Fused filament fabrication is a type of material extrusion process category of additive manufacturing. Because the material is prepared in the form of filaments, a wide variety of materials including composite materials with continuous fibers can be used. With the recent increase in environmental consciousness, the use of biodegradable composites using polylactic acid (PLA) and continuous cellulose nanofiber (CNF) strings has garnered attention from the scientific community. However, the fiber content of the composites remains low, preventing full exploitation of the ultrahigh intrinsic strength of CNFs. In this study, we proposed two methods to increase fiber content. First, we modified the cross-sectional shape of the filament from circular to rectangular to increase the fiber content. Second, we optimized the process parameters during filament fabrication by adjusting the feed rates of continuous CNFs and PLA, resulting in a higher fiber content up to 35%. Following this, filaments with higher fiber content were used in fabrication experiments. Tensile tests of the fabricated specimens showed that the mechanical strength increased with the fiber content. Finally, we present an application example of the developed CNF filament for reinforcing finger orthosis.
In-process measurement of changes in grinding wheel condition is expected to prevent machining defects. A method for monitoring grinding wheel condition through grinding vibration analysis was examined in this study. To achieve this, a measurement device was developed by housing two accelerometers, a compact microcontroller, a wireless transmitter, and two batteries in an acrylic case mounted on the grinding wheel, enabling vibration acquisition and wireless transmission during operation. Two measurement methods were implemented in the developed system. The first is a raw data transmission method, which measures biaxial acceleration at a sampling frequency of 24 kHz and simultaneously transmits the data to a personal computer (PC). The second is an edge computing method, which calculates anomaly scores using a neural network within the microcontroller and transmits only the results. The advantage of the raw data transmission method is that it allows various analyses using the raw acceleration data received by the PC. However, the disadvantage is the heavy load on the network due to the large volume of data transmitted. In contrast, the edge computing method significantly reduces data volume and power consumption by transmitting only anomaly scores, thereby extending battery life. Experiments were conducted using a surface grinding machine. In the raw data transmission method, it was found that the integrated value of the absolute acceleration measured by the developed device strongly correlates with the magnitude of the grinding force. This result indicates that the developed device can estimate the grinding force. In the edge computing method, the anomaly scores calculated within the microcontroller correlated with the grinding force. This confirms that the developed device can estimate the grinding force using this method as well. Furthermore, it was demonstrated that this method can detect abnormalities in wheel rotational speed, changes in wheel condition, and the occurrence of grinding burn.
Environmental temperature changes are a major factor in machining accuracy degradation in machine tools. As maintaining a constant environmental temperature is costly, reducing thermal deformation through machine design is important. For this purpose, it is essential to clarify the mechanisms of thermal deformation caused by environmental temperature variations. In recent years, machine tools have increasingly been required to incorporate covers for chip and coolant management as well as compliance with safety regulations. However, covers influence the heat transfer between the machine and the environment and complicate the mechanism of thermal deformation. In this study, the influence of covers on the heat transfer and thermal displacement of a turning center was investigated. The relationship between thermal displacement and temperature variations in the ambient air and machine structure was examined for different cover configurations under environmental temperature variations. Experimental results demonstrated that, while the influence of environmental temperature changes was suppressed by the machine outer cover, the temperature difference of the air within the machine outer cover increased due to the mechanical configuration, resulting in thermal deformation. Additional covers suppressed the temperature rise of the air around the structure and the structure itself, but the temperature distribution of the air and the structure was not improved, and thermal deformation was not reduced. Simulation results showed that the heat transfer rate from the air to the structure was reduced by 20% with additional covers. These results indicate that thermally robust machine tools under environmental temperature changes can be developed by appropriately designing the arrangement of covers.
Heat generated in machine tools during operation causes thermal deformation and deteriorates machining accuracy. To suppress thermal deformation and the resulting displacement, strategies such as reducing heat generation, cooling machine elements that generate heat, and compensating for thermal displacement are generally adopted. However, existing methods for estimating and compensating for thermal deformation and displacement can only be adopted in limited situations. In particular, there are few reports on real-time estimation methods that take into account moving parts and actual machine operating conditions. For high-accuracy machining, it is important to understand the temperature field and the associated displacement. In this study, real-time estimation of the temperature field and displacement is carried out on a test apparatus equipped with a ball screw drive system and a linear guideway system. In the estimation process, heat generation values are first calculated from servo data corresponding to the machine operation. Using these calculated values, the temperature field is then derived through the finite volume method. Finally, the thermal displacement is obtained from the temperature field using a simplified estimation method. The results are validated by comparison with experimental data and with results from commercial finite element method software, demonstrating the effectiveness and real-time performance of the proposed approach.
