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The purpose of this study is to find the best geometries among the cylindrical, enamel and honeycomb geometries based upon the mechanical properties (tensile test, compression test and shear test). Further this obtained geometry could be used to fabricate products like exoskeleton and its supporting members.

The present research focuses on the mechanical testing of cylindrical, enamel and honeycomb-shaped parts fabricated through multi-jet printing (MJP) process with a wall thickness of 0.26, 0.33, 0.4 and 0.66 mm. The polymer specimens (for tensile, compression and shear tests) were fabricated using a multi-jet fusion process. The experimental results were compared with the numerical modelling. Finally, the optimal geometry was obtained, and the influence of wall thicknesses on various mechanical properties (tensile, compression and shear) was studied.

In comparison to cylindrical, enamel structures the honeycomb structures required less time to fabricate and had lower tensile, compressive and shear strengths. The most efficient geometry for fully functional parts where tensile, compressive and shear forces are present during application – cylindrical geometry is preferred followed by enamel, and then honeycomb. It was found that as the wall thickness of various geometries was increased, their ability to withstand tensile, compressive and shear loads also enhanced. The enamel shape structure exhibits greater strain energy storage capacity than other shape structures for compressive loads, and the strength to resist the compressive load will be lower. In the case of cylindrical geometries for tensile loading, the resisting area toward the loading will be higher in comparison to honeycomb- and enamel-based structures. At the same time, the ability to store the stain energy is less. The results of the tensile, compression and shear load finite element analysis using ANSYS are in agreement with those of the experiments.

From the insight of literature review, it is found that a wide range of work is done on fused deposition modeling (FDM) process. But in comparison to FDM, the MJP provide the better dimensional accuracy and surface properties (Lee et al., 2020). Therefore, it is observed that past research works not incorporated the effect of wall thickness of the embedded geometries on mechanical properties of the part fabricated on MJP (Gibson, n.d.). Hence, in this work, effect of wall thickness on tensile, compression and shear strength is considered as the main factor for the honeycomb, enamel and cylindrical geometries.

This paper aims to design a magnetostrictive tactile sensor for surface depth detection. Unlike the human finger, although most tactile sensors have high sensitivity to pressure, they cannot detect millimeter-level depth information on the surface of objects precisely. To enhance the ability to detect surface depth information, a piezomagnetic sensor combining inverse magnetostrictive effect and bionic structure is developed in this paper.

A magnetostrictive tactile sensor based on Galfenol [(Fe₈₃Ga₁₇)_99.4B_0.6] is designed and studied for surface depth measurement. The optimal structure of the sensor is determined by experiment and theory. The test platforms for static and dynamic characteristics are set up. The static and the dynamic sensing performance of the sensor are studied experimentally.

The sensor can detect 0–2 mm depth change with a sensitivity of 91.5 mV/mm. A resolution of 50 µm can be achieved in the depth direction. In 50 cycles of loading and unloading tests, the maximum error of the sensor output voltage amplitude is only 2.23%.

The sensor can measure the depth information of object surface precisely with good repeatability through sliding motion and provide reference for object surface topography detection.

The implementation of smart maintenance (SM) has greatly benefited facility managers, construction project managers and other stakeholders within the built environment. Unfortunately, its actualization for stakeholders in the built environment in the fourth industrial revolution (4IR) era remains a challenge. To reduce the challenge, this study aims at conducting a bibliometric analysis to unearth the critical success factors supporting SM implementation. The future direction and practice of SM in the construction industry were also explored.

A bibliometric approach was adopted for reviewing articles extracted from the Scopus database. Keywords such as (“smart maintenance“) OR (“intelligent maintenance”) OR (“technological maintenance”) OR (“automated maintenance”) OR (“computerized maintenance”) were used to extract articles from the Scopus database. The studies were restricted between 2006 and 2021 to capture the 4IR era. The initial extracted papers were 1,048; however, 288 papers were selected and analysed using VOSviewer software.

The findings revealed that the critical success factors supporting the implementation of SM in the 4IR era are collaboration, digital twin design, energy management system and decentralized data management system. Regarding the future practice of SM in the 4IR era, it was also revealed that SM is possible to evolve into maintenance 4.0. This will support the autonomous maintenance of infrastructures in the built environment.

The use of a single database contributed to the limitation of the findings from this study.

Despite the limitations, the findings of this study contributed to practice and research by providing stakeholders in the built environment with the direction of SM practice.

Stakeholders in the built environment have clamoured to implement SM in the 4IR era. This study provided the critical success factors for adopting SM, guaranteeing the 4IR era. It also provides the research trends and direction of SM practice.

Human skin temperature data can provide reference advice for diagnosing many diseases, but current wearable skin temperature monitoring systems have few points and may miss temperature information in critical areas. This paper aims to develop a wearable system that can be used for local temperature monitoring and restore better the actual state of local human temperature by exploring ways to extend more temperature measurement points. This will provide better assistance in developing medical targeting and intelligent clothing.

The temperature measurement system contains modules for temperature monitoring, digital-to-analog conversion and regulated power supply, enabling fast reading of 12 channels of monitoring data. The microprocessor unit is the STM32F407. The instructions and control modes are written in C. The waist area was chosen as the monitoring area because it is susceptible to temperature, and many diseases are associated with skin temperature. Twelve points, including temperature-related acupuncture points and heat-sensitive points, were selected for testing and the data results agreed well with the infrared imaging results.

