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The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

The objective of this paper is to quantitatively assess shear band evolution by using two-dimensional discrete element method (DEM).

The DEM model was first calibrated by retrospectively modelling existing triaxial tests. A series of DEM analyses was then conducted with the focus on the particle rotation during loading. An approach based on particle rotation was developed to precisely identify the shear band region from the surrounding. In this approach, a threshold rotation angle ω₀ was defined to distinguish the potential particles inside and outside the shear band and an index g(ω₀) was introduced to assess the discrepancy between the rotation response inside and outside shear band. The most distinct shear band region can be determined by the ω₀ corresponding to the peak g(ω₀). By using the proposed approach, the shear band development of two computational cases with different typical localised failure patterns were successfully examined by quantitatively measuring the inclination angle and thickness of shear band, as well as the microscopic quantities.

The results show that the shear band formation is stress-dependent, transiting from conjugated double shear bands to single shear band with confining stress increasing. The shear band evolution of two typical localised failure modes exhibits opposite trends with increasing strain level, both in inclination angle and thickness. Shear band featured a larger volumetric dilatancy and a lower coordination number than the surrounding. The shear band also significantly disturbs the induced anisotropy of soil.

This paper proposed an approach to quantitatively assess shear band evolution based on the result of two-dimensional DEM modelling.

To solve the problems caused by using precise molds for copper column positioning in the current column grid array package, this paper aims to optimize the proposed friction plunge micro-welding (FPMW) technology without mold assistance, to overcome the problems of low interfacial bonding strength, shrinkage cavities and flash defects caused by the low hold-tight force of solder on the copper column.

A pressurizing device installed under the drill chuck of the friction welding machine is designed, which is used to apply a static constraint to the solder ball obliquely downward to increase the hold-tight force of the peripheral solder on the copper column during welding and promote the friction metallurgical connection between them.

The results show that the application of static constraint during welding can increase the compactness of the solder near the friction interface and effectively inhibit occurrences of flash, shrinkage cavities and crystal defects such as vacancies. Therefore, compared with the unconstrained (UC) FPMW, the average strength of the statically constrained (SC) FPMW joints and aged SC-FPMW joints can be increased by 51.1% and 122.6%, and the problem of the excessive growth of the interfacial connection layer in the UC-FPMW joints during aging can be effectively avoided.

The application of static constraint effectively inhibits the occurrence of defects such as shrinkage cavities, vacancies and flash in FPMW joints, and the welding quality is significantly improved.

Despite the many advantages this type of equipment offers, there are still some major drawbacks. Linear cutting machine (LCM) cannot accurately simulate the true rock-cutting process as 1. it does not account for the circular path along which tunnel boring machine (TBM) disk cutters cut the tunnel face, 2. it does not accurately model the position of a disk cutter on the cutterhead, 3. it cannot perfectly replicate the rotational speed of a TBM. To enhance the knowledge of these issues and in order to mimic the real rock-cutting process, a new lab testing equipment was developed by Hyundai Engineering and Construction.

A new testing machine called rotary cutting machine (RCM) is designed to simulate the excavation process of hard-rock TBMs and includes features such as TBM cutterhead, RPM simulation, constant normal force mode and constant penetration rate mode. Two sets of tests were conducted on Hwandeung granite using different disk cutter sizes to analyze the cutting forces in various excavation modes. The results are analyzed using statistical analysis and dimensional analysis. A new model is generated using dimensional analysis, and its results are compared against the results of actual cases.

The effectiveness of the new RCM test was demonstrated in its ability to apply various modes of excavation. Initial analysis of chip size revealed that the thickness of the chips is largely dependent on the cutter spacing. Tests with varying RPM showed that an increase in RPM results in an increase in the normal force and rolling force. The cutting coefficient (CC) demonstrated a linear correlation with penetration. The optimal specific energy is achieved at an S/p ratio of around 15. However, a slightly lower S/p ratio can also be used in the design if the cutter specifications permit. A dimensional analysis was utilized to develop a new RCM model based on the results from approximately 1200 tests. The model's applicability was demonstrated through a comparison of TBM penetration data from 26 tunnel projects globally. Results indicated that the predicted penetration rates by the RCM test model were in good agreement with actual rates for the majority of cases. However, further investigation is necessary for softer rock types, which will be conducted in the future using concrete blocks.

The originality of the research lies in the development of Hyundai Engineering and Construction’s advanced full-scale laboratory rotary cutting machine (RCM), which accurately replicates the excavation process of hard-rock tunnel boring machines (TBMs). The study provides valuable insights into cutting forces, chip size, specific energy, RPM and excavation modes, enhancing understanding and decision-making in hard-rock excavation processes. The research also presents a new RCM model validated against TBM penetration data, demonstrating its practical applicability and predictive accuracy.

This study aims to determine the effect of replacing a portion of the cement in the concrete mixture with silica fume (SF) on the corrosion resistance of reinforcing bars, the compressive strength of concrete and the tensile strength of hook bars in both corroded and non-corroded external joints of structures. The external beam-column connection was studied because of its critical role in maintaining structural continuity in all three directions and providing resistance to rotation.

