In the manufacturing field where machine tools are used, electrical vehicles, aging, and IoT have been important keywords. Although an automobile has been a byword for a product for mass production, the number of mass production processes to manufacture the same parts will be reduced because the number of components in the powertrain will be significantly reduced due to the transition to electrical vehicles. More and more new materials will be used to reduce the weight of automobiles, which means die and mold production will be demanded instead. In the aging society, the demand for implants and medical equipment will be significantly increased. Furthermore, growing demands from the semiconductor industry in the IoT boom bring momentum to the machine tool industry. The manufacturing style is rapidly changing from mass production of the same parts to high-mix low-volume or custom-design production. On the other hand, lack of experienced engineers has been a serious problem in both developed countries and developing countries. For machine tool manufacturers, providing not only machine tools but also engineering is an important task. Furthermore, promoting automation in high-mix low-volume production is even more important. To tackle those tasks, machine tool manufacturers must work on development of automation technologies for long-time automatic machine operation, improvement of machining accuracy, effective chip disposal and production of machines that never stop. This keynote speech is about effort to achieve these goals by using IoT and sensing technologies and what the machine tool should be in the future.

Advanced mobility research center, Institute of Industrial Science, The University of Tokyo conducted projects for development and evaluation of automated driving system for sustainable transportation system of next generation. Automated driving is expected to be implemented socially as next-generation mobility. Changing the mobility society may lead to improvement of productivity of Japan, Asian countries, and all of the world. It is important to build a business ecosystem. Development of research on sensing technologies, artificial intelligence, and control engineering for automated driving should be improved. However, more important things is technologies of HMI (Human-Machine-Interface) technologies to establish and consider the social acceptance of automated driving system. Not only driver but also people for transportation around the automated driving vehicle should accept the new system. Moreover, non-technical issuers such as legal and management matters should be considered. In this presentation, recent trends for consideration of ecosystem will be introduced. In Japan, a lot of demonstrated experiments on the public roads are conducted under the newly authorized rules by Japanese government even for driverless operation. Some of the examples will be shown. For future prospects, such as social acceptability considering the impact on users and industry will be presented showing experiments of business model in local community.

Integrated Computational Materials Engineering (ICME) hinges on engineering microstructural features into the materials design process where the overarching goal is to search for materials with superior structure-level performance while systematically accounting for various sources of uncertainties, including those introduced by manufacturing processes. Quantification of manufacturing induced uncertainties is significantly challenging since they are multi-dimensional, spread across different length-scales, spatially correlated, and embody different characteristics (e.g., topological vs. property-related). In this talk, we address these challenges by presenting a non-intrusive computational approach for multiscale and multidimensional uncertainty quantification. We introduce the top-down sampling method that allows to model non-stationary and continuous (but not differentiable) spatial variations of uncertainty sources by creating nested random fields. We employ multi-response Gaussian random processes in top-down sampling and leverage sensitivity analyses and supervised learning to address the considerable computational costs of multiscale simulations. Examples with carbon fiber reinforced polymer (CFRP) composites will be used to illustrate the broader impact of the uncertainty quantification methods for reducing the production costs by guiding the manufacturing and quality control processes.

Recently new technology emerges for innovating design and manufacturing activities. It is well recognized the influences of advanced ICT, IoT, model-based engineering and system engineering. The innovation is generally called as smart manufacturing. Core technology of smart manufacturing is comprehensive digitalization of whole products and processes, which enables completely new system architecture. A manufacturing system becomes a system of systems, which is open and flexible to configure and manage. Traditional engineering chains and supply chains will be re-configured into flexible network configurations. Direct process-to process communication becomes possible, and enables to realize connected smart products which exhibit new services and value additions to product customers. In these innovations, IT itself cannot create any new systems, but vision and concept for manufacturing come first, and a system is realized by IT. IT platform is an IT system framework for architecting and implementing a target system by utilizing component systems and modules, and will play an important role as a new work space for an industrial ecosystem. This presentation will review recent trends of smart manufacturing, identify core technology and methods for innovations, and discuss the practical approach based on IT platforms. Some examples from industries and national projects will be shown.

