This paper points out that Japanese culture has many interesting ideas which can be utilized for the development of the next generation engineering. As changes occur frequently and extensively and in an unpredictable manner, the traditional engineering approach of system identification is no longer applicable. We need a new approach to adapt to these changes. To cope with such situations, we need more heads and machines are also teamed to work. Thus, team working becomes important. But as the case of soccer demonstrates, to cope with the rapidly changing situation, we need communication. In the case of soccer, midfielders who understands most how the play is changing is now becoming playing-manager and he instructs other members how to form the next formation. But unless other players understands what is on his mind and prepare in advance, the new formation cannot be formed in time and fails. Japanese culture does not discriminate inside and outside. Shoji penetrates outside situations so we understand the weather, temperature, wind, etc. of the outside world, although we are in the room. Thus, Shoji is a holistic sensor. And besides, the production system of the Japanese paper for Shoji is basically the same as Cellulose Nanofiber, the next generation CNF. And Japanese introduced modularization in Kimono long time ago. So, Japanese are very adept in modularization. Further, Japanese are very good at promoting process value. Tea Ceremony, Flower Arrangement, are called Sa-Do, Ka-Do and these words with the suffix -Do is selling process values. Thus, we should look at Japanese culture from the new perspective of how we can make the most of it for the development of the next generation engineering.

This paper points out the importance of Natural Intelligence. Artificial Intellience and the Digitized World are getting wide attention these days. But we should not forget that we are living in the Physical World and most elements there are analog. And the world is rapidly expanding, and changes occur frequently and extensively and in an unpredictable manner. So, we need to look at the Physical World to really adapt to these situations. The Digital World is not the Real World. It is a model and digital information is edited based on our preferences. And Knowledge which plays an important role in the Digital World is the concepts which are condensed in each person’s way to save space in the brain. To adapt to the unpredictable changes of situations, we need to look at the Real World. And we should also remember that engineering and science are different. In engineering, what matters is the outcomes. We do not care what paths we take to get the results. As Shakespeare said, “All’s well that ends well”. This is engineering. In this sense, we need to learn from the invertebrates such as the octopus, which directly interact with the Real World without any Knowledge. They live on their instincts alone. So, we need to make use of our instincts and interact with the Physical World more directly. To develop the next generation engineering in this way, we need to develop truly adaptive team working approach, which is far beyond the current team working approach with the limited number of members and with the strict rules. The Real World does not have such constraints at all.

Creative idea generation with consideration of logical and precise reasoning of design elements requires “unrestricted thinking” and “rational thinking”. M method is one of the designing methods based on the “Multispace Design Model” which enables to combine the “unrestricted thinking” and “rational thinking”. This method is a method for creating ideas by entering keywords and sketches on paper media such as cards and sticky notes and organizing them. However, it is difficult to manage and reuse the deliverables by using the paper media. In order to improve these issues, the M method system Ver.1, which digitized the method, was developed. However, it was thought that the system needed to improve functions related to "operability", "co-creation", and "management". Therefore, in order to improve the above three functions, we developed M Method System Ver.2 with a smartphone and server installed. This system was exhibited at SIGGRAPH Asia 2018, and a questionnaire survey was conducted for visitors. From the results, we clarified the superiority of M Method System Ver.2 over other idea generation methods. In addition, it was confirmed that the functions related to “operability”, “co-creation”, and “management” were improved compared to M method system Ver.1

Today, where mechanization for mass production is advancing and the scale and complexity of products are increasing, design domains are expanding and subdividing. Along with this subdivision, each design domain has propopsed design methods individually, causing misunderstanding of the other. Under such circumstance, it is considered essential to construct a cross-cutting foundation for diverse design domains, which would lead to the development of design science. In this research, we analyzed the features of the design methods used in various design domains from the consolidated viewpoint and constructed guidelines for selecting the design methods according to the purpose and process of design. First, we extracted 111 design methods from numbers of articles related to design. The design methods are then classified into 12 clusters by employing correspondence analysis and cluster analysis, according to the features which each method share in common. At last, the 12 clusters are categorized according to their usage purposes. While there is room for examination on the validity of the analysis criteria set in this research, the derived clusters are considered to be guidelines for the proper use of the design methods.

The manufacturing sector plays a key part in the advancement of the Malaysian economy. The various challenges encountered by the manufacturing industries, such as social, environmental, economic and technological, have prompted the assimilation of technology with production for enhancing operational efficacy. The inclination of the manufacturing sectors in Industry 4.0 can signify the relationship of the company structure with the facets of Industry 4.0. The firms comprise national, GLCs, SMEs and multinationals, which encompass all the manufacturing entities in Malaysia. Based on the model, the challenges pertaining to applying Industry 4.0 have been reflecting for companies that could also be referred for countering the weakness portions. Many companies have implemented IoT to enhance production as well as offer customer-oriented service. Simultaneously, companies’ organisational structure has been designed to quickly adapt with the latest development in technologies. Due to high investment costs, the companies’ willingness to invest in Industry 4.0 has reduced significantly, which has deterred many companies to implement Industry 4.0. The companies demonstrated low implementation of cloud service as well as standard security to safeguard the companies’ database from getting stolen or compromised. This is caused due to high cost associated with cloud computing service as well as low awareness pertaining to the implementation of big data analytics. The manufacturing companies have demonstrated positive motivation pertaining to the Industry 4.0 development from the beginner level.