In external concrete joints, the bars at the end of the beams are often bent at 90° to form hooks that embed in columns. Owing to the importance of embedding distance and the need to understand its susceptibility to corrosion damage from chloride attack, a series of experiments were conducted on 12 specimens that accurately simulate real-site conditions in terms of dimensions, reinforcement and hook bars. SF was replaced with 10% and 15% of the weight of cement in the concrete mixture. To simulate corrosion, the specimens were subjected to accelerated corrosion in the laboratory by applying a low continuous current of 0.35 mA for 58 days.

The results revealed the effect of SF in improving the compressive strength of concrete, the pullout resistance of the hook bars and the corrosion resistance. In addition, it showed an apparent effect of the corrosion of reinforcing bars in reducing the bonding strength of hook bars with concrete and the effect of SF in improving this strength.

It was noted that the improvement of the results, achieved by replacing 10% of the weight of cement with SF, was significantly close to the results obtained by replacing 15% of the SF. It is recommended that an SF ratio of 10% be adopted to achieve the greatest economic savings.

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged robot. The autonomy of obstacle-surmounting is reflected in obstacle recognition based on multi-frame point cloud fusion.

In this paper, first, for the problem that the lidar on the robot cannot scan the point cloud of low-height obstacles, the lidar is driven to rotate by a 2D turntable to obtain the point cloud of low-height obstacles under the robot. Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping algorithm, fast ground segmentation algorithm and Euclidean clustering algorithm are used to recognize the point cloud of low-height obstacles and obtain low-height obstacle in-formation. Then, combined with the structural characteristics of the robot, the obstacle-surmounting action planning is carried out for two types of obstacle scenes. A segmented approach is used for action planning. Gait units are designed to describe each segment of the action. A gait matrix is used to describe the overall action. The paper also analyzes the stability and surmounting capability of the robot’s key pose and determines the robot’s surmounting capability and the value scheme of the surmounting control variables.

The experimental verification is carried out on the robot laboratory platform (BIT-6NAZA). The obstacle recognition method can accurately detect low-height obstacles. The robot can maintain a smooth posture to cross low-height obstacles, which verifies the feasibility of the adaptive obstacle-surmounting method.

The study can provide the theory and engineering foundation for the environmental perception of the unmanned platform. It provides environmental information to support follow-up work, for example, on the planning of obstacles and obstacles.

Lean management tools are becoming increasingly applied in different types of organizations around the world. These tools have shown their significant contribution to improving business performance. In this vein, the purpose of this paper is to examine the influence of lean management on both occupational safety and operational excellence in Tunisian companies.

A survey was conducted among Tunisian companies, and it resulted in the collection of 62 responses that were analyzed using the software SPSS. In addition, a conceptual model linking the practices of the three basic concepts was designed to highlight the hypotheses of the research. Subsequently, factor analysis and structural equation method analysis were conducted to assess the validation of the assumptions.

The results obtained have shown that lean management has a significant impact on occupational safety. Similarly, occupational safety has a significant impact on operational excellence. However, lean management does not have a significant impact on operational excellence.

This work highlighted the involvement of small and medium-sized enterprise’s managers from emerging economies in the studied concepts’ practices. Likewise, it testified to the impacts of lean management on occupational safety and operational excellence in the Tunisian context.

Large optical mirror processing systems (LOMPSs) consist of multiple subrobots, and correlated disturbance terms between these robots often lead to reduced processing accuracy. This abstract introduces a novel approach, the nonlinear subsystem adaptive dispersed fuzzy compensation control (ADFCC) method, aimed at enhancing the precision of LOMPSs.

The ADFCC model for LOMPS is developed through a nonlinear fuzzy adaptive algorithm. This model incorporates control parameters and disturbance terms (such as those arising from the external environment, friction and correlation) between subsystems to facilitate ADFCC. Error analysis is performed using the subsystem output parameters, and the resulting errors are used as feedback for compensation control.

Experimental analysis is conducted, specifically under the commonly used concentric circle processing trajectory in LOMPS. This analysis validates the effectiveness of the control model in enhancing processing accuracy.

The ADFCC strategy is demonstrated to significantly improve the accuracy of LOMPS output, offering a promising solution to the problem of correlated disturbances. This work holds the potential to benefit a wide range of practical applications.

The purpose of this paper is to design a climbing robot connected by a connecting rod mechanism to achieve multi-functional tasks such as obstacles crossing and climbing of power transmission towers.

A connecting rod type gripper has been designed to achieve stable grasping of angle steel. Before grasping, use coordination between structures to achieve stable docking and grasping. By using the alternating movements of two claws and the middle climbing mechanism, the climbing and obstacle crossing of the angle steel were achieved.

Through a simple linkage mechanism, a climbing robot has been designed, greatly reducing the overall mass of the robot. It can also carry a load of 1 kg, and the climbing mechanism can perform stable climbing. The maximum step distance of the climbing robot is 543 mm, which can achieve the crossing of angle steel obstacles.

A transmission tower climbing mechanism was proposed by analyzing the working environment. Through the locking ability of the screw nut, stable clamping of the angle steel is achieved, and a pitch mechanism is designed to adjust the posture of the hand claw.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.