Inconel 718 has high temperature strength and corrosion resistance, and it is used for turbine blades such as those used in gas turbines. However, turbine blades must be repaired to extend their product life, because they are used in highly heated centrifugal fields, and often experience damage such as cracks, breakdowns, and oxidation thinning. We sought to perform additive fabrication onto the thin end of a plate using WAAM and cutting to repair turbine blades using Inconel 718. We were able to roughly fabricate a wall structure with of the target lamination width of +2 to +3 mm for plate thickness onto a thin end of a plate with a thickness of 5 mm while maintaining a constant interlayer temperature. In addition, we performed cutting to the wall structure onto the thin end of the plate, and showed that additive fabrication can be performed with almost no defect.

The present study discusses a design method for controlling a twin-motor system, where a shaft is actuated by two direct-current (DC) motors. In order to optimize controller parameters such that the trajectory of the rotation speed of the shaft follows that of the reference model, fictitious reference iterative tuning (FRIT) is used. To decide the controller parameters of a two-input one-output system using FRIT, the system is designed as a dual-rate system. Finally, the designed controller parameters are applied to an experimental setup, and its effectiveness is demonstrated.

In this study, the two-dimensional structure with negative Poisson's ratio was built using the powder bed fusion (PBF) process which was one of the additive manufacturing method, and its mechanical characteristics were investigated. The unit cell was designed based on the topology optimization and the homogenization method. The bead model including the unit cell size of 20 × 20 mm was built, and the tensile test was performed by a universal tensing equipment. The bead model during the tensile test was captured by the digital camera, and the Poisson's ratio was evaluated by the digital image correlation method. The metal powder used was a mixture of chromium molybdenum steel, copper alloy and nickel. As results, the width of the bead model was increased as the bead model was extended by the tensile test. The Poisson's ratio calculated was -0.55. The difference of the Poisson's ratio between the target value and the calculated value was due to the limitation of the PBF processes. The micro structure in the designed model was filled by the partially melted powder which was formed around the built structure, and resulted in the decrease of the Poisson's ratio.

Nature provides inspirations of creative multi-functional materials and structures. However, biological systems are usually composed of materials and structures in multi-scales with high geometry complexity, which brings challenges to bioinspired design and fabrication. Additive manufacturing (AM) presents a potential solution due to its capability of creating three-dimensional (3D) objects with freeform surface and multi-materials. The aim of this research is to investigate the fabrication of multi-scale biomimetic structures using the integrated photo-polymerization based 3D printing processes. We firstly introduced the macro- and meso-scale mask image projection based stereolithography (MIP-SL). We then present the micro-scale immersive surface accumulation (ISA) printing. Based on them, a multi-scale 3D printing method by integrating the ISA and MIP-SLA processes is presented. To achieve high-resolution fabrication, the process planning, the material curing performance, and the printing parameters are discussed. Two test cases are presented to demonstrate its fabrication capability. The experimental results verify the accuracy and efficiency of the developed multi-scale 3D printing method on the fabrication of bioinspired structures with functional surfaces.

This research presents an examination of the Abrasive Blasting technique (Sandblasting) as an alternative for the surface treatment of Additive Manufacturing products obtained through Fused Filament Fabrication (FFF) method. The growing popularity of this kind of manufacturing brings more attention to its problems, and being the final product surface aspect, a known problem of this method, this research aims to find alternatives to the usual surface finishing techniques. The focus of this research then, was the surface quality of FFF products, and to analyze this quality, values of Surface Roughness (Ra) was used as a primary tool, being aided by microscopic pictures and F profiles from a profilometer. Another aspect of the research was the tensile strength analysis. It was considered important that this mechanical property was examined to understand the effects that the abrasive blasting treatment could bring to the additive manufactured products.

A cross-spring flexure pivot with variable cross-section is studied in this paper, with the purpose of overcoming the disadvantages of the conventional cross-spring flexure pivot with uniform cross-section, such as axis drift and low axial stiffness. The work started with deducing the load-displacement relationship of a variable cross-section spring leaf by using the improved Awart’s beam constrained model. Then, a mechanical model of the proposed flexure pivot was established. The effectiveness of the deformation model is verified by finite element analysis. Finally, the proposed flexure pivot is compared with a conventional one, and the results show that the flexure pivot with variable cross-section has a higher rotational accuracy and a higher axial support stiffness.

