One of the Melaka casting firms was facing an issues regarding the current hood placement on the casting machine. the current hood placement design was so poor at capturing scattered chips. The placement was not as close to the emission source as possible, leading the chips to be spread in different directions. To solve the problem, the House of Quality (HOQ) received an analysis based on feedback from industrial members. The HOQ was used to identify the preferable criteria for hood location, with “ease of maintenance” scoring the highest at 26.67%, followed by “stable and safe,” which scored 22.22%. Then, three innovative designs were offered from the HOQ result specification, and following consultation with the external engineers involved in the process. In addition, the Pugh was employed to determine the best hood placement. Finally, the concept of Design-3 was selected with a concept score of 3.9. The outcome shows that by using Kaizen, the time required to clean the equipment is to be reduced. As a result, the company's production has increased due to the reduction of 90 minutes of cleaning time.

This paper comprehensively reviews the labor shortages faced by Malaysian manufacturing firms and analyzes the impact of various new sourcing strategies on production performance. The focus of this review centers on several emerging sourcing strategies, namely automation and robotics, training and development programs, local talent utilization, collaboration with educational institutions, and the utilization of gig workers and freelancers. The literature review critically evaluates the effects of these new strategies on production performance, taking into consideration factors such as cost-effectiveness, efficiency, flexibility, and quality control. In conclusion, this paper suggests several implications for Malaysian manufacturing firms, including the adoption of new sourcing strategies, investment in technological infrastructure and human capital, and collaboration with government agencies and other stakeholders. Additionally, the paper highlights the need for further research in this area and provides recommendations for policymakers and practitioners to effectively address the labor shortages and enhance production performance in the Malaysian manufacturing sector.

In the field of industrial machines, the mechanical systems composed of the power-circulation structure exist, and the powers of two or more motors of the same output are synthesized through the gear stages to drive the driven machine part and the desired motion of the machine is achieved. However, in the mechanical system with a power-circulation structure, the residual vibration related to the natural frequency in the lower-frequency range will be generated when the motor starts or stops. This phenomenon causes problems such that the productivity of the mechanical system will be reduced. In this paper, the case that the power-circulation mechanism is driven by two motors is taken up, and the vibration suppression control of this mechanical system is investigated by simulations. First, the analytical model for the torsional vibration and the analytical results are shown. Second, a sensor-based control related to the velocity control loop is proposed to reduce the residual vibration. The effect of the sensor-based control was confirmed by using the performance evaluation index of the control error area and the current consumption area. Simulations show satisfactory control results to reduce the transient vibration at the driven machine part.

Hammer forging is a traditional manufacturing technology to produce high stiffness product and is widely used in heavy industries. In the hammer forging, the product is produced through several blows. Forging using mechanical press controls the distance between dies and then the product is produced, whereas the product is produced by the energy in the hammer forging. Therefore, it is difficult to control the distance between dies in the hammer forging, and the energy plays a crucial role in the hammer forging. It is necessary to determine appropriate energy at each blow to produce highly accurate product. Conventionally, the energy at each blow is determined by the trial-and-error method. This paper proposes a methodology to determine the optimal energy at each blow using numerical simulation and design optimization technique. It is important to save the energy in the hammer forging for green environment, and is also important to reduce the forging load. To produce the highly accurate product, underfill should be avoided, which is handled as the design constraint. Therefore, multiobjective design optimization is performed to minimize the total energy and the forging load without underfill. The numerical simulation is so intensive that sequential approximate optimization that response surface is repeatedly constructed and optimized is adopted to identify the pareto-frontier between the total energy and the forging load. It is clarified through the numerical result that the proposed approach can determine the energy at each blow effectively, compared with the trial-and-error method.

Manufacturing industries have increasingly recognized the value of Lean Six Sigma (LSS) not only for improving productivity but also for enhancing sustainability. LSS has also gained popularity in the service sector, prompting the exploration of enablers supporting its adoption in environmental services. This study aims to investigate the relationship between Green LSS enablers and operational benefits (OB) in wastewater treatment plants (WWTPs) in Malaysia. The study examines five independent variables (IVs): strategic-based enablers (S), environmental-based enablers (Env), culture-based enablers (C), resource-based enablers (R), and linkage-based enablers (L), in relation to the dependent variable (DV) of OB. Data was collected from 65 certified competent personnel working in WWTPs and analyzed using validity, reliability, factor analysis, and multiple linear regression. The results indicate that the IVs significantly predict OB when the p-value is below the 5% threshold. This suggests that the factors examined have a significant impact on WWTP operational benefits. Furthermore, the R² value of 0.390 indicates that the model explains 39% of the variance in OB. Specifically, the variables S and C significantly support the hypotheses, while Env, R, and L do not significantly influence OB. These findings provide valuable insights for the wastewater service sector in improving their understanding and implementation of Green LSS to enhance operational performance in a developing country, Malaysia.