In the market of home appliances that it is necessary to capture a share of global market. By shifting their production process to localized design, Japanese companies can develop more products in the same amount of time. It means that production process is changed from the traditional one in which the mother factory in japan sends the designs to the overseas factories where they are produced. The new model allows the overseas factories to design and produce and include any localization needed for that market. This paper proposes a case study when we used the new model to design and produce and product overseas. We were successful in developing the new products while reducing material cost. I propose a study to analyze that process.

Small Medium Enterprises (SMEs) in Malaysia is very important for countries prosperous and are considered the foundation and the backbone of industrial development. According to the Malaysian Investment Development Authority (MIDA) 2018’s report, SMEs contributes at least 40% to the country’s Gross Domestic Product (GDP) providing jobs to almost 65% of Malaysians. The present paper aims at developing an effective and efficient framework of Kanban system including all the components required for implementing successfully in SMEs. The paper begins with the study of existing framework of lean and Kanban implementation in small companies. To overcome this literature gap, data in the last six years of lean and Kanban implementation in different countries is studied in order to find the success factors for successful Kanban framework. Seven factors have been identified and the influence of those factors towards Kanban system implementation had been reviewed from previous related publications. Those factors are including top management (30%), organizational culture (11%), resources (13%), employee related barriers (22%), knowledge (16%), government support (3%) and supplier participation (5%). A proposed framework of Kanban system for SMEs in Malaysia has been introduced by mapping it with the seven success factors and also for future recommendation seven hypotheses had been constructed in order to test the framework.

Space debris, which has been increasing recently in orbit around the Earth, should be removed for future space transports and developments. To carry out active space debris removals (ADR) by entering space debris to the Earth atmosphere. In such mission, the risk to the ground should be decreased in case debris reaches to the ground possibility including heavily populated areas. In addition, to increase the mission efficiency, the total energy of the space debris removal satellite throughout the mission, that was the total increment of the velocity, should be decreased. Thus, this study discussed the multi-objective optimizations considering the simultaneously minimizing of the total energy of the space debris removal satellite, passing area of the satellite over the ground and the populated area. Firstly, we proposed parametrization for risks on the ground. Then, multi-objective genetic algorithms were applied to solve problems. ADR results for three target debris which had different orbits was compared. According to the result, it was found that the minimization of the total energy of the satellite during the mission and the minimization of the risk on the ground showed the trade-off. In addition, results were depended on orbit of the target debris.

Multiobjective design optimization of the engine of the atmosphere-assisted reusable sounding rocket is performed for maximizing the maximum altitude and the payload weight. The result shows that a trade-off between maximization of maximum altitude and payload weight maximization.

A supersonic civil transport has priority to target noise reduction and aerodynamic performance to become environmentally viable and economically practicable. To match ambitious goals, this research proposes a waverider configuration to solve these primary design of commercial supersonic aircraft. A waverider is famous for providing higher lift-to-drag ratio (L/D) than other conventional design in supersonic and hypersonic flight. The conceptual study of a supersonic waverider was done by previous research to look for an optimal shape that generates lower sonic boom strength and produce high L/D at supersonic cruise condition. This research considers the multipoint study of supersonic and low supersonic flight condition. A waverider has a crucial effect on increases drag in lower Mach number if it takes only a single-point design. This study fills these gaps by optimizing a power-law wedge waverider between two operation phase. Aerodynamic forces of a waverider are solved by numerical simulation using compressible Euler’s equation. The sonic boom strength is predicted based on augmented Burgers equations by considering overpressure peak. Bayesian optimization is conducted to visualize the Pareto-optimal solution for overpressure in normal supersonic flight and drag in low supersonic flight. Besides, the benefit of shape optimization is to address complex design trade-offs and offer physical insight for discussion.

This paper discusses computer-based comprehensive exploration of preferred design principles of bridge structures. A preferred design principle means here a system-level, conceptually optimal structure that differs by each system scale range. When recognizing that each principle is derived from a different system scale under the unique optimality, it could be assumed that classification of comprehensive optimal alternatives derives all principles at once in advance of individual design activities. Such a framework should be effective for conceptual design. This paper demonstrates such a possibility in the case of bridge structures, the preferred design principles of which are explicit historically. After the existing design principles are reviewed, the minimum representation of bridge structures is proposed as abstract but essential description. Following, topology optimization is performed comprehensively for different conditions. By classifying the obtained alternatives with a data-science approach, essential design principles hidden in the design problem is systematically derived. Finally, some future works toward the framework are discussed under such a demonstration.