This paper studies control approaches to advance the quality of repetitive energy deposition in powder bed fusion (PBF) additive manufacturing. A key pattern in the nascent manufacturing process, the repetitive scanning of the laser or electron beam can be fundamentally improved by repetitive control (RC) algorithms. An intrinsic limitation, however, appears in discrete-time RC when the exogenous signal frequency cannot divide the sampling frequency. In other words, N in the internal model 1/(1−z^−N ) is not an integer. Such a challenge hampers high-performance applications of RC to PBF because periodicity of the exogenous signal has no guarantees to comply with the sampling rate of molten-pool sensors. This paper develops a new multirate RC and a closed-loop analysis method to address such fractional-order RC cases by generating high-gain control signals exactly at the fundamental and harmonic frequencies. The proposed analysis method exhibits the detailed disturbance attenuation properties of the multirate RC in a new design space. Numerical verification on a galvo scanner in laser PBF reveals fundamental benefits of the proposed multirate RC.

A 4-axis turning center realizes cuttings from axial and radial direction for side milling，face turning and so on by changing cutting tools on its turret．In a sense, tool posture can be controlled by tool change on the machine tool．However, high degrees of freedom of its tool posture is not fully reflected to complexity of its machinable shape since the operation of tool posture including tool change cannot be seamlessly treated in conventional CAM system[1]．In the study, a CAM system whitch realizes complex shape applying different direction of tools seamlessly as a means of control of tool posture, called "4.5-axis CAM" for turning center, is proposed. In the report, concept of the CAM system and example of tool paths actually generated by the system are shown.

For turn-milling process using multi-tasking machine, some process parameters such as depth of cut, feed rate, rotational speed of workpiece, spindle speed, relative angle between tool axis and workpiece, and offset of cutting position influence on cutting force variation and tool wear. However, there exist little investigations for the effect on cutting state by those machining parameters. In this paper, the combination of machining parameters and cutting process is defined for the turn-milling process with bullnose mill. Furthermore, this paper proposed a method to calculate the effect of tool posture for turn-milling by analyzing contact area between workpiece and tool modeled as point-cloud.

BL-PCD is expected to be an excellent material for a micro cutting tool because it is the hardest material in the world. Micro tools are used for the direct machining of high precision die and mold, and conventional PCD tools are often used for such precise machining in general. However, conventional PCD tools are insufficient when it comes to wear and chipping resistance. To study the unique die and mold machining application using a micro end mill made of BL-PCD, systematic experiments involving the machining of ultrafine grain tungsten carbide alloy have been conducted. In the study, tool wear and machined surface quality of tungsten alloy material have been evaluated in relation to the machining conditions and machining process parameters. The results have justified the superior performance of BL-PCD micro end mill, as compared to results obtained in the machining experiment based on a regular PCD micro end mill, which has the same tool geometry.

This study presents a fundamental estimation method of drilling characteristics of carbon fiber reinforced thermoplastics (CFRTPs). To simplify the evaluation of the relation between the drill rotation angle and the fiber orientation, a unidirectional CFRTP was used workpiece. The waveform behavior of the thrust force during drill rotation and the quality of the drilled hole entrance were investigated. The thrust force reached its maximum during drill rotation when the tangential direction of the rotating peripheral corner edge of the drill coincided with the fiber orientation of the workpiece. The relationship between the drill rotation angle with respect to the fiber orientation and the generated burrs and chippings on the edge of the drilled hole entrance were observed.

Niobium-Titanium (Nb-Ti) alloy is composed two elements, niobium and titanium, which have extremely low cytotoxicity, and has excellent corrosion resistance. Moreover, Nb-Ti alloy has a Young’s modulus similar to that of human bone, and so is suitable as an implant material. Although manufacturing and shaping implants requires cutting processes to be performed, there has been no research on the cutting of Nb-Ti alloys, and the processing characteristics of Nb-Ti alloys have not yet been clarified. In the present study, the influences of tool material and cutting speed on tool life were investigated by milling of Nb-Ti alloy using a small ball end mill tool. The results of these investigations indicate that the tool life can be extended by using a diamond-coated tool and that a cutting speed of 8.0 m/s provides the longest tool life.