The use of digital manufacturing has become increasingly important to maintain competitiveness in the market as companies embrace Industry 4.0. In most enterprises, there is an increasing demand for remote communication and collaboration as an alternative to travelling between locations. This trend is influenced by many factors, including the recent epidemic of Covid 19, the increasing cost of travel, and the desire to reduce carbon emissions. Companies can implement mixed reality technology, which can supplement the real world with virtual information and help production workers complete tasks. Mixed Reality technology is increasingly being used in industry to immerse users in semi-virtual environments such as factories. This research aims to study and develop a mixed reality solution that allows manufacturers' staff to collaborate and share resources and knowledge at a distance without needing to be in the same location. This study investigates the potential use of Microsoft HoloLens 2 headsets for creating and remotely cooperating in mixed-reality manufacturing environments. Four Unity projects were developed using imported mixed reality tools and other imported resources in Unity for HoloLens 2. Two users can interact and complete a set of tasks within the mixed reality factory while remaining physically separated. The results show that remote collaboration in mixed-reality manufacturing environments can be used in the industry to help with plant planning, learning factories, remote maintenance assistance, and monitoring. The work applies and builds on existing knowledge, demonstrating the potential for rapid development and sharing of mixed-reality manufacturing environments in remote collaboration.

As manufacturing facilities move towards Industry 4.0, automation is becoming increasingly prevalent. The development of innovative manufacturing technologies, complex parts and high-precision parts has resulted in the deficiency of traditional manual inspection methods. This has led to computer-aided inspection systems (CAIs), including image-based systems and 3D scanning technologies. In this work, a quality inspection system using 3D scanners has been developed and proposed. These innovative systems reduce human error and maintain accurate and reliable results to address traditional quality control limitations. The current literature indicates that part inspection should be automated to avoid limitations in manual visual inspection, establish stronger and more systematic inspection methods, and make full use of point cloud data. The proposed system aims to improve quality inspection processes in manufacturing. The system is based on the Artec Leo 3D scanner system. The operation of the 3D scanner was studied and the point cloud data was processed. Finally, the reliability and efficiency of the proposed system are studied and analyzed. The system focuses on trends and challenges in Industry 4.0 by dealing with the development of quality assurance topics. This complete inspection system gathers relevant quality characteristics and forms a complete basis for the evaluation of product quality. The developed system can be used to measure parts' dimensions accurately, with an average accuracy of 98.69%, comparable to the literature review system, as the inspection time has been optimized and the requirements for the required equipment are kept to a minimum.

In recent years, communication robots are commonly used in various places and situations such as guidance work at hotels and stations and elderly supports for the purpose of reducing human loads and releasing from simple works. However, it is also shown that people still have a sense of anxiety toward robots. For this reason, there are few people who have motivations to communicate with robots. On the other hand, it has been suggested that the emotion expression of robots contributes to create a sense of familiarity and smooth communication. Therefore, we propose a method of emotion expression and enhancement by changing the color of the clothes the robot is wearing. Also, we have clarified the matching between the clothes colors and 10 emotions (joy, anger, sorrow, fear, shame, like, dislike, excite, relief and surprise). In this research, we investigate the influences of changing the clothes color in scenes where the robot's speech emotions change in time series. As a result of the experiment, it becomes clear that feeling of transmission can be improved by changing the clothes color according to the speech emotion in case that the mechanism of clothes color change is correctly understood. On the other hand, feeling of transmission is decreased in case that the mechanism is not understood.

Multi-project management is the tactical and operational management of a set of concurrent projects sharing the same resources and is controlled by the portfolio manager. Resource sharing significantly increases complexity since it creates resource dependencies between tasks, especially in high uncertainty and complex environments. Hence, resource allocation in multi-project environments is difficult for portfolio managers. According to prior literature, classical mathematical approaches are effective for dealing with resource and project scheduling problems of low complexity or in a relatively static environment. Still, they have limitations in describing interrelationships in multi-project environments and adapting the analysis to dynamic change. In this study, we have proposed a simulation method for human resource allocation for multi-project management in a project portfolio system considering resource buffers. We have suggested how resource buffers can be applied for resource allocation in multi-project management and affect portfolio performance. Different sizes of resource buffers have been tested in various situations by considering different levels of uncertainty and complexity and determining how they affected performance. Furthermore, the effect of varying resource buffer sizes on reducing completion time has been investigated, which might be useful to portfolio/project managers in practice.

In a precision machining of workpiece profile using a machining center (MC), how to choose cutting parameter values for achieving simultaneously high contouring accuracy and high machining efficiency is a very important problem in actual manufacture. Although a lot of efforts have been made, so far there is no effective and convenient method to provide to the field for practical use. From the machining center (MC) user’s point of view, the authors have developed a practical and convenient approach to estimate the trajectory motion error of a cutter path produced by the NC acceleration/deceleration (Acc/Dec) processing and the position servo control for a target MC. In this study, a further examination to the different interpolation types of cutter paths is performed under the different motion conditions has been completed. The comparison results of the estimated cutter path trajectories with the measured ones only not demonstrate the validity of the proposed approach from a wider perspective, but also, some important features of the motion error with respect to different interpolation condition are identified. Moreover, A new reverse compensation principle to improve the cutter path motion accuracy is proposed, which only requires the simulation result of the object cutter path by using the motion parameter values commanded in the NC program and a relatively simple modification based on the simulation result to the NC program. The confirming experiment result has proved the possibility of the principle.