Rapid heating cycle molding (RHCM) that controls the mold temperature during the plastic injection molding (PIM) is a novel plastic injection molding (PIM) technology. It has been reported in the literature that weldline which has an influence on not only the appearance but also the strength of a plastic product can be reduced by using the RHCM. Although various studies on the RHCM have been conducted, many of those studies focused on the layout and diameter of the heating/cooling channel. Like the conventional PIM, the mold temperature profile as well as several process parameters such as melt temperature, injection time, packing pressure and cooling time are crucial process parameters, but they are rarely discussed in the literature. In this paper, the mold temperature profile and several process parameters in the RHCM are optimized for the weldline reduction. In addition, the cycle time is also taken into account for high productivity. Numerical simulation in the PIM is so intensive that a sequential approximate optimization that response surface is repeatedly constructed and optimized is adopted to identity the pareto-frontier between weldline reduction and short cycle time. It is found from numerical result that the trade-off between them is observed. Based on the numerical result, the experiment using the PIM machine (GL100, Sodick) is conducted to verify the proposed approach. It has been confirmed through the numerical and experimental result that the proposed approach for the RHCM is valid for simultaneously minimizing the weldline and cycle time.

In this study, we construct an analysis and visualization method that can be easily understood by a person who does not have much knowledge of optimization using the data set obtained from Mazda's multi-objective car structure optimization problem. First, we perform filtering according to the gauge thickness of feasible solutions using hierarchical clustering, and then focus on the solution pair between clusters and visualize them with parallel coordinate plots. As a result, it is confirmed that even if the solution pair have no weight difference, not only the difference in thickness combination but also the constraint conditions close to the feasibility boundary are different. This implies that if there are multiple ways of combining design variables with the same objective function, it is necessary to filtering the data set in advance for extracting design information.

This study considers structural design problem of a displacement magnifying structure (DMS) for a highly precious space smart structure. The design problem is formulated by a multi-objective optimization problem that maximizes displacement magnification ratio and a fundamental eigen frequency and also minimizes the maximum stress in terms of several prescribed dimensions as design variables. During optimization process, the maximum stress value is often shifted discontinuously. Therefore, this problem considers stresses at several stress evaluation points and these stresses are also adopted as objective functions. Through numerical calculations, validity of the proposed formulation is demonstrated. Then, the structural characteristics of the obtained Pareto designs of DMS are discussed.

This work presents a constraint handling technique (CHT) for multi-objective evolutionary algorithms for the many-constrained multi-objective optimization problem (MaCMOP). The proposed CHT considers diversity of solutions in the design variable space to find many Pareto-optimal solutions. We verify the effectiveness of the proposed CHT on the Mazda benchmark problem.

This paper investigates the relation between the selection pressure of the mate selection scheme and the convergence speed of Multi-Objective Evolutionary Algorithm based on Decomposition – Multi-objective-to-Multi-objective. By quantifying the selection pressure, it is enabled to investigate the detailed relation between the selection pressure, the population size, and the number of subproblem.

As more information actively sharing and flowing due to the recent development in information and communication technologies, changes in the customer requirements to artifacts have been accelerating. In such market circumstances, companies are focusing on agile methods, which are design methods for software development. These methods continuously adjust artifacts based on customer requirements and create sustainable value. By means of applying agile methods not only to software developments but also to the broader artifact developments, the Agile Innovation (AI) expected to be realized. The process in agile methods includes the iteration phase which embraces the changes in customer requirements. To lead the agile development to the success, team managements that enable the efficient iteration phase is the most important. In previous research, agile modeling (AM), which is the methodology to support the modeling in the iteration phase, is known as the means of critical team management. By applying the AM to the modeling in the iteration phase, the team will work efficiently in the whole of the iteration phase. Thus, if we can extend the conventional AM for software to AM for a broad sense of artifacts including products and services, etc., designers can realize AI more efficiently. This paper aims to extend the conventional AM for software to a new AM for a broad sense of artifacts and reconfigures the new AM that enables to apply to the AI processes.

In the context of recent servitization of manufacturing characterized by IoT, Bigdata, and AI, we need data-driven front-loading design of product with service and engineering support for it. This paper proposes TriCyPSS (Triple Cycles for Product Service System) that supports developing service content from the viewpoints of service chain and continuous improvement among customer company, my company, and partner company. Using the TriCyPSS method, we can investigate not only service content but also plans of data utilization and information circulation based on its structure. This paper also details notations of the proposed model using the i* (eye-star), which is a methodology of system modeling in requirement engineering.