In various manufacturing processes, feedback control systems have been investigated to enhance productivity. However, applications in practical mass production are still limited. This study aimed to develop a closed-loop feedback system involving a new die set for nonstop mass production using a transfer press machine and to demonstrate its effectiveness in the real production of millions of pieces. Displacement and load sensors were embedded in the die set to monitor the product dimension and status of the upsetting punch. An actuator was also installed to adjust the product dimension controlled by threshold-type discrete feedback. Complex wiring from the sensors and their power sources were replaced with dedicated wireless data and power transmission devices to improve the mountability and operability when changing the die set. In the demonstration tests, the product thickness was precisely adjusted to 0.016 mm using the actuator controlled with a feedback command of 0.02 mm. The proposed system has been successfully used for the production of more than 6.5 million pieces during the period from the middle of 2023 to the end of 2025, demonstrating good durability and practicality. To detect a partial punch fracture, the Mahalanobis method is effective even when the fracture area is relatively small. To apply this method when a step-like change in the Mahalanobis distance is inevitable owing to interruptions according to the production schedule, the training data of the first several hundreds of shots need to be used for the production schedules.
Ensuring consistent mesh geometry is essential for mechanical reliability and quality control of knotted nets in factory production line inspections. This paper presents a fully automated visual inspection system that integrates knot detection, mesh topology reconstruction, and real-world dimensional measurements within a distortion-aware deep learning framework. The knots were detected using a YOLOv11-based object detector trained to localize small and densely arranged targets under varying illumination, deformation, and partial occlusion. To enable accurate metric measurements over large net areas, the images captured using a 150° ultrawide-angle lens were rectified through camera calibration and distortion correction. Knot centroids were extracted from the detected bounding boxes and organized using a row-wise directional linking strategy that reconstructed a diamond-shaped mesh topology while avoiding physically implausible connections. Interknot distances were computed in the rectified image plane and converted into real-world measurements using a K-nearest neighbors (KNN) regression model, which compensated for the residual nonlinearities remaining after distortion correction. The scope of inspection in this study was limited to mesh size and knot spacing evaluation. However, missing knots, broken strands, or other structural defects may affect the dimensional consistency of the net and may be indicated indirectly through abnormal mesh measurements. The proposed system is not intended for direct detection or classification of such defects. It was evaluated on a custom dataset of 1,054 industrial fishing net images, achieving a high detection performance with an mAP50 of 0.99 and mAP50–95 of 0.86. The calibration stage achieved distance estimation errors within ±3.53% relative to the nominal mesh size. The results demonstrated that the proposed approach enabled the automated and quantitative assessment of mesh uniformity, providing a practical and scalable solution for industrial net quality inspection.
Additive manufacturing (AM), defined as the “process of joining materials to make objects from three-dimensional model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies” by the American Society for Testing Materials, has been recognized as a remarkable scientific and industrial technique due to its capacity to produce complex and functional parts directly. AM is a process to build up these parts in a layer-by-layer process involving sequential deposition, melting, fusion, and binding of the successive material layers from three-dimensional design data, and has allowed the reduction of waste material, minimal production lead time, eliminated design constraints, and reduced the cost involved. Many industries are currently adopting AM to exploit these advantages, and AM products are expected to find application in a wide range of fields beyond the medical, aerospace, and mold sectors. It is important to note that not all conventionally manufactured parts can be replaced by AM. The objective of this special issue is to collect recent research works focused on recent trends in AM. It includes four papers covering the following topics: • Metal-based powder bed fusion using a laser beam (PBF-LB/M) • Wire and arc-based AM (DED-Arc/W) • Material extrusion (MEX) This issue is expected to help readers understand the recent trends in AM, leading in turn to further research on AM. We deeply appreciate the contributions of all authors and thank the reviewers for their incisive efforts.