Disassembling of a part is required for maintenance of machinery in case. However, the disassembling process is often not explained in the operation manual, or the explanation of the disassembling does not cover all the situations of all the individual parts, even though, such disassembling could be dealt with by operators that are not familiar with the mechanism of machine. Operators themselves have to determine the disassembly process in such a case. Therefore, it is crucial to develop a system that helps inexperienced operators to find out a proper disassembling process. We focus on the disassembling of a specific part referred to as a target part. The approach is based on the positional relation information among the parts. The positional relations matrix that obtained from the contact states of any two parts in all possible directions and can be generated from the ordinary CAD data. This study proposed a method to infer a disassembly process of a specific part based on the positional relation matrix. The method deduces the disassembly process of the target part with the shortest steps, in the condition of one-part-at-a-time manner. We also introduced an integration of disassembling parts based on the obtained process. A case study was conducted and the result confirmed the feasibility of the proposed method; the effectiveness of the integration approach was also demonstrated.

The mechanical systems composed of the power-circulation structure exist in the field of industrial machines, and the powers of two or more motors of the same output are synthesized through the gear stages to drive the driven machine part and the desired motion of the machine is achieved. However, in the mechanical system with a power-circulation structure, the residual vibration related to the natural frequency in the lower-frequency range will be generated when the motor starts or stops. This phenomenon causes problems such that the productivity of the mechanical system will be reduced. In this paper, the case that the power-circulation mechanism is driven by two motors is taken up, and the vibration suppression control of this mechanical system is investigated by simulations. In the other paper of author at this conference, the effect of the sensor-based control was confirmed by using the performance evaluation index composed of the control error and current consumption areas. On the other hand, in this paper, the disturbance suppression performance is investigated. The author proposes a control method to switch the control mode between starting/stopping and steady state of rotations. Simulations show satisfactory control results to reduce the residual vibration at starting/stopping and the angular speed fluctuation when the disturbance is exerted at the driven machine part.

A variety of underwater exploration robots are currently used for underwater exploration and research. Their main propulsion device is a screw propeller. While this mechanism is highly efficient and versatile, it has various problems, such as attracting marine organisms and malfunctioning due to the rotation of its wings. For this reason, underwater robots that mimic marine organisms have been widely studied. These underwater robots pose less danger to living creatures and are more environmentally suitable than screw propellers. This study describes a novel propulsion mechanism for underwater robots used for exploration of rivers and oceans. Unlike these underwater robot propulsion mechanisms, this study provides a novel propulsion mechanism inspired by shrimp swimming. Focusing on the shrimp's swimming technique of paddling its limbs, we developed a paddle-type propulsion mechanism that applies the movement of the shrimp's abdomen during swimming. To evaluate the effectiveness of the propulsion mechanism, experimental results of propulsive motion using the developed prototype were presented and analyzed. As a result, it was confirmed that this propulsion mechanism has a certain motion performance that can be used as a propulsion device for underwater robots. The establishment of a control method for phase differences in this study will also contribute to the generation of motion for underwater robots that move their fins in a certain pattern, such as rays and squids, which will be the subject of future research.

Understanding latent demands and incorporating them into product functionality are crucial steps in the product development process. "Those that many customers identify as significant but cannot be adequately articulated in advance" is how latent demands are described. Latent needs are the subject of numerous surveys conducted to find new ideas, but the circumstances and elements that can produce latent requirements are not known. Additionally, it is difficult to identify latent needs from consumer wants using quantitative analysis. The purpose of this research is to verify the method in the elicitation of latent needs from consumer needs by introducing directly the working prototype to the consumers, conducting interviews, and collecting responses from the consumer after they touched and observed the working prototype directly and the results from conducting the research with a focused working prototype of a childcare device with the “preventing entry into dangerous areas” function was presented in this paper. The interpreted needs that obtained high scores of the Degree of Latent Needs (DLN) which is our proposed quantitative evaluation method for identifying latent needs from product function are “The device can emit light from its eye” and “The device can change the facial expression”. In addition, a method for investigating the effectiveness of the quantitative evaluation method was evaluated by applying the Anderson-Darling test. The results indicated that the DLN values of the needs translated from the working prototype of the “preventing entry into dangerous areas” function did not follow a normal distribution, however our previously interpreted needs from comprehensive working prototype interviews follow a normal distribution. Therefore, we are able to say that our evaluation method using DLN could be applied to calculate and assist in evaluating important latent needs.

Latent needs are defined as "those that many customers recognize as important but cannot be clearly articulate in advance". Latent needs are the subject of numerous surveys conducted to find new ideas, but the circumstances and elements that can produce the hidden requirements are not known. In our research, we conducted interviews after introducing a working prototype of a childcare device. The responses in the interview were then interpreted based on the guideline commonly used by other designers. Then, as we assumed that experience, empathy, and knowledge of working prototype is essential elements in product development, the new additional guidelines which are "to write a statement with empathy", "to write a statement as a designer", and "to write a statement as someone with experience" were proposed to see whether these new guidelines will influence the process of identifying latent needs. From the research result, we were able to conclude that the number of interpreted needs increased when we additionally applied the new proposed guideline. Although the number of increased needs is small, the needs might not be interpreted if the new guidelines were not considered. We also discovered that the interpreted needs of newly proposed guidelines obtain high scores with our quantitative evaluation method of interpreted needs. We could conclude that including these guidelines upon interpreting raw data from consumer interviews might lead to discovering important and critical latent needs of the consumers.