Recently, commoditization of product has proceeded and manufacturing company in developed countries are exploring a new approach to create value. Value-in-context, which is co-created among the company and their user, has received attention as a new concept of value. In order to enhance the value-in-context, designers should minutely analyze users’ rationality in the use phase and improve their product and service continuously based on the result of the analysis. The rationality of users is bound of their context such as their mental state and environment surrounding them. Thus, by means of extracting and modeling context, designers can analyze their rationality. However, designers struggle to extract the context and construct its model only with previous user research tools due to complex structure of user’s context and its transforming property through the influence of product and service. Therefore, the method which supports extraction and modeling of context should be provided. This paper constructs a mental model related to rationality of users and discuss how to conduct context modeling in efficient. Finally, this paper discusses the research direction toward proposing the method for value-in-context.

Increasing competition has encouraged manufacturing company to shift their mind set from only selling a product to providing an integrated product-services system (PSS). The transition of manufacturing company to be PSS company is called as servitization. In order to successfully undertake servitization, it is necessary to formulate strategic objectives in accordance with company-specific context consisting of the company’s internal capabilities, competitiveness, and external forces. However, the existing research of strategic objective formulation method for servitization lacks the viewpoint of competitiveness. The information (contextual data) and procedures required for analysing the context are not adequately clear. As a consequence, the formulated strategic objectives are lack of concreteness and rationality. In addition to clarifying the information and procedures required for the analysis of company context, this paper proposes a method to formulate practical strategic objectives for servitization based on the company’s context analysis. For this purpose, this paper firstly investigates the required capabilities which leverage the successful servitization of manufacturing company based on the literature survey. Based on those prerequisite capabilities, the context evaluation and the necessary contextual data are developed to facilitate the formulation of concrete and rational strategic objectives.

This paper proposes a timeaxis design (TaD) support method using patterns between temporal changes and countermeasures. For this purpose, we take three steps; (1) extracting patterns of temporal changes and countermeasures from collected TaD cases. (2) proposing TaD support method using the patterns. (3) illustrating timeaxis design of umbrella as a case study using the design support method. The TaD support method we propose enables to design a product with introducing countermeasures against plausible temporal changes into the design object. The case study indicate that designer can find out TaD design solution systematically using the proposed method and the proposed method can help designers well.

A value growth mobility is a concept of a future automobile system that the value rises more as it is used. Vehicle control and information presentation will be held based on driving states learned from driving data in the value growth mobility. An identity mapping model that was one of the methods of timeaxis design was applied to the estimation of driving states, and studied the possibility of the estimation of different driving patterns and a different subject by using one leaning data of a driving. As a result, it was confirmed that the driving states related to the relationship with the preceding vehicle could be estimated from the neurons of the intermediate layers. Furthermore, it was found that it was necessary to detect the driving states in two stages of macroscopic and microscopic in the case that the driving data patterns of the learning data and estimation data were extremely different.

Companies and other organizations are required to incorporate Sustainable Development Goals (SDGs) into their strategies. Roadmap has been widely used to visualize possible options for long-term strategic planning. The research challenge is how to support roadmap design for sustainable futures. One of the requirements for roadmap design for sustainability is to develop a sustainable social vision to be achieved and identify necessary technologies and policies. In this paper, we propose a method to design roadmap for sustainable futures in backcasting manner. Backcasting is to delineate a future vision and draw pathways backward from the vision. In the proposed method, we divide roadmap creation into two process: developing vision and developing pathways. We use a logic trees to develop a vision, while we develop pathways to connect the vision and the present in three steps: describing a vision and future situation, describing present situation, and describing ideas to connect the vision and the present. In a case study of sustainable manufacturing industry for Japan, two roadmaps were developed. Results show that the proposed method helped workshop participants generate ideas to connect sustainable visions and the present.

Product-Service Systems (PSS) is attracting attention as a means to contribute to a sustainable society. On the other hand, PSS benefit will be not realized without being implemented in society. Therefore, it is necessary to create a societal purpose to solve social problems and design it to be accepted by individuals belonging to Socio-Technical Systems(STS). Previous research has discussed how STS and other multi-scale system levels are related to PSS. However, they have a lack of practicality because of the abstract/theoretical discussion. It is necessary to develop a practical method that enables PSS design which contributes to the realization of a sustainability while considering the relationship between such a complex system. Specifically, “purpose” of solving social problems and the setting of specific “goals” to achieve them are important for consolidating motivation among stakeholders in the early stages of PSS design. This paper proposes a practical method to logically derive design purpose and design goals for sustainable PSS design. The operability of the proposed method was evaluated by applying a case study to workshop in agricultural high school.

Due to societal/environmental crises caused by excessive pursuit of productivity and efficiency in the last decades, the social awareness recently tends to respects sustainability and the role of design to achieve social well-being and equality. To address this, Product-service systems (PSS) is regarded as a one of the promising way to contribute to sustainable society. PSS is a system that is highly integrated by tangible products and intangible services to fulfill a particular customer demand and environmental benefit. On the other hand, to take advantage of PSS benefit for sustainability, it is essential to appropriately design and diffuse to be accepted by socio-technological system (STS) in which PSS is implemented. Moreover, STS has a property of transforming dynamically under the influence of internal and external disturbances caused by environmental, social and economic changes. Therefore, it is difficult to develop a PSS by traditional approach that regarding system statically. The purpose of this study is to construct a PSS development method that is accepted by socio-technical system with a systematic approach considering the characteristics of dynamic and multi-scale systems. To this end, this paper proposes a conceptual framework enables co-design of sustainable product-service systems by conducting related literature review. As a result, this paper identified five system levels to take into account and their relationships and five development processes for developing PSS to diffuse in STS.