The waist is selected as the monitoring object, and an easy-to-wear waist temperature monitoring belt is designed to verify the application value of the system. The development of the system provides reference suggestions for the exploration of multi-point temperature monitoring systems and the integration capabilities of temperature measurement modules in wearable multifunctional systems.

In addition to waist temperature monitoring, the wearable temperature measurement system developed in this study can also be applied to other body parts. In addition, the system can be efficiently and effectively combined with various garments, making it a useful tool for researching human skin temperature.

The wearable temperature monitoring system designed in this paper extends the number of temperature test points to 12. The number of test points covers as many localized body areas as possible to indeed reproduce the temperature distribution of the human body. In addition, the selection of test points combines medically relevant body points with physiologically relevant heat-sensitive areas, which makes the temperature measurement data more valuable.

The six-axis force/torque sensor based on a Y-type structure has the advantages of simple structure, small space volume, low cost and wide application prospects. To meet the overall structural stiffness requirements and sensor performance requirements in robot engineering applications, this paper aims to propose a Y-type six-axis force/torque sensor.

The performance indicators such as each component sensitivities and stiffnesses of the sensor were selected as optimization objectives. The multiobjective optimization equations were established. A multiple quadratic response surface in ANSYS Workbench was modeled by using the central composite design experimental method. The optimal manufacturing structural parameters were obtained by using multiobjective genetic algorithm.

The sensor was optimized and the simulation results show that the overload resistance of the sensor is 200%F.S., and the axial stiffness, radial stiffness, bending stiffness and torsional stiffness are 14.981 kN/mm, 16.855 kN/mm, 2.0939 kN m/rad and 6.4432 kN m/rad, respectively, which meet the design requirements, and the sensitivities of each component of the optimized sensor have been well increased to be 2.969, 2.762, 4.010, 2.762, 2.653 and 2.760 times as those of the sensor with initial structural parameters. The sensor prototype with optimized parameters was produced. According to the calibration experiment of the sensor, the maximum Class I and II errors and measurement uncertainty of each force/torque component of the sensor are 1.835%F.S., 1.018%F.S. and 1.606%F.S., respectively. All of them are below the required 2%F.S.

Hence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

Most of the linear encoders are based on optics. The accuracy and reliability of these encoders are greatly reduced in polluted and noisy environments. Moreover, these encoders have a complex structure and large sensor volume and are thus not suited to small application scenarios and do not have universality. This paper aims to present a new absolute magnetic linear encoder, which has a simple structure, small size and wide application range.

The effect of swing error is analyzed for the sensor structural arrangement. A double-threshold interval algorithm is then proposed to synthesize multiple interval electrical angles into absolute angles and convert them into actual displacement distances.

The final linear encoder measurement range is 15.57 mm, and the resolution reaches ± 2 µm. The effectiveness of the algorithm is demonstrated experimentally.

The linear encoder has good robustness, and high measurement accuracy, which is suitable for industrial production. The linear encoder has been mass-produced and used in an electric power-assisted braking system.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

The aim of this review is to present together the studies on textile-based moisture sensors developed using innovative technologies in recent years.

The integration levels of the sensors studied with the textile materials are changing. Some research teams have used a combination of printing and textile technologies to produce sensors, while a group of researchers have used traditional technologies such as weaving and embroidery. Others have taken advantage of new technologies such as electro-spinning, polymerization and other techniques. In this way, they tried to combine the good working efficiency of the sensors and the flexibility of the textile. All these approaches are presented in this article.

The presentation of the latest technologies used to develop textile sensors together will give researchers an idea about new studies that can be done on highly sensitive and efficient textile-based moisture sensor systems.

In this paper humidity sensors have been explained in terms of measuring principle as capacitive and resistive. Then, studies conducted in the last 20 years on the textile-based humidity sensors have been presented in detail. This is a comprehensive review study that presents the latest developments together in this area for researchers.

This study aims to outline the current challenges in ultrasonic additive manufacturing (AM). AM has revolutionized manufacturing and offers possible solutions when conventional techniques reach technological boundaries. Ultrasonic additive manufacturing (UAM) uses mechanical vibrations to join similar or dissimilar metals in three-dimensional assemblies. This hybrid fabrication method got attention due to minimum scrap and near-net-shape products.

This paper reviews significant UAM areas in process parameters such as pressure force, amplitude, weld speed and temperature. These process parameters used in different studies by researchers are compared and presented in tabular form. UAM process improvements and understanding of microstructures have been reported. This review paper also enlightens current challenges in the UAM process, process improvement methods such as heat treatment methods, foil-to-foil overlap and sonotrode surface roughness to increase the bond quality of welded parts.

Results showed that UAM could solve various problems and produce net shape products. It is concluded that process parameters such as pressure, weld speed, amplitude and temperature greatly influence weld quality by UAM. Post-weld heat treatment methods have been recommended to optimize the mechanical strength of ultrasonically welded joints process parameters. It has been found that the tension force is vital for the deformation of the pre-machined structures and for the elongation of the foil during UAM bonding. It is recommended to critically investigate the mechanical properties of welded parts with standard test procedures.

This study compiles relevant research and findings in UAM. The recent progress in UAM is presented in terms of material type, process parameters and process improvement, along with key findings of the particular investigation. The original contribution of this paper is to identify the research gaps in the process parameters of ultrasonic consolidation.