Japan is currently a super-aged society. Gait support is becoming increasingly necessary as a result. In this study, we will develop a particle filter to be incorporated into a 2.5D gait recognition method under development that uses three sensors instead of a camera or other devices. This is because recognition using a camera or other means involves issues such as privacy and the time and effort required to attach the filter. The information used in this recognition method is based on sensor readings of the center points of the torso and legs, and the amount of change is modeled as a system model. The center points of the torso and legs were calculated as an elliptical model and a cylinder model, respectively. In actual simulations using simulation software such as Matlab, we were able to achieve the desired movement of the torso and legs during walking. We believe that this will eliminate errors and disturbances in the model and enable more accurate recognition. In the future, we would like to define an actual model that recognizes the state of walking in this research and develop a walking support machine to support walking. In addition, we plan to further develop the particle filter system model to be able to read special gait such as hemiplegic gait.

In the manufacturing industry, knowledge transfer of experts has become an important issue because of the decreasing number of experts. To support knowledge transfer, various support systems have been developed. To present appropriate knowledge to the user, the user’s skill level needs to be assessed. The purpose of this study is to develop a technique for judging a user’s skill level using gaze-measurement data. The gazes of experts and beginners were measured in relation to their vortex-search skills when searching for vortices of fluid-simulation results. We generated 111 features from the fixation time of each vortex, the transition frequency between vortices, and the average pupil size, calculated the importance of the feature values using the Decision Tree, and extracted the top five feature values. Several machine learning models were examined to estimate the user's skill level by using these five feature values. As a result, by using the K-nearest Neighbor, the model was able to discriminate between experts and beginners with an accuracy of 84.2%. These results imply the gaze shows the difference in the users' skill levels and show the prospect of presenting appropriate knowledge to the user of the design support system by using the gaze-measurement result.

Concurrent Engineering (CE) is a methodology aimed at reducing costs and time in production processes. To achieve this goal, collaboration among various activities is essential, including design, manufacturing and assembly, marketing and distribution, and customer relations. Collaboration among individuals from different activities is particularly crucial for the success of CE, not only in industry but also in academia, where global research and educational collaboration are highly valued. In 2014, TMAC or Tokushima University (TU)-Universiti Teknikal Malaysia Melaka (UTeM) Academic Centre, was established to promote academic collaboration between the two universities. Among its various activities, the TMAC Design Workshop (TDW) series plays a central role in facilitating student exchanges between the two universities and enhancing student education. This year, TDW series has expanded to include participation from Okayama Prefectural University (OPU), further strengthening the collaboration among the three universities.

This paper presents the educational program of the TMAC Design Workshop (TDW) 2023, which is designed to cultivate teamwork skills within the context of Concurrent Engineering (CE). The primary objective of this program is to enable students from Japan and Malaysia to comprehend the significance of productive collaboration in a multicultural setting. The paper specifically concentrates on TDW2023, an event that transpired in February of the present year. It presents an overview of the global teamwork activities carried out by students from Japan and Malaysia during the workshop, elucidating their accomplishments, evaluations, and outlining potential avenues for future study.

Magnesium alloys expected to be widely used as a component material of vehicle and high speed rail for sustainability because the advantages, lightweight properties and high recyclability. On the other hands, the magnesium wrought alloys are not used widely compared with casting alloys due to poor plastic workability from magnesium’s hexagonal close-packed crystal structure. In previous research, various material designs have been performed to improve the poor plastic workability in the wrought magnesium alloys such as ECAP, HPT. Among them, we studied torsion and back-torsion for magnesium alloy pipes. Our previous study clarified one of the factor in improvement workability was deformation twin formation. In the present study, we researched effect of various condition that torsion angle, varying rotating speed or heat-treated on deformation twin formation by torsion or back-torsion for clarify good design conditions of improve plastic workability of magnesium alloy pipes. We observed microstructure of twisted pipes by various conditions, and extracted deformation twin area. After that, deformation twin area ratio calculated from extracted area. The result shows deformation twin area increased with increasing torsion angle. In addition, the area of heat-treated back-torsion pipe was decreased from the not heat-treated pipe. Besides, the result shows the area of torsion or back-torsion pipes are less affected by rotating speed.

Working machinery used at construction sites, such as plant construction, can cause accidents including overturning, swinging of suspended loads, and damage to the machine body. Because of their large size, these machines can cause extensive damage to the surrounding area when an accident occurs, and new measures are needed to prevent such accidents. We are developing a system that effectively conveys safety information to operators of these machines. In this paper, we report on a vibrotactile safety information system. In addition, a crawler crane simulator using mixed reality technology for validating the safety system is reported.

Pandemic of COVID-19 accelerated usage of various online communication tools including video conference software, and Metaverse applications. But it is not clear that what are characteristics of communication performed in each online communication environment. Especially, research of comparing nonverbal communication between different environments is not enough. It is supposed that adapting nonverbal behaviors to the online communication environment can enhance facilitate effective communication among collaborative employers, such as engaging engineering works. This paper aims to reveal characteristics of communication in video conference and metaverse environment by comparing them. The experiment was conducted to observe how subjects perform gestures using card game which is playable on the web browser. Subjects are assigned to two groups, video conference and metaverse environment. Video conference environment group used Zoom as communication tool, and metaverse group were in 3D virtual reality space created by Unity, wearing Meta Quest 2. Parameters to measure the characteristics of communication are number of the gestures per second, percentage of gesture time per second, and average duration of gestures, for hands and head respectively. In addition, gestures of hand are used as information transmission gesture, and gestures of head is used as responding gesture. The result shows that comparing two environment groups, the video conference environment group had more responding gestures, while the metaverse environment group had more information transmitting gestures.