In general, automobile repair options have three types: new, rebuilt and reuse parts. Both rebuilt and reuse parts are manufactured from used parts, so environmental impact and cost are lower than new parts. However, rebuilt parts need more manufacturing processes than reuse parts for overhaul, so they need more environmental impact and cost than reuse parts. Therefore, compared with these three options, product value is high in order new, rebuilt and reuse parts, but environmental and economic performance are high in inverse order. Hence, it is difficult for automobile users to evaluate which repair option is high suitability for them over the entire lifecycle of automobile. Besides, the suitability may change depending on the difference of requirements to automobile types. This paper assesses which repair options are suitable for automobile users in terms of product value, environmental and cost. Product value of automobile parts is assessed by distributing product value of an automobile to each part. Environmental impact is calculated by investigating automobile recycling parts factory and life cycle assessment method. Cost is calculated by life cycle costing method. This study applies to the automobile engine as a case study.

With the background of regional environmental regulations and improvement of battery technology, the popularization of electric vehicles is advancing. On the other hand, the new business model for the utilization of the battery of the electric vehicle such as battery reuse of the electric vehicle and demand substitution for the battery has been actualized. The purpose of this study is to develop a life cycle simulation model considering reuse from electric vehicles to home storage batteries and demand substitution between electric vehicles and home storage batteries. The rule for controlling reuse and demand substitution of the battery was embedded in the system, and the behavior of the rules was confirmed through the scenario evaluation.

Sense of agency (SoA) is the sense that “I am the one who is causing or generating an action”⁽²⁾. SoA is similar to sense of control in flow state. A user’s SoA decrease with assistance, possibly resulting in an obstruction of the flow state. This study aims to provide a design guideline for an assistance to maintain and improve the sense of fulfilment with flow state. We propose a mathematical model describing the mechanisms by which SoA of the assistance induces flow state. The assistance effect on the skill-challenge plane in flow theory was defined as an increase in skill and decrease in challenge. The factor separating the two effects from attribution theory is the locus of causality, which is matched to the judgement of agency (JoA) from the two-step account of agency. We hypothesized that the assistance increases the perception of skill and the flow state is stronger when the JoA is internal, rather than external. To verify this hypothesis, the experiment was conducted with assistance that varied with the ease of recognition. This result supported our hypothesis.

Research and development of autonomous driving systems are undergoing to realize a safe and secure mobility society, and technological improvement is expected, but the safety of the system itself and the driver’s feeling of security do not always match. The purpose of this study was to quantify risk feeling perceived by the driver in consideration of individual differences. We extracted the factor of individual differences comprehensively to examine the model of risk feeling based on expectation effect theory. Using a driving simulator, we investigated the effect of extracted factor on the subjective report of risk feeling in the overtaking scene. In obtaining subjective assessment, we set up an adapting session and manipulated the driver's prior distribution to investigate the effect of the prediction error and uncertainty on the driving behavior. The result suggested that risk was perceived based on both the sense of the individual's driving characteristic regarding the anxious tendency and the experimentally manipulated prior prediction. Based on the obtained findings, we examined the model of individual differences in risk feeling.

Novelty is an important factor of creativity in product design. Acceptance of novelty, however, depends on one’s emotions. Yanagisawa et al. developed a mathematical model of emotional dimensions associated with novelty. The model formalized arousal as Bayesian information gain and valence as a function of arousal based on Berlyne’s arousal potential theory. One becomes accustomed to novelty by repeated exposure. This so-called habituation to novelty is important in the design of long-term product experience. We herein propose a mathematical model of habituation to novelty based on the emotional dimension model. We formalized the habituation as a decrement in information gain from a novel event through Bayesian update. We derived the information gained from the repeated exposure of a novel stimulus as a function of three parameters: initial prediction error, initial uncertainty, and noise of sensory stimulus. With the proposed model, we discovered an interaction effect of the initial prediction error and initial uncertainty on habituation. Furthermore, we demonstrate that a range of positive emotions on prediction errors shift toward becoming more novel by repeated exposure.

Finally, we predicted that the ease to become accustomed to novelty depends on the initial uncertainty.

The product concept developed in the planning stage needs to be maintained from product development, design, production, and subsequent operation, maintenance, and disposal stage. In this paper, we show that functional and performance requirements for Kansei design can be clearly defined by sharing a conceptual model described based on behavioral analysis in the life cycle stage. Since the interaction between the external system and the product is described according to the scene, product information that contributes to the Kansei design can be included in the conceptual model.