The vibration trajectory of an ultrasonic elliptical vibration cutting tool is critical for its performance in vibration-assisted cutting/texturing. The shape and amplitude of vibration trajectories will significantly affect the surface quality, tool life, and material removal mechanism. The tool trajectories are often unregulated in current practice due to the difficulties in direction measurement during cutting. In this paper, an analytical model based on the feedback signals from piezoelectric plate sensors has been proposed for the prediction of tool vibration trajectory. The proposed model calculates the elliptical vibration trajectory considering the mode superposition of two orthogonal resonant modes and the measured sensor amplitudes and phase angles. The relationship between the excitation voltage and frequency and the model parameters were studied and calibrated. Experiments were conducted to evaluate the model accuracy and to verify the feasibility of online prediction of the tool trajectory.

We conducted milling experiments of Ni-based super alloy by use of the developed milling cutter with Self-Propelled Rotary Tool (SPRT). Experimental results verified that the tool life is increased 12 times as compared with the conventional milling without insert rotation due to tool wear suppressions. Cutting process parameters were also identified by inverse analysis of the cutting forces. The identified parameters may be available for advanced estimations in tool geometry and machining quality. On the other hand, disadvantageous characteristics in ramping process were revealed due to flank face contact.

Machining accuracy of the part which has low-rigidity is greatly influenced by cutting deformation in milling process. Prediction of cutting deformation could effectively decrease surface errors of the part through optimizing tool path or cutting parameters. In this paper, deformation mechanism of the workpiece during milling process is studied by simulation method and cutting tests. The analytical model of cutting force is established, and the model of temperature field during milling process is built to predict cutting heat of the workpiece. Model parameters of cutting force and temperature are determined to satisfy the current cutting conditions based on several orthogonal experiments. Cutting deformation of the workpiece at different time could be calculated by finite element method under coupled thermal-mechanical conditions. According to the experimental results, the proposed simulation method could minimize the error between the calculation value and detection value in terms of workpiece deformation.

In recent years, the further miniaturization of products and machine parts is progressing. On the other hand, the size of the machine tool has still remained from the conventional size. Since the rigidity is regarded as the most important in the design of machine tools, therefore downsizing of machine tools has not considered much [1].
Therefore, we propose a unique machine tool which consists of hollow CFRP pipes, and it has driven by the original NC controller. It has truss structure, thus we can save the space for setting machine tools. In addition, it has also the enough high rigidity [2].
In this paper, it will reported the measurement results of positioning accuracy. Thus, we solved the torque deficiency to drive with harmonic drive reducer unit. In addition, we also estimate its control performance when simple machining test is carried out with this machine tool.

S-shaped test piece has been proposed by China as a method to evaluate the finishing accuracy of 5-axis machining center. In this test, machining accuracy of a 5-axis machining center is evaluated by measuring the shape error of a workpiece machined by 5-axis simultaneous control of an inclined S-shaped part with a flat end mill. In this report, among the series of draft standards proposed by China, the method given in September 2016 which is the newest executable one is examined using a medium-size vertical 5-axis machining center and checked its validity.

A three-dimensional (3D) printer using the fused deposition modeling (FDM) method generally has a 3-axis configuration. However, with this method, the posture of the workpiece is fixed and the shape of the 3D model is restricted. Use of support material can solve this problem, but at the cost of extra material and laminating time. The purpose of this research is to make shapes that are difficult to laminate with 3-axis 3D printers without using support material. Therefore, we developed a 5-axis 3D printer, its control program, and 5-axis laminating paths. As a result of laminating experiments using the developed 3D printer and laminating paths, it was possible to make an overhang shape without using support material. Thus, it is possible to make 3D objects faster and more efficiently with a 3D printer having a 5-axis configuration. In this paper, the basic configuration and the control system are reported.

This study deals with a new method of the compliance measurement in cutting process on a CNC lathe. In general, the impact test is widely used to measure frequency response functions (FRF). However, this test cannot be adopted during cutting process in terms of danger and accuracy of measurement. Therefore, a new method of the FRF measurement that the turning process itself becomes frequency-sweep excitation is proposed. In this paper, our method is explained first, and a comparison experiments between results of the conventional impact test and our proposed method is described. As the result, it was confirmed that the measured natural frequencies was slightly different between these tests.