Triply periodic minimal surfaces (TPMSs) exhibit excellent mechanical properties. However, their complex geometries impose significant limitations on their fabrication processes. In this study, we fabricate TPMSs using wire and arc-directed energy deposition (DED-Arc) for the first time to leverage its large-scale manufacturing and low production costs. DED-Arc is generally associated with challenges such as distortion caused by high heat input and challenges in fabricating complex geometries. Moreover, TPMS structures feature curved surfaces that include a characteristic overhang in the surface extension direction, i.e., where the width of thin walls increases with height. When fabricating such overhangs, the deposited layers are generally insufficiently tall at the ends of each deposition path. Hence, we propose a novel fabrication strategy incorporating spot deposition, in which localized deposition and cooling are applied repeatedly at the end of each deposition path. Additionally, we devise a method to determine the optimal number of spot depositions based on the overhang angle in the surface extension direction to compensate for the insufficient layer height. Subsequently, we fabricate single- and 27-cell TPMS structures—including Schwarz primitive geometries—using the proposed strategy to evaluate its effectiveness. We evaluate the accuracy of the fabrication process based on X-ray computed tomography measurements, the results of which confirm high geometric fidelity. These findings demonstrate the feasibility of TPMSs fabrication using DED-Arc.
A high-efficiency, high-quality coating technology for pure copper was developed using a multi-beam metal powder deposition method with a rectangular beam profile at the processing point. Pure copper is a metal with antibacterial properties and high thermal and electrical conductivity. Its use in multi-material applications via metal powder deposition is expected to conserve resources and further expand its applications. In this study, a pure copper layer was formed on a stainless-steel substrate using a blue diode laser with high light absorption in pure copper and a rectangular top-hat beam capable of uniform heating of both the substrate and pure copper powder. Compared with a circular beam, the rectangular beam improved layer formation efficiency up to twofold and was also found to reduce dilution, the mixed layer between the layer and substrate. The pure copper layer formed using the rectangular beam exhibited a smaller difference in dilution between the center and edge of the cross-section compared to the circular beam. This demonstrates that the rectangular beam achieves uniform heating, which is beneficial for layer formation using the multi-beam metal powder deposition method.
The behavior of bubble and pore formation during selective laser melting of ceramics remains unclear. In this study, in situ observations of a single laser scan over an alumina powder bed were performed using a simple near-infrared visualization system. A CO 2 laser was scanned over a pressurized powder bed under various irradiation conditions, and the interior of the molten pool was recorded with a high-speed camera. The solidified beads were then analyzed by X-ray computed tomography. The observations revealed bubbles forming at the solid–liquid interface and migrating within the molten pool, which were ultimately trapped as pores in the solidified structure. In addition, a qualitative correlation was established between the pore distribution in the solidified structure and the bubble distribution observed in situ. The influence of laser irradiation conditions on pore formation behavior was systematically clarified. These results demonstrate the effectiveness of near-infrared observation techniques in selective laser melting of oxide ceramics.
The development of advanced manufacturing paradigms is significantly influenced by the ongoing digital transformation and green transformation (GX). In this context, key challenges across various domains, including design, processing, fabrication, inspection, maintenance, and recycling, must be addressed to satisfy the requirements for labor reduction, skill-free operation, and efficiency enhancement throughout the entire production process. Social prosperity must be sustained while concurrently managing resource consumption by linking these challenges. Consequently, the fundamental performance of production tools, such as machine tools, assembly machinery, industrial robots, and measuring instruments, is paramount. Additionally, the circulation of design, evaluation, and operational information within the value cycle should be actively promoted. This special issue explores diverse topics related to GX and its role in promoting cleaner production in manufacturing industries and related sectors. It comprises papers on sustainable manufacturing processes, the circular economy, green supply chains, as well as algorithms and models that address their theoretical foundations. The editor extends their sincere gratitude to all authors for their dedication and high-quality submissions. We also acknowledge the reviewers for their thorough evaluations that have contributed significantly to the excellence of this special issue. Finally, we hope that the publications in this issue will support the advancement of cutting-edge technologies and next-generation systems dedicated to sustainable manufacturing and cleaner production.
Sales and operations planning (S&OP), despite its importance in balancing demand and supply, faces significant challenges due to system complexity, uncertainty, and conflicting objectives. While previous research has primarily examined the effects of integration, flexibility, and inventory control on cost and customer service level under demand uncertainty, it has often overlooked the simultaneous consideration of plan stability, procurement time uncertainty, and supplier capacity constraints. This study addresses these gaps by developing a multi-objective S&OP simulation-optimization model that jointly considers plan stability objectives and capacity-constrained supply order allocation under both demand and procurement time uncertainty. Computational results from an automotive industry case study show that frozen horizon length has a more significant impact on customer service, delivery time, and plan stability than on total profit. A bi-sourcing policy proved more advantageous than single sourcing even under unlimited capacity and lower unit costs, while moderate procurement lead-time uncertainty outperformed deterministic lead times under long supply intervals. This reveals counterintuitive temporal supply dynamics in which lead-time overlaps and order crossings yield favorable logistics cost tradeoffs. The results also indicate that sourcing policies, supply intervals and lead-time uncertainty influence plan stability even when frozen horizon length is fixed. These findings provide manufacturers with insights to balance flexibility and stability in S&OP, while managing multiple uncertainty sources and multi-sourcing strategies in dynamic supply chain environments.