The aim of this study was to investigate useful parameters of eye and head movement for estimation of mental workload (MWL) during automobile driving. Twelve students (6 males and 6 females) participated in this study. The participants performed a driving task with a driving simulator and a secondary task simultaneously. The N-back task was taken as the secondary task to control the MWL. The levels of N-back task were set as follows: None, 0-back, 1-back, 2-back, and 3-back. The gaze and head angles and blink frequency were measured with a visible-light image sensor. The eyeball rotation angle was calculated from the gaze and head angle. The sharing rate of head movement, which is the ratio of head movement against the gaze movement, was also calculated. In addition, the subjective MWL and accuracy of N-back task were measured. The result showed that the average subjective MWL monotonically increased with the increase of the difficulty of N-back task. The effect of the difficulty of N-back task was statistically significant for the standard deviations (SDs) of horizontal and vertical gaze angle, SD of horizontal eyeball rotation angle, sharing rate of head movement in horizontal direction, and blink frequency. The result of logistic regression analysis showed that the SD of horizontal eyeball rotation angle and blink frequency were the most significant parameters to estimate the MWL.

The user perceives sensory information, such as sounds and vibrations, generated by the operation of mechanical mechanisms, in response to the operation input of many common products. With the digitization of products, the mechanical operation response is lost, as the sensory information associated with it cannot be obtained, and there is no confirmation of the completed operation. Adding a digital sound or vibration could solve this problem. The challenge, however, is designing an operation response without inducing any sense of discrepancy. The purpose of this study was to create a method of quantitative evaluation of the sense of discrepancy to the operation response and its time transition. We investigated the possibility of using the event-related potential (P300), believed to reflect attention to stimuli, as a quantitative evaluation method of the sense of discrepancy. Experiment 1: We studied the sense of discrepancy between the lack of operation response (sound, vibration), and the shutter operation of a mirrorless single-lens camera, using subjective evaluation and P300. We confirmed that the P300 amplitude corresponds to the sense of discrepancy degree. Experiment 2: With the mouse click being the operation sound, the attenuation of the P300 amplitude by the repeated operation was consistent with the subjective attention direction attenuation. We conclude, based on these results, that the P300 amplitude could help determine the sense of discrepancy to the operation response and its temporal transition.

In Japanese language, the onomatopoeia is used frequently in communication. Recently, many researches on onomatopoeia have been performed in many fields such as engineering, psychology, medicine and so on. And the effectiveness of onomatopoeia is indicated in these researches. In this research, we investigate the influence of the body motion on quality of communication using onomatopoeia. In the experiment, we verify the quality of communication from three points of view: the degree of transmission, the feeling of transmission, the degree of rebuilding of contents. We prepare the videos of storytelling in which different expression methods: not using onomatopoeia and not using body motion, not using onomatopoeia and using body motion, using onomatopoeia and not using body motion, using onomatopoeia and using body motion. As a result of the experiment, the degree of transmission becomes high by using body motion. In addition, the degree of transmission becomes low by using onomatopoeia. Also, the feeling of transmission becomes high by using body motion. Especially, in the impression of the story, when onomatopoeia co-occurs with body motion, the feeling of transmission becomes high remarkably. Furthermore, the degree of rebuilding of contents becomes high by using onomatopoeia.

Human motor control system must tame interaction torque that is derived due to the multi-joint structure of the body to propose a desired movement. We attempted to evaluate the trajectories of human movements by focusing on the aspect of interaction torque on human arm movements produced with elbow and shoulder joints. As the results of the measurement experiment in which participants performed movements specified three-point as the task of the experiment, interaction torque relates some characteristics of the trajectories of arm movements and there is the difference of its contribution to achievement of the task between dominant and non-dominant hands. In the simulation experiment, interaction torque of simulated trajectories was distorted to assess the materiality of that on arm movements.

For a point-to-point movement, some characteristics of actual movements were reproduced in simulated trajectories. Meanwhile, for a three-points movement, the characteristics of simulated trajectories were partially similar to that of measured actual trajectories. We assumed that interaction torque was important for motor control whereas explicit tuning of interaction torque is bit circuity compared as other criteria of motor control.

In this research, to develop a gait feedback training system optimized for individuals where trainees can efficiently train features that do not satisfy ideal walking using a deep learning, we examine classification and features visualization of gait using Convolutional Neural Network (CNN) and Grad-CAM. In the experiment, the thumb-floor distance of right foot was measured when young people walked normally and when they walked with a brace, to limit their movement. Further, these data were clustered to 3 clusters using k-shape method. And these data were learned and classified as input data and using these cluster as the label. As the result, the accuracy was 86.07%. In addition, the part where the feature in thumb-floor distance appears were visualized as heat map using Grad-CAM and it is confirmed that usefulness for gait training.