The stiffness of machine tools is a key factor to increase the productivity. The dynamic stiffness dominates the stable cutting conditions, where forced and regenerative chatters do not occur. In general, dynamic stiffness is measured using an impact hammer as it does not require the particular device setting. However, humans should use a hammer and impact control needs skills. To this end, several researches have been conducted to establish automatic excitation methods. To measure the dynamic stiffness of a rotating spindle, authors have developed an electromagnetic biaxial excitation device which can generate biaxial force. This paper presents the measurement result of dynamic stiffness for both the structure and spindle of a five-axis machining center using the developed device.

In this paper, we propose a novel 3D shape representation method called “radial ray representation (3R)”. In this method, a solid shape is recorded by a set of dense rays radially expanding from a single point. This representation is especially useful for determining the optimal cutter posture in the 3+2 axis milling of a mold part. As a measure of the appropriateness of the cutter posture, the peak angle of the accessibility cone (AC) is used. In the appropriate postures, we select the optimal one as the tool posture with possible shortest cutter length without holder collisions. We developed 3R model based algorithms for computing the AC and for selecting the optimal cutter posture. We also propose a fast method for obtaining a 3R model using the polygon rendering function of the graphics processing unit. An experimental system is implemented and some computation results are demonstrated.

A novel approach is proposed for the path planning of the aircraft tail in automated fiber placement (AFP), which combines the fixed angle path planning algorithm with the isometric offset algorithm. In this method, the fixed angle path planning algorithm is used to generate the tows centerline (i.e. the placement trajectory) and boundary line, and the isometric offset algorithm is used for the single tow path. Post-processing is also studied in this paper, including the insertion of auxiliary control points, the connection of tows centerlines and the inverse kinematics of the AFP machine. Finally, the generated G codes are verified on a virtual machine tool in VERICUT.

Off-line teaching systems are becoming the mainstream method of making a robot program, as opposed to a teaching playback method that requires the technical skill of a worker. The off-line teaching system enables to make the robot program on a computer and allows the simulation of robot motion by checking the program. However, to make an optimal program with consideration to the prevention of sudden change in the robot’s motion, singularity should be avoided and workpiece placement should be optimized. In particular, to determine the workpiece placement, the operator must perform many trial and error operations. In this paper, we propose an optimization method for workpiece placement during a sealing operation by using an industrial robot. This method is based on manipulability, which is a measure of the robot’s manipulating ability. We confirmed the effectiveness of the proposed method by applying it to an actual sealing process.

Die and mold are necessary to produce present industrial products. In recent years, it is strongly required that the complicated surfaces are machined with high quality and low cost. However, it is difficult to generalize process planning that still depends on skillful experts and decreases the efficiency of preparation in die and mold machining. In order to overcome an issue that is difficult to be generalized, it is well known that neural network has a possibility to estimate a valid value based on past case data. Therefore, this study aims at developing a computer aided process planning (CAPP) system to determine tool path pattern for die and mold surfaces by using NN and past case data. From the result of conducted case studies, it is recognized that the developed CAPP system is helpful to determine tool path pattern even for complicated surfaces according to the implicit machining knowhow.

An automatic process planning system for end-milling operation is proposed, in which CAM operator's intention for process planning is considered. In the previous process planning systems, the machining sequence is calculated geometrically. However, it remains difficult to determine the best machining sequence from the large number candidates of the calculated machining sequences. The previous process planning systems also do not consider CAM operator's intention in the determination of the appropriate machining sequence. First, our new process planning system stores the priority of machining features to be machined and the geometrical properties of the selected machining region from operations of CAM operators to decide the machining sequence. After storing the priority of machining feature and the geometrical properties, the appropriate machining sequence can be automatically determined by reflecting these information. CAM operator's intention, which is involved implicitly in the stored geometrical properties of the machining region, can be applied to decide the appropriate machining sequence.

Filament winding is an efficient method to produce fiber-reinforced composite product. However, it is difficult to automatically manufacture tee pipe by filament winding because of complex shape. In this paper, a key point based method is proposed to generate winding path for tee pipe. The key points are connected by two non-geodesic lines with different slippage tendency to ensure the stability of filament. The motion path of deposition head is generated by calculating the intersection between filament and envelope. For the problem of collision and unexpected intersection between filament and pipe occurred in winding, post processing method is developed to adapt motion path by inserting points on the discontinuous path.