This study aims to automate the production of globes for the visually impaired (VI) and provide low-cost alternatives. This process is achieved using a spherical surface processing machine dedicated to globe fabrication, equipped with a two-axis rotary positioning mechanism and a semiconductor laser. The machine operates based on machining paths generated by a custom-developed computer-aided manufacturing system specifically designed for globe production. As the system generates tool paths from geopolitical information, it supports a variety of applications beyond conventional drilling. These include the creation of raised solid borders, the addition of textures using small point clouds applied exclusively to land areas, and the merging of small-area countries with larger neighboring countries. This allows users to obtain globes tailored to their specific purposes and preferences. As a result, the developed processing system is capable of automatically producing customized globes for VI individuals within one day. In an experiment conducted to investigate which globe characteristics were preferred by several VI participants, no single design was found to be universally preferred. This finding indicates the effectiveness of the proposed system, as it enables customization according to individual user preferences.
A sophisticated chemical mechanical polishing (CMP) technology with in-line optical-thickness verification was developed for shallow-trench isolation formation in gate-all-around field-effect transistors with a multilayered Si/SiGe superlattice. The CMP tools were equipped with in-line optical critical dimension (OCD) measurement and a torque current monitor of the CMP turn-table motor for endpoint detection (EPD). In this study, model-based OCD fitting was applied to estimate the thicknesses of complex multilayered films: a SiN stopper on a thin SiO2 buffer layer over a Si/SiGe/Si/SiGe/Si/SiGe superlattice epitaxially grown on a Si substrate. Immediately after the CMP with the electrical EPD and the in-line OCD measurement, the over-polished thickness of the SiN stopper was within 3 nm on the fin-patterned Si/SiGe superlattice despite the change in the SiO2-CMP rate during continuous wafer processing. This nondestructive CMP control method improves the efficiency and quality of the CMP process in GAAFET fabrication.
When lifting a load using a crane, it must be hoisted directly above its center of gravity (COG) to prevent tilting and swinging, which can lead to serious accidents. Therefore, accurately identifying the COG before lifting is essential for crane safety and is a key technology for crane-lift automation. Although many methods exist for measuring the COG after the load is lifted, they often fail to prevent potential risks. Therefore, for loads with a rectangular bottom, we propose and develop a sensor system capable of detecting COG "before" the load is lifted. A depth camera and a lifting force sensor are mounted on a crane hook. The lifting force sensor also functions as a spring, allowing the lifting force to increase gradually when a crane wire is wound. The direction of the tilting of the load, that is, the direction of the COG, is detected from the change in the depth image of the top surface of the load when the load is lifted only slightly. The horizontal distance to the COG is determined by observing the changes in the lifting force, which varies before and after any edge of the load bottom is slightly lifted. Unless the COG of the load is directly beneath the lifting position, the load typically tilts toward one of the four edges of the rectangular bottom. Subsequently, to determine the COG in a two-dimensional plane, two lifting trials are required when the weight of the load is known, whereas three trials are required if the weight is unknown. Experiments were conducted to detect the COG of loads, confirming the effectiveness and sufficient accuracy of the proposed detection method.
When measuring large, elongated structures such as tunnels, the integration of the local three-dimensional (3D) shapes measured at multiple points using tools such as laser scanners is necessary. However, because tunnel interiors often have smooth, texture-less surfaces, estimating the relative pose between measurement points is difficult. This paper proposes a lightweight 3D measurement method using a single camera and laser projection. The system performs cross-sectional shape measurements using the light-section method and pose estimation using the projected laser features. By introducing a scale optimization approach that minimizes the nearest-neighbor distances between point clouds, accurate global 3D reconstruction is achieved without relying on external sensors. The proposed method enables efficient and precise measurements, even in featureless environments.
