.

In 2014, we set up a committee at Japan Society for the Promotion of Machine Industry (JSPMI) to evaluate whether 3D printing technology could help provide suitable work roles for people with disabilities 1). We conducted a three-year study to develop a business model based on subcontracting finishing work for the stereolithography from a 3D printing company to Social Welfare Corporations. Although the suitable work roles were limited to those in the final production processes such as removing, polishing etc., the finished quality of 3D-printed products were equal to that of where work was done by normal workers. The final processes are always to be done manually and the work is highly valued especially in prototyping. This combined with the quality of the workmanship demonstrated during the study made this business feasible. In this paper, this subcontracting business model and the results obtained from a three year trial are presented.

Recently, we developed the novel damper named as Passive Damper with Anisotropic Composite Structure (P-DACS). It is consist of metal and polymer structures. P-DACS can tune static and dynamic characteristics by controlling its anisotropic of stiffness with changing several design parameters and polymer material. Additive manufacturing technology allows realizing P-DACS and also mechanical structural members such as bearings, beams embedded the P-DACS. In this paper, the influence of design parameters on the whole static and dynamic characteristics of P-DACS, and evaluating its damping performance of table which is supported by P-DACS. As the results of numerical analysis, the specific stiffness and damping ratio of P-DACS can be controlled by the design parameters. Similarly the vibration characteristics of the table supported by P-DACS is able to control with the damper design.

We are developing a solution called "crowd manufacturing" which realizes a symbiotic manufacturing society with mutually interchange by sharing 4M (Man, Machine, Material, Method) resource information among factories and enterprises. In order to achieve improvement in capacity utilization rate, we developed a sharing platform for manufacturing facilities which enables visualization and sharing of schedule for facilities in different factories. This system provides environment for searching facilities in different factories, for requesting production, and for offering production, and enables mutual communication for confirmation and adjustment of specifications required for requesting production.

Most high-value-added workpieces have complex three-dimensional shapes such as aircraft parts. However, it is difficult to automatically determine the cutting procedure during a rough machining operation using a commercial CAM system because there is a large number of combinations to reduce the induced displacement and vibration of the workpiece. Therefore, in order to objectify the machining know-how of skillful experts, a determination method of cutting procedure is proposed based on topology optimization that solves the maximum static stiffness design problem. The determination method aims to reasonably improve workpiece stiffness and to automatically generate pillar-like supports for workpieces. A case study is conducted to confirm the effectiveness of the cutting procedure for complex parts according to the optimized workpiece shapes based on topology optimization. The result shows the possibility of achieving a high efficient rough machining operation to obtain the target shape.

Metal additive manufacturing (AM) attracts a great deal of attention from manufacturing industries. Thus, a multi-functional machine tool that has not only machining function but also AM function is recently developed to realize high flexibility and productivity. However, it is difficult to expect and control workpiece shapes created by AM. These workpiece shapes are slightly different from the 3D model assumed in advance. The differences may induce unexpected collisions on a multi-functional machine tool. Additionally, machining productivity may decrease when NC program is generated with an original 3D model which is different from the actual workpiece shape. Therefore, this study aims at realizing high efficient machining of complicated workpiece shapes corresponding to the actual workpiece shape as created by AM. Key Words: Complicated workpiece shape, Multifunctional machine tool, CAM, On-machine measurement, Structure from motion

In this study, an automatic process planning system for milling operation is proposed, in which user's intention for process planning is considered. First, our new process planning system stores the geometrical properties of the selected machining region when a user decides the machining sequence. After storing the geometrical properties, the appropriate machining sequence can be automatically selected by referring geometrical properties of the machining region. User's intention, which is involved implicitly in the stored geometrical properties of the machining region, can be applied to decide machining sequence. A case study was conducted to show the effectiveness of our new proposed process planning system. In the case study, user-specific machining sequences were automatically determined based on the implicit relation among the geometrical properties of the machining region and the individual user's intention.