In this paper, a new criterion for evaluating speckle pattern in DIC method is proposed. In our study, the authors assumed that the identification of unknown parameters by inverse analysis using strain field measurement based on digital image correlation (DIC) is promising because there are many possible applications: in-process monitoring of metal working, extraction of implicit know-how of manufacturing process, and identification of mechanical parameters not only in industrial materials but also in inhomogeneous biological materials. To establish this method, it is difficult to construct a useful physical model, an efficient reverse analysis process, and the measurement quality evaluation criteria. As a first step, this paper focuses on evaluating the quality of transitional speckle patterns on the surface of objects during large deformation.
Although the quality of the speckle pattern greatly affects the number of search errors, it is difficult to evaluate the quality reliably by a single criterion such as the mean subset fluctuation or Shannon entropy proposed as the quality evaluation criterion. Therefore, a new criterion FE is proposed and its characteristic is investigated through experiments.

Lattice structures fabricated by Additive Manufacturing (AM) processes are promising for many applications, such as lightweight structures and energy absorbers. However, predicting and controlling of their mechanical behaviors is challenging due to the complexity of modeling and the uncertainties exist in the manufacturing process. In this paper, we explore the possibilities enabled by controlling the local densities. A set of lattice structures with different density gradients are designed using an implicit isosurface equation, and they are manufactured by Selective Laser Melting (SLM) process with 304L stainless steel. Finite element analysis and compression test are used to evaluate their mechanical properties. The results demonstrate the strong correlations between the structural gradient and the mechanical behavior. Introducing the density gradient provides more possibilities in the design phase, which can be used to further customize the design both structurally and functionally.

Multi-scale computer aided design (CAD) systems for product design are particularly suited for additive manufacturing. A concept for a new design and manufacturing system using the multi-scale CAD system and additive manufacturing machines is proposed. The design and implementation of the multi-scale CAD system are proposed.

Topology optimization for additive manufacturing has been limited to designing parts smaller than the printer's build volume. To enable the design of structures larger than the printer's build volume, this paper presents a gradient-based multi-component topology synthesis for designing structures assembled from components made by powder bed additive manufacturing. The manufacturing constraints on the maximum allowable build volume (which is limited by the machine specification), the elimination of enclosed holes (which will trap un-melted powders inside), and the minimum printable feature size are modeled and incorporated in a gradient-based multi-component topology optimization framework. As a result, the manufacturability of each constituent component is satisfied. Numerical results of multi-component topology designs optimized for the minimum compliance subject to powder bed additive manufacturing constraints are presented. The resulting multi-component designs unlocked richer design space for early-stage topology exploration.

The objective of this research is to construct a process model of workholding process which can be connectable to end-milling process simulation. Workholding process has been assumed to be represented as a simple linear elastic deformation process with solid contact boundaries. It however has reported actual workholding processes show various difference from the simple elastic analysis. In order to clarify influential factors of workholding uncertainty, experimental investigations of workholding with operational variations are conducted. From the results of the experiments, it becomes clear that fixturing sequence and loading increments affect workpiece deformation.

On-machine-Measurement (OMM) is the measuring on the machine tool and getting the result of machining instead of measuring on a measuring instrument. OMM doesn’t require the desperation and repositioning process, so the shortening the lead time for inspections is achieved. For execution of OMM the operator should set measurement strategy, such as measurement item, the number of measuring points and the position, to generate a NC program for the measurement.
In this study, our aim is the automation of those preparation tasks required time and effort, especially touch trigger probe which is introduced for NC machine tools is utilized. Our proposed system automatically recognize the machining feature from the Total Removal Volume (TRV) detected between the CAD models of product and material, and decide the measuring strategy. Therefore, the NC program for executing OMM with touch trigger probe is automatically generated. A case study was conducted to show the effectiveness of the developed OMM system.

Metal additive manufacturing (AM) attracts a great deal of attention from manufacturing industries. Thus, a multifunctional 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. The differences may induce unexpected collisions on a multi-functional machine tool. Additionally, even though machining productivity is affected by the arrangement of target shape, it is difficult to decide the target shape position and orientation according to complicated workpiece shapes. Therefore, this study proposes a decision method of target shape position and orientation using workpiece shape obtained by on-machine measurement to realize high efficient machining of complicated workpiece shapes as created by AM on a multifunctional machine tool.