This paper addresses geometric modeling using stochastically manipulated triangular tessellation or meshing. We employ two different methods. The first method randomly selects triangles on a rectangular or circular plane. The use can adjust the overall porosity and fineness of the triangular mesh. This method can create complex structures that have pores scattered randomly. However, the pores themselves are not necessarily irregular. The other method first creates a point cloud around a given closed boundary. Triangles are formed among some randomly selected points inside the boundary. Finally, the triangles are merged to form tunnel-like openings. This way, the method produces a complex structure exhibiting highly irregular and randomized pores. Unlike the first method, this method does not help adjust the porosity that much, but the sizes of the pores can be adjusted by changing the density of the points in the point cloud. Thus, a hybrid method can be used to create porous structures exhibiting highly randomized pores with predefined porosity. Consequently, the hybrid approach method can be used to develop products for biomedical engineering (e.g., implants) and engineering devices (heat and mass transfer equipment where percolation is necessary). In the next phase of the study, we plan to study the manufacturability of the stochastic shapes we designed in this study.

The 3D direct drawing system can create the point, the segment, the polygonal and curved surface, and the solid model. However, creating the model is difficult for a user because the command is multiple and complicated. In this paper, the drawing trends and trajectories are investigated. After that, they are predicted and converted to the desired shape using the k-NN method and Neural Network method of machine learning, and the accuracy rates of the two methods are compared.

Creating a control program for robots needs explicit definition of each action to handle inputs from sensors and produce outputs to actuator. The aim of this project is to use Grammatical Evolution (GE) to automate the process of producing multiple actions as strategy. This algorithm can separate searching space and generated program, thus eliminating human criteria bias when creating a robot controller while able to find more optimized and complex actions strategy. The evaluation is done through partially observed maze problem which objective to find goal without defining starting orientation and discoverable path along the way.

Today, Japan's infrastructure is more than half a century past its construction and is deteriorating. The goal is to improve the efficiency and automation of infrastructure inspections with the aim of preventing accidents such as the Sasago Tunnel collapse. We decompose infrastructure inspection into four elements: "movement," "signal input," "signal acquisition," and "analysis". In this paper, we focus on movement and develop a mobile robot to transport equipment necessary for inspections. The robot to be developed employs a skid steer, eliminating a complex steering mechanism, and is designed to be compact and simple while maintaining the rigidity of the vehicle body. In addition, to achieve automation of the entire inspection process, we aimed to develop a mobile robot to be used for the inspection robot and its feedback control, and based on the data of the designed robot, we conducted a simulation using MATLAB and showed that PD control was possible. Experiments were conducted to verify whether the created robot could actually be used for inspection in tunnels. We conducted a turning test, a hill climbing test, a battery durability test, and a wall-following test on the university's premises. The performance was sufficient as a mobile foundation for a tunnel inspection robot.

In recent years, advancements in Additive Manufacturing (AM) technology have enabled the fabrication of complex shapes that were difficult to achieve with traditional manufacturing methods. Notably, in Fused Filament Fabrication (FFF) process, some research have been conducted not only on traditional planar layering but also on non-planar layering. By aligning the deposition layer in AM with a non-planar surface rather than a flat one, anisotropy can be reduced with increasing the contact area between layers, thereby improving strength and rigidity. In non-planar layering, the nozzle of an FFF-AM machine moves not only horizontally but also vertically during fabrication, which can construct accurate curved-surfaces that could not be achieved with existing planar layering.

On the other hand, a technique called computational design has been adopted for creating complex shapes, including in the design of modern architectural structures. In this study, the term “computational design” is regarded as "having the computer automatically design according to an algorithm conceived by the user." This can greatly reduce the modeling time for fabricated objects.

In this study, we apply the computational design to model cell structures that conform to a desired curved surface shape. The experiment is conducted to fabricate a test model and verify the effectiveness.

Launching a new system is essential for a company to continue its business. When a product or service is launched to the market as a product that provides completely new value, it not only fails to provide that value under the current legal and operational environment, but rather often causes conflicts with existing systems. Start-up products that do not consider the constraints of existing laws and operational environments to a great extent are expected to cause such problems. However, since new values have the potential to provide benefits not previously available to humankind, the focus should be on how to accommodate and transform society rather than dismissing them as incompatible with existing laws and operational environments.

This paper focuses on the life cycle as a design concept to address this problem. Much of the discussion of life cycles to date has focused on life cycles for the System of Interest. This paper makes a clear distinction between the lifecycle of the law, the operational environment, and the object. We then propose a framework that considers the interactions among these three life cycles. The possibility of conflict-free social design by utilizing the proposed framework is also explained using the introduction of electric kickboards in Japan as a case study.