In recent years, the number of traffic accidents has decreased due to the development of driving support systems. Driving assistance system supports to the driver, however when driving assistance is not appropriate, the driver may be bothered by the assistance and distrusted of the system. In order to provide appropriate support, a method that driver behavior prediction has been proposed. In this research, we measured seat pressure distribution and driving information using a driving simulator, and predicted driving behavior using a convolutional neural network. In this research, we predicted five driving behaviors: "Go straight ahead", "Turn right", "Turn left", "right lane change", and "left lane change”. As a result, it was possible to predict with an accuracy of 65.4% in inter participant evaluation and 96.4% in overall evaluation.

Pupil response is closely related to own affect and interest, and an enlarged pupil makes a good impression on others. Focusing on effects of the pupil response, we have developed a pupil response pet-robot for improving familiarity. This pet-robot can generate pupil response like human by tactile input during body contact. In this study, we conducted the experiment to evaluate the generation timing of enlarged pupillary expression using the developed pet-robot. The result demonstrated that the enlarged pupillary expression synchronized with body contact is effective in improving familiarity between human and pet-robots.

As a method of evaluating usability, usability tests are widely used, in which designers observe users using products. However, conventional usability tests take efforts on designers because designers need to manually input and analyze operation data of users when using tests. This paper proposes methods that can be applied uniformly through upstream to downstream design phases by using motion capture and Dynamic Time Warping (DTW). These methods enable designers to automatically acquire operation data of users and to calculate similarity of operation locus between designers and users. As the first step, an experiment was conducted that assumed the upstream design phases, using a triple digital timer. Consequently, it is revealed that it is possible to detect operations which are considered to have usability problems by using methods which this paper proposes.

In different environments, people's time perception varies based on various factors (people’s personal experience, degree of mental concentration, people’s age, etc.). The main factors can be divided into two parts which are external factors and internal factors. Though it is difficult to create a variety of environments and change factors in real world, VR technology can easily simulate various environments and control factors that can influence people’s time perception. In this research, we built a VR environment and change conditions in external and internal factors to study how it could affect user's time perception when they performed a simple work or exercised on sports bicycle. Through the experimental results, we found that controlling conditions in external and internal influence factors can create affective or functional value for the users wearing HMD by changing the users’ time perception.

Mobility scooters are three or four-wheeled electric-motor-driven wheelchairs with a handlebar for steering. In the use environment of a mobility scooter, there may be many obstacles that need to be avoided, such as pedestrians on a narrow sidewalk or cars on the edge of the road. These obstacles not only interfere with smooth driving but also induce mental strain on the user such as fear and anxiety, which may cause a decrease in comfort and an accident. The purpose of this study is to estimate physical obstacles in the road environment when driving a mobility scooter from operation information and physiological information of the user obtained during driving. We measured skin conductance, manipulation amount of accelerator, steering torque, and acceleration when driving on a course with physical obstacles. We tried to build a model that estimates the type of physical obstacles in the course based on these time-series data by using a random forest, which is one of the machine learning methods.

Because of its extremely high strength-to-weight ratio and specific elastic modulus, carbon fiber reinforced polymer (CFRP) has been widely employed in aerospace, automotive, sports equipment, civil engineering, and so on. In the present work, we aim to develop a free-form optimization system and apply it for optimizing the shapes of CFRP shells considering the fiber orientation to maximize its fundamental frequency under the volume constraint. This shape optimization system composed of vibrational eigenvalue analysis, derivation of shape gradient function, velocity analysis, and shape update, is implemented with a finite element method code and in-house program. We employ the method of Lagrange multiplier and the material derivative method to derive the shape gradient function considering the repeat eigenvalues. We adopt the H¹ gradient method in the velocity analysis to achieve the “free-form” of CFRP shells. We perform two simple numerical examples using the developed free-form optimization system. The optimal results show that the natural vibration behavior of CFRP in each design example can be significantly enhanced after the free-form optimization.

In this study, we propose a non-parametric shape-topology optimization method for tailoring the static deformation of micro-frame structures. The design objective is to minimize the sum of squared error norms for achieving the desired displacements on specified members. The shape gradient function, the topology gradient function, and the optimality conditions for this problem are theoretically derived with the Lagrange multiplier method, the material derivative method, adjoint variable method, SIMP and GSIMP method. The sensitivity functions for this problem are applied for the H¹ gradient method for frame structures. With the proposed method, the optimal arbitrarily formed frame structures will be obtained without any shape and topology parameterization while maintaining their smoothness. Optimum design examples are demonstrated and the results are discussed.

Optimized smooth shells resist the external force efficiently through membrane stiffness. However, the smooth optimal shapes aren’t always fabricated because of some shape restrictions. In this case, ridges need to be designed properly to increase the stiffness. Their anisotropic mechanical characteristics increase local bending stiffness and influence on load transfer and deformation. In this paper, we propose a shape optimization method for designing ridges on a shell structure by modifying the H¹ gradient method. In the proposed method, fictitious shell elements are connected with the rotational springs and the spring constants are set up manually to adjust the local stiffness. In addition, the bending stiffness of the fictitious shell is increased to assist in the creation of ridges. The proposed method was applied to the shape optimization problem for minimizing the mean compliance, where the total volume is constrained. Case studies were performed with different rotational spring distribution and stiffness of shell elements. For proper conditions, ridges were created according to the rotational spring distribution and the mean compliance decreased by 99%. We confirmed the proposed method is effective for optimizing shell structure with ridges.