Recently, many people have taken a physical exercise for their shape-up/beautiful body in the world. Deciding the goal of weight or size is easy, but its shape is very difficult. Then, we focus to relate the beautiful body shape with the log-aesthetic curved line. The log-aesthetic curved line has characteristic that the curvature is constant multiplier of curve length, and the natural shape object follows it. In this paper, we build up a hypothesis that the body line fitting the log-aesthetic curved line is curvaceous, and the body parts shape is determined for curvaceous parameter using the hypothesis. Firstly, the male body parts and female doll parts are captured, and compared the similarity of curvature to a log-aesthetic curved line. Afterwards, we investigate the curvaceous validity of physical exercise. The before and after exercise thighs are compared, and we analyze the curvaceous similarity of a log-aesthetic curvature for analyzing the correlation of physical exercise and curvaceous in 3 months.

Sheet metal processing is one of popular machining technique. In sheet metal processing, the parts are cut from sheet metal as many as possible in order to reduce the waste of material. The parts cut from sheet metal are processed by the given due date. In order to keep due date, scheduling is important. The optimization of cutting layout and that of schedule are called nesting and scheduling, respectively. The relation between them often become a trade-off. In order to enhance the efficiency of entire manufacturing activities, they should be considered simultaneously.
In this study, therefore, we propose an environment-adaptive GA based nesting scheduling method. We consider nesting and scheduling as different environments, and the cutting layout and the processing order of parts evolve under each environment by using genetic algorithm.

In this paper, two intermittent feedforward functions, called posicast shaped function (PSF) and vibration manipulation function (VMF), are compared to suppress residual vibration of an undamped oscillator, such as an overhead travelling crane. The conditions of posicast shaper are limited, such as intermittent operational period, no feedback control, constrained application for a one-time rest-to-rest motion and requirement of an original command. On the other hand, operational period of VMF is not restricted into an integer times of the natural period of the target oscillator. Since VMF can make the object into the arbitrary aimed state after each operation, the remaining vibration can be additionally suppressed by the next operation under discrete sampled-data control. In this study, we will simulate to control an overhead travelling crane for a rapid rest-to-rest transfer by using these methods under certain noises or non-linearity. We will show advantages of VMF for the suppression of residual vibration in these circumstances.

In flexible manufacturing systems, the importance of automated guided vehicles is increasing because they can respond flexibly to changes in facilities and factory layouts. We propose an autonomous conveyance system for automated guided vehicles based on the operation of a taxi transportation system to solve indefinite and accidental problems. The system focuses on applying traffic engineering knowledge regarding a flexible taxi transportation system. A taxi is a transport unit in a traffic system involving high flexibility in traveling routes and at arrival/departure points. In this report, we suggest quantifying a driving course shape using a network Voronoi diagram. As a result, by using the weighted network Voronoi diagram and the coefficient of variation CV, a correlation is obtained between the variation coefficient CV and the average matching time T_a, and an appropriate path can be arranged to determine the course shape.

This paper presents a mixed integer bi-level dynamic hub location problem for freight transportation. The problem is formulated as a mixed integer bi-level optimization model. The upper-level problem maximizes the profit of a freight company and the lower level problem minimizes the cost paid by costumers. The bi-level problem is reformulated into a single level model using the KKT reformulation and a numerical example is provided to show the validity of the proposed model.

A new investment planning method is proposed to determine purchase of suitable production equipment considering demand fluctuations by using portfolio for manufacturing systems consisted of CNC machine tools and jobs in this research. The portfolios are set to consider candidates of the purchasing production equipment for investment.
Returns and risks considering demand fluctuations of the individual portfolios are required in order to select the best portfolio in the proposed investment planning method. The returns and the risks of the portfolios are calculated under assumptions that candidate production plans and probabilities that correspond to demand have already been obtained. Estimated profit is required to calculate the returns and the risks of the individual portfolios. The profit is estimated based on the cases where the production plans are carried out by using the purchased production equipment and existing equipment.
Evaluation method of the obtained portfolios is also proposed based on information ratio in this paper.