This paper aims to address vibration problems that occur in machines, structures, and vehicles. Vibration is one of the causes of various issues in these systems. While vibration problems can arise from various factors, the vibration can be suppressed by optimizing the shape of the structure if the excitation force can be estimated. Another method is to suppress vibration by placing damping elements in the structure. In this case, more effective damping performance can be achieved by efficiently positioning the damping elements. Therefore, in this paper, we investigate the simultaneous optimization of damper arrangement and model shape. The objective is to minimize the total kinetic energy of the structure, under the constraint of mass. In shape optimization, the modal method is used to derive the shape gradient function considering the effect of the viscous damper, and H¹ gradient method is used to modify the model shape. In damper arrangement optimization, since the number of combinations of dampers is large, the genetic algorithm is used to reduce the computational time. The system for shape optimization using the H¹ gradient method and the shape gradient function, and damper arrangement optimization using a genetic algorithm, is established by combing CAE analysis software HyperWorks and a self-made program. A numerical example shows both the shape optimization and the optimization of damper arrangement work properly. Additionally, it also shows that using a genetic algorithm can significantly reduce the computational time required to find the optimal combination of dampers.

Big data analytics, an essential constituent of smart manufacturing, fuels decision-making by extracting knowledge underlying big data. However, the existing analytics frameworks are heavily resource-dependent and computationally heavy. This creates a digital division in accessing and analyzing the data, known as big data inequality. As such, although large enterprises can utilize big data, small and medium-sized companies fall behind. Moreover, the frameworks often result in black box systems due to a lack of transparency, engagement of human intelligence, and integration of externally generated data. This study sheds some light on developing big data and relevant analytics, mitigating the abovementioned limitations. In particular, this study first articulates the limitations and alternatives in detail. It then elucidates how manufacturing big data can be constructed and made widely accessible by creating digital manufacturing commons. A big data analytics architecture is also proposed to extract knowledge from big data. The analytics consists of four integrated yet independent and modular sub-systems: data exploration system, data visualization system, data analysis system, and knowledge extraction system. The functionalities of each system are described. The sub-system-based modular architecture ensures transparency of the inner processes and engages human intelligence straightforwardly. Finally, considering a real-life machining experiment, this study demonstrates the big data construction process and knowledge extraction from the constructed big data using a developed data visualization tool.

The application of electric vertical takeoff and landing (eVTOL) aircraft to emergency medical services (EMS) is progressing with the expectations of physicians. The study of business and stakeholder needs has been limited to verbal discussions without much visualization or deepening through modeling. This limitation is due to the situation that people discussing in existing consortia have some knowledge about eVTOLs and/or EMS and share some images. Accordingly, they have been able to discuss verbally to some extent. This study aims to propose a reference model to visualize and deepen discussions through modeling to define needs and requirements for EMS eVTOLs, for use by both existing relevant people and new people from different industries who are to form a regional committee and deepen discussions. This study proposes a reference model that represents multiple views (“concept,” “process,” and “architecture”) in diagrams, in contrast to conventional studies and methods that hardly focused on deepening through modeling in the discussion of defining needs and requirements for EMS eVTOLs due to the different purposes from this study. As for the evaluation method, by using the modeled results in the online discussions, the authors check each participant whether they have any differences in recognition in the discussions and what the differences are. The results suggest that the reference model combining the three diagrams is effective in deepening the discussions. Future work includes 1) developing a reference model that takes into account the level of automation of aircraft and EMS operations as well as the roles and responsibilities assumed at that level, 2) applying the method to the discussion of a specific regional committee to validate its effectiveness, and 3) development of a modeling support method.

Pursuing the perception of beauty is a natural instinct for human beings. Makeup, haircuts, and outfits can make people look more exquisite and attractive. Choosing a suitable fashion style is a form of art, and face types play an important role that is closely related to people's style choices. The importance of human appearance lies in giving people a favorable impression, enhancing positive feelings, and increasing charm. This study aims to meticulously classify people's face types based on their facial features and quickly identify a person's face type, enabling people to understand how to wear makeup and choose outfits to enhance their glamour value. The paper proposes a 16-face types classification method as the formula for achieving beauty. The study employs machine learning (ML), including data acquisition, pre-processing, feature extraction, and classification, to automatically identify face types among sixteen categories and assess accuracy using different samples. To design the supervised machine learning system, the study utilizes the vision transformer (ViT) model for feature extraction and the classical classifier random forest algorithm (RF) for classification. Additionally, the results are compared with other classifiers such as support vector machine (SVM), decision tree (DT), Adaboost, and k-nearest neighbor (k-NN).

Technically, the 5S principle is a systematic method for improving productivity, quality, and workplace safety. However, the sustainability of 5S practices in small and medium-sized manufacturing enterprises (SMEs), especially in Indonesia, often faces challenges such as synchronization with other management systems (quality management system, safety and health standardization, environmental standardization, and others). Similarly, there are constraints in building commitment, communication, and stakeholder involvement to ensure the success of 5S practices. As a result, this will impact the sustainability performance of manufacturing SMEs. Therefore, this research aims to develop a conceptual model through a socio-technical perspective approach to enhance the sustainability performance of manufacturing SMEs in Indonesia. The model also involves relational coordination as a mediating variable that bridges the relationship between 5S practices and sustainability performance. The methodology of this study is conducted through survey research and data processing using the SEM AMOS statistical analysis tool. The study's results prove, through hypotheses, that 5S practices with socio-technical dimensions influence sustainability performance through the mediating variable of relational coordination among leaders, employees, customers, and suppliers simultaneously. However, the direct influence of the social and technical dimensions on 5S practices partially does not significantly affect sustainability performance. Therefore, it can be concluded that the conceptual model is a cohesive unity between the social and technical dimensions of 5S practices, relational coordination, and sustainability performance. Nevertheless, to strengthen the robustness of the conceptual model, further validation is needed through future studies based on other sectors, such as the service sector or different geographic locations.