A topology optimization method to design micro structures of sound-absorbing poroelastic media utilizing the homogenization method based on an asymptotic expansion is proposed in this study. Design sensitivities of homogenized properties with respect to design variables defined on nodes of a microscopic finite element model are derived by using the homogenization method and the adjoint variable method. Then, design sensitivities of macroscopic objective function, which is dissipated power in this study, with respect to design variables defined on nodes of a microscopic finite element model are derived by using the adjoint variable method. The design variables are updated by using Method of Moving Asymptotes (MMA). Here, the design sensitivities both in microscopic and macroscopic scales are verified by a numerical examples.

Stiffness maximization of structures subjected to frictionless contact is one of fundamental problems in structural optimization. This paper presents a formulation that can be handled with a standard nonlinear programming approach. The frictionless contact problem of an elastic body is formulated as a complementarity problem. Therefore, it is natural to formulate a design optimization problem of structures subject to frictionless contact as a mathematical programming problem with complementarity constraints (MPCC problem). However, since any feasible solution of an MPCC problem does not satisfy standard constraint qualification, conventional nonlinear programming approaches cannot be applied to an MPCC problem. In contrast, the formulation presented in this paper does not involve complementarity constraints, and hence can be solved with a standard nonlinear programming approach. Derivation of this formulation is based on the Lagrange duality applied to an optimization problem defining the compliance.

In this paper, we present a numerical solution to optimize thin walled cross section shape of a solid structure, which is often demanded at the early stage in structural designs. The thin walled cross section is minimized subject to the constraints of sectional properties including the torsional constant, the moment of inertia of area, the center of figure and the share center of figure. The problem is formulated as a distributed shape optimization problem, and the shape gradient function is derived using the Lagrange multipliers and the material derivative method. The traction method, which was proposed as a gradient method in the Hilbert space, is applied to determine the smooth optimal shape. The constraint conditions are efficiently satisfied using the modified feasible direction method. The validity of this method is verified through several design examples for obtaining the optimal shape of the thin walled cross section under the constraints of sectional properties.

Usually, the topology optimisation related to wave devices is formulated to minimise a shape function of a structural response to wave with a single frequency. The optimal structure obtained in such a way may not be robust with respect to the frequency change, i.e., the performance of the optimal structure may considerably deteriorate when the frequency of the incident wave is slightly different from the expected one. To remedy the robustness, it may be efficient to consider the shape function involving higher-order frequency derivatives of the structural response. In this paper, we discuss a computation for the topological derivative of higher-order frequency derivatives of acoustic response in a two-dimensional exterior domain. We show that we can “interchange” the topological and frequency derivatives. We also demonstrate that automatic differentiation is useful for computing higher-order frequency derivatives of the topological derivative.

We aim to understand the mechanism that forms the shapes of bones. Biological studies suggest that bone morphology is adapted to the external loads. To explain how the external loads affect bone morphogenesis, the mathematical models have been developed using topology optimization. Using these mathematical models, the structure like trabeculae can be generated. However, the formation of external shapes of bones has rarely been studied. Because the inner structure and the external shape of bones are formed by the same types of cells, we hypothesize that the formation of external shape also depends on the external loads and can be explained by topology optimization. The vertebral body of fish we focus on exhibits the various shapes and its morphology seems to be closely related to the swimming mode of fish. To reveal the relationship between the vertebral shapes and the external loads, we built a mathematical model using topology optimization. By setting the different loadings expected to occur during swimming of fish, the model can produce the shapes similar to the vertebral bodies of the different species. Numerical results suggest that the external load is one of the main factors to determine the shape of vertebral bodies of teleost fish. Also, this mathematical model enables us to discuss what external load is important to form each vertebral shape of the different species.

Weldline that has an influence on not only the appearance but also the strength of plastic product is one of the crucial defects in plastic injection molding (PIM). It is important to reduce it as much as possible for high product quality. In addition, high productivity that is short cycle time is also required in PIM. To minimize the weldline and the cycle time for high product quality and productivity, process parameters such as melt temperature, injection velocity, packing pressure and so on should be adjusted and optimized. For more effective weldline reduction, variable injection velocity and variable packing pressure that are injection velocity or packing pressure vary during the PIM are adopted. Besides, a new weldline evaluation instead of weldline length is proposed. In this paper, a multi-objective optimization of variable injection velocity, variable packing pressure and process parameters is then performed for the weldline reduction and the short cycle time. A sequential approximate optimization using Radial basis function (RBF) network is used to identify the pareto-frontier. The experiment using the PIM machine (GL100, Sodick) is conducted. Though the numerical and experimental result, the validity of the proposed approach is examined.