Much emphasis is now being given to research and development of fully closed and controlled plant factories, aimed at supplying various vegetables safely and constantly. The plant factories daily produce the large volume of the safely packed vegetables under the artificially controlled environment. One of the important issues in the management and control of the plant factories is to establish a systematic method for the planning for the production and the shipping of the daily produced vegetables to the various customers. The paper deals with a basic study on the demand prediction of the wholesale vegetable markets, aimed at forecasting the customers’ demands to the existing plant factories. The demand prediction is very important for establishing a systematic planning method for production and shipping of the produced vegetables. Especially, an emphasis is gives to the demand prediction model of the representative wholesale vegetable markets.

To make the machining equipment on a production line more smart and connected, a centralized intelligent control system architecture is proposed. The equipment control systems are integrated into a clustered data center with big data processing ability. Industrial Real-time Ethernet is applied for machine controlling and process data acquisition. The massive process data are stored and analyzed with the big data processing platform. With the application of machine learning tools, intelligent control models and algorithms could be trained by making use of the large-scale process data. And the processing technic could be improved by optimizing the process parameters. All the process data and parameters in the data center are shared by the control systems of different equipment, each machine could adjust its technological parameters adaptively according to the output information of previous working procedure. The proposed system architecture could promote the flexibility and the level of automation of production lines in the era of big data.

Production style has been changed from high-volume low-variety production to low-volume high-variety production. On the other hand, customers require manufacturing companies to make the desired products quickly. It is important to consider the usage plan of material resources to carry out the production schedule. Lacking parts should not be allowed when the production is started.
This study defines parts ordering planning which decides parts order quantity and ordering time. The evaluation criteria of the ordering parts planning are multiple. This study proposes a parts ordering method, for multi-objective combinatorial optimization approach. A proposed method uses Combinatorial Auction. There is the case that there are some feasible solutions of Winner Determination Problem. The proposed method obtains multiple feasible solutions in iteration, checks whether the solutions are included in a set of Pareto solutions or not, and renews the set of Pareto solutions. Computational experiment is conducted to evaluate the proposed method.

In this research, we deal with a robot arm type electric power assist system used in factories and others. In the conventional electric power assist system, automatic control is performed for assisting the vertical movement, but automatic control is not performed for the turning operation. Therefore, in this research, we have constructed a system that senses the operator's force input to the force sensor of the operation lever and performs power assist to the operator. In this paper, we evaluate how much the physical and mental burden of workers has been alleviated by using a power assist system equipped with automatic controlled turning assist / brake function. We compare the results and discuss the effectiveness of the power assist system with the swing assist / brake function.

In this research, we focus on a power assist system in which the operating part is gloved. In this system, the force sensor attached to the operation part of the glove is used as an input interface to assist the operating force. However, it is necessary to get used to the operation of inputting the sensor while gripping the object. Therefore, when the input to the sensor is insufficient, the assist may not be sufficiently received in some cases. Therefore, in this study, we investigated the optimum sensor position for easily realizing the intended motion with the subject experiment for the lifting / descending operation while grasping the work target.

In-vitro study of mastication process is beneficial for dentists, physiotherapists, and the food industry. Robotic platforms can aid such study by mimicking a human-like chewing pattern for which capturing chewing trajectory of human subjects is an essential step. This chewing trajectory is required for analyzing kinematics, dynamics, and control of the chewing robots. In this paper, a novel motion-capture system using ArUco markers is proposed to capture mandibular movements of a human subject. The proposed system allows for a low-cost alternative for conventional optical motion-capture systems with simpler experimental setup. Using the proposed system, the incisal chewing trajectory of a human subject is captured, the head movements are compensated, and lateral, superoinferior, and anteroposterior mandibular movements are reported.

In this paper, we develop a prototype of legged robot to investigate whether its efficient jumping motion is achieved by using singular configurations. The experimental prototype is composed of a legged robot with three revolute joints and a tilting table on which the robot performs its jumping motion. According to the tilt angle of the table, various motions can be performed on the table from vertical jumping to horizontal pushing. The results of trial experiments for horizontal pushing indicate that, when the final posture of the robot is close to the singular configuration, the movement distance of the robot tends to be larger comparing with the case where the final posture is far from the singular configuration.