The objective of this study is to design self-deployable membranes integrated with elastic frames that can be deployed by intrinsic elasticity. The deployment by elasticity is relatively simple rather than mechanical and hydraulic actuating systems so that deployable structures do not lose the advantages of having compactness and portability. In this study, the elastic convex tape with a characteristic arc-shaped cross section (so-called carpenter tape) was used as a driving force to deploy membranes. Numerical simulation revealed that until the elastic buckling occurred, the stiffness of the convex tape was 50 times higher than that of a flat tape with the equivalent width and thickness. We fabricated the deployable membrane with the pattern of the origami-based deployable array by Zirbel et al. using a sheet of paper and integrated three convex tapes on it symmetrically along the straight fold lines of the membrane. In the deployment experiment, the membrane was successfully deployed from 100 mm to 700 mm in diameter within 0.34 seconds; i.e., the membrane integrated with the convex tapes was self-deployable. Also, the convex tapes worked as supporting frames to maintain the deployed shape of the membrane owing to its high stiffness.

This paper presents a novel multimodal optimization algorithm by modifying our previously proposed gravitational particle swarm algorithm (GPSA). The conventional GPSA has demonstrated its ability to generate multiple design patterns for mechanical engineering problems, surpassing traditional methods. However, an important challenge in the conventional GPSA pertains to determining its control parameter. To address this challenge, the study proposes a modified version of GPSA called αGPSA, where the value of control parameter is adjusted based on a linear mapping of particle fitness values. Experimental evaluations were conducted using a simple multimodal optimization problem. The experimental results demonstrate that the proposed αGPSA achieves better performance in terms of peak ratio and success rate. Furthermore, the proposed αGPSA reduced sensitivity to the control parameter, streamlining the process of parameter selection for users compared to the conventional GPSA.

This paper examines the effects of lubrication and cooling techniques on cutting force generated during milling Inconel 718. The study focuses on three different lubrication cooling strategies, namely dry, chilled, and chilled minimum quantity lubrication (MQL). In this study, the cutting parameters considered are a cutting speed between 100 and 140 m/min, a feed rate between 0.1 and 0.2 mm/tooth, and a constant depth of cut of 0.1 mm. 720 ml/h of Synkool 300G was used as the cutting fluid during the experiments. The results of the experimental analysis reveal that the chilled MQL strategy exhibits a noteworthy reduction in the main cutting force, even under high cutting speed conditions. This reduction in cutting force signifies improved machining efficiency and suggests the effectiveness of chilled MQL as a cooling and lubricating technique during the milling of Inconel 718. This research contributes to the optimization of cutting parameters and the selection of suitable cooling/lubricating strategies for improved machining performance and tool life in Inconel 718 milling.

SMEs are the main factor driving the country's economic growth. However, SMEs experience various difficulties in maintaining their business competitiveness. Therefore, they must carry out evaluations and improvements to improve their business performance. One of the management tools used to measure performance is the Balanced Scorecard (BSC). KPIs (key performance indicators) are used to determine the right initiatives to achieve targets. Unfortunately, the determination of process initiatives is usually based solely on previous experience, and there is no continuous improvement to find the best-targeted initiatives. Through kaizen, efforts to achieve targets can be carried out continuously and gradually using the PDCA pattern. This effort is a form of standardized improvement, so business performance is hoped to increase. The BSC and kaizen integration methods will complement each other to meet SMEs' needs and continuously improve their business performance. The research was conducted through case studies on SMEs manufacturing Batik Fashion. This study used surveys, discussions, and questionnaires to obtain data. This study proves that the kaizen approach can support the use of BSC in achieving goals and improving business performance in SMEs.

Simulation-based optimization often requires many simulations, which can be challenging to adapt due to time constraints. To address this issue, constructing approximators for simulations, such as the finite element method using machine learning, has gained attention. However, constructing these approximators requires a significant amount of training data. For this problem, we proposed an integration neural network as a highly accurate approximator with small data. Our method is based on Weierstrass’ approximation theorem, which uses a polynomial approximation. We constructed the integration neural network by integrating a linear approximator, which uses deductive knowledge to constrain the shape of the approximation curve between training points through multiple regression analysis, with a nonlinear approximator, which uses inductive learning to reduce overlearning of the linear approximator and correct errors. In this paper, by applying the approximator theorem one step further, we reduced the computational complexity of the learning process by simplifying and improving the network structure. Our experiments show that we can construct approximators with almost the same accuracy as previous methods while reducing the number of weight updates in the learning process to about 5%. Furthermore, by analyzing the weights of the approximators, we confirmed that the basic concept drove and that the improved integration neural network could learn with appropriate weights.

Manufacturing industry is transitioning towards a new stage called personalized and regionalized production, moving away from mass production and customization. In this stage, 3D printing or additive manufacturing technology plays a vital role. While utilizing 3D printing technology for regionalized-personalized production, appropriate supporting systems are needed to facilitate a seamless customer-producer interaction. The authors have proposed a customer-producer interaction system consisting of five system components: input, modeling, feedback, output, and delivery modules. The complexity of these components must be kept as minimal as possible to achieve the goal: seamless interaction between customer and producer. From this point of view, this paper analyzes the abovementioned customer-producer interaction system components using axiomatic design theory. The concepts of functional requirements, design parameters, coupled design, decoupled design, uncoupled design, design matrix, and design equation of the axiomatic design theory are used to analyze the system components. It is found that these concepts can identify bottlenecks in the system itself and its components. As a result, designing, constructing, implementing, and maintaining the system become more systematic and less esoteric.