The accurate evaluation of pitch deviations in scale gratings is essential to ensure the performance of high-precision positioning systems, such as optical encoders and machine tools. Conventional methods, including interferometry and microscopy, provide high resolution but are limited by a restricted measurement range, environmental sensitivity, and poor suitability for insitu applications. To address these challenges, this paper presents a differential angle sensor that can detect the angles of +/- 1st-order diffracted beams from a scale grating for pitch deviation calibration of the scale grating. The developed sensor employs a pair of adjustable plane mirrors and a single CMOS image sensor to capture +/- 1st-order diffracted beams simultaneously. This configuration eliminates the need for multiple detectors and complex symmetric optics, reducing structural complexity while maintaining high sensitivity. More importantly, gratings of different pitches can be accommodated by simple shifts of mirror positions without reconfiguring the optical structure. The method was validated in two stages. First, comparative experiments with a 1.6 & micro;m-pitch grating confirmed that the configuration achieved stability and sensitivity comparable to conventional layouts. Short-range bidirectional scanning and long-range measurements up to 90 mm showed excellent agreement with reference data from a commercial Fizeau interferometer. Second, adaptability tests on a scale grating with a different pitch of 8 & micro;m demonstrated that lateral mirror translation preserved measurement stability and angular sensitivity, confirming the capability to evaluate multiple gratings without structural modification. These results show that the system attains accuracy equivalent to that of interferometric methods while offering significant advantages in simplicity, adaptability, and suitability for in-situ industrial calibration. This paper highlights a practical, cost-effective approach for high-precision evaluation of linear scale gratings.
This study addresses the limitations of conventional frequency converter-driven dual-motor systems, such as excessive space occupancy and power imbalance between the front and rear motors. An integrated dualmotor synchronous drive system is presented, integrating voltage conversion and variable-frequency functionality. Furthermore, this study proposes two cross-coupling synchronization strategies: a speed-loop compensated proportional integral derivative (PID) control and torque-loop compensated PID control. In accordance with the system architecture, phase-shift control for the triple active bridge converter and direct torque control for the motors are investigated. Under unbalanced load conditions, the proposed speed-loop compensated PID cross-coupling method replaces the conventional single-gain cross-coupling controller, significantly improving speed synchronization accuracy. The torque-loop compensated PID cross-coupled control further enhances synchronization performance. Both simulation and experimental results validate the accuracy and effectiveness of the proposed control strategies.
Three-dimensional (3D) measurement systems are widely used in the machinery industry, and the measuring range has expanded with the popularization of optical probes. As measurement results are highly dependent on the scanning path, a computer-aided testing (CAT) system is developed to automatically generate a scanning path from the computer-aided design (CAD) data of the target. However, in the case of line laser probes, which are commonly used as optical probes, it is necessary to generate scanning paths considering the shape variations along the scanning lines based on the scanning posture. Furthermore, using probes with a wide measurement area, such as a line laser probe, causes overlaps, i.e., the duplication of the measurement areas. Reducing overlaps is required because they cause deterioration of the quality of point-cloud data and increase the amount of data. Focusing on a 3D measurement system using a line laser probe, this study developed a path generation system to automatically create scanning paths from the CAD data of a target and a measurement simulator to detect overlaps. This study presents the measurement results obtained using the scanning paths generated by the proposed CAT system and compares the results of simulations with those of actual measurements.
In this study, the milling of submillimeter-deep stepped micro-grooves on nitrile rubber surfaces was investigated. Rubber products with microstructured surfaces are typically manufactured by molding, which is costly and unsuitable for prototyping or small-lot production. Machining provides a promising alternative but faces challenges due to rubber's flexibility and elastic deformation. Experiments were conducted using a numerically controlled milling machine and cemented carbide end mills with different twist directions and angles. The experiments compared left-twist and right-twist tools, whereras left-twist tools have cutting edges twisted opposite to the conventional right-twist tools. The effects of twist angle and feed rate on burr formation and dimensional accuracy were evaluated in detail. As a result, burr formation was notably suppressed with the left-twist tool, especially at larger twist angles and lower feed rates. In contrast, right-twist tools produced significant burrs and residues due to chip deformation and bouncing. Moreover, cross-sectional profiles measured by laser profilometry revealed that depth errors decreased as feed rate and twist angle decreased. These errors are attributed to elastic deformation and recovery of the rubber surface induced by cutting forces. These findings demonstrate that appropriate tool geometry and machining parameters can achieve burr-free, high-precision stepped microgroove milling on nitrile rubber. These results also provide important insights for the cost-effective and rapid manufacturing of rubber products with microstructured surfaces, especially suited for small-lot and prototype production.