This paper presents a method to improve the motion performance of industrial machines. Their motion trajectories are optimized in B-spline representation, in which control points and knot vectors are adjusted mainly. Positions of control points should be optimized such that tolerances around corners are satisfied as constraints. The number of control points is reduced by assigning straight-line segments as target trajectories and constraining the range of control points around start and end position of each line segment. The control polygons can be explicitly set within a range of tolerances around corners. The proposed problem formulation can be successfully solved by a nonlinear programming technique. A trajectory generation example demonstrates the effectiveness of the proposed in which minimal-time and tolerance satisfaction are achieved.

The authors propose a design methodology for a Web 3 Service Architecture that enables Self-Sovereign Services. Sovereign and Decentralized ID requires a suitable policy agent. This paper provides a basic description of blockchain, smart contracts, and Self-Sovereign services. The policy agent is determined by a score based on policies pre-established by the client and user logs. This provides dynamic access control. The authors implemented the service infrastructure of Self-Sovereign in Web3 and confirmed its feasibility. In addition, a delivery service is presented as an example of a Web3 Service Architecture.

This paper proposes a user-centered design method for the entire process, from needs discovery to design solution derivation. The proposed method consists of five steps: visualize users’ evaluation structure, select the needs to be the design target, quantitatively extract design variables related to the selected needs, conduct sensory evaluations using samples created by the experimental design method, and derive the design solution using rough sets. Evaluation Grid Method is used for the discovery of needs and design variables. For the selection of needs, we refer to the quality classification by Kano model. The importance is used as an indicator for the selection of design variables. Rough sets are applied to the derivation of design solutions. This paper applies the proposed method to the design of a perfume bottle as a case study and derives design solutions that satisfy the needs of each cluster. The proposed method can potentially achieve user-centered products that reflect users’ evaluation structures. Various applications of our proposed method contribute to the development of user-centered design. The proposed method is expected to be applied to a wide range of products and services, contributing to the development of user-centered design.

Robot avatars are attracting attention as a means of remote communication. One of the elements required when using a robot avatar to work and communicate with a partner in another location is the conveyance of information by pointing in order to share the location of objects and other information. However, it has not yet been fully evaluated to what extent pointing gesture by a robot avatar, which is treated as its own alter ego, is able to convey spatial information. In this study, we developed a robot avatar that realizes the tele-immersion of communication and evaluated the degree to which pointing information by the robot avatar can be conveyed to the other person through an evaluation experiment. The results showed that the information conveyed by the pointing gesture of the robot avatar using a humanoid communication robot was generally communicated and effective. In the case of the robot avatar that can be programmed to point in the correct direction, it was found that information is conveyed to some extent by pointing with the hand without using the index finger.

Micro screws with sizes M2.0 or smaller are widely used to assemble smartphones, tablets, and wearable devices. Due to the delicate nature of the assembled parts, the screws often require tightening torques less than 100 mNm with an accuracy in the range of ±5%. In recent years, high-performance electric drivers have been developed to meet these requirements. However, optimizing screw tightening conditions for micro screws of M2.0 or smaller remains challenging because the axial force during screw tightening cannot be directly measured using conventional methods. Consequently, the optimization process relies on time-consuming and costly trial-and-error methods. To address this issue, this study proposes a system that leverages IoT sensing technology and a machine-learning regression prediction model to accurately estimate the axial force during micro screw tightening. In the data collection phase, a system was designed to sense and capture multivariate time-series data, such as tightening torque, pushing force, and vibration of the electric screwdriver during screw fastening. Subsequently, a machine-learning regression prediction model was developed to accurately estimate the axial force of the screw based on the collected data. Experimental validation using M2 cross-recessed pan head screws demonstrated that the proposed system achieves axial force estimation accuracy within 5%. This study offers a potentially effective approach to optimize screw tightening conditions for micro screws, enabling efficient and reliable assembly processes in the production of electronic devices.

Filters are often employed in fluid transport lines that produce beverages, serving as a countermeasure against foreign objects. However, when these filters become clogged during removal, this can lead to an enlargement of the openings or damage to the mesh, leading to secondary generation of foreign objects. Thus, a system that continuously monitors to prevent accidents before they occur is necessary. However, it can be difficult to learn due to the absence of data from actual abnormal situations, and various elements intertwine on the production floor. Therefore, it is necessary to verify which methods are optimal for responding to these situations, and analyze elements for problem identification and improvement. In this study, we leverage the pressure loss caused by filter clogs in the fluid conveyance lines that produce beverages to validate various anomaly detection methods through real simulations. We test the appropriateness of each method based on the nature of the problem and the characteristics of the data, thereby enhancing the interpretability of the model. We compare the detection capabilities of different anomaly detection methods and perform an analysis of feature importance to clarify the importance of each element. Since the results of anomaly detection methods can vary based on the nature of the problem and the characteristics of the data, making interpretability clear can make the results of the anomaly detection methods easier to understand and improve prediction accuracy. By understanding the causes of abnormalities and the contribution of characteristics, it is possible to suppress the occurrence of foreign objects.