The company seeks the role of internal function and external partnership to eliminate or reduce the waste generated and its impact on the environment. Internally, Top management needs to commit and actively increase the participation of employees in implementing total quality management and production waste management to enhance business performance. This study surveyed the companies engaged in the industry sector producing finished products while generating waste in the production process. Data collection is carried out using online questionnaires through Google Forms with data analysis using PLS software. One hundred and thirty-six (136) manufacturing companies located in East Java, Indonesia. The results of the data analysis indicated that top management commitment significantly influences firm performance, employee empowerment, and total quality management. Employee empowerment impacts total quality management and production waste management. Total quality management positively influences production waste management and firm performance. In addition, production waste management significantly impacts the firm performance. In addition, top management commitment indirectly affects firm performance through the mediating role of total quality management. However, the mediating effect of production waste management is insignificant in translating top management commitments to firm performance. The result provides a theoretical contribution to developing green supply chain practices and sustainability. Furthermore, the practical contribution provides insight for top management companies that production waste management can improve performance with high management commitment and employee empowerment.

This study aims to investigate and scrutinize the financial performance, represented by the Return on Asset (ROA), considering the mediating roles of Corporate Social Responsibility (CSR) and Sustainable Development Goals (SDGs). The sample selection method used purposive sampling, which used several criteria with the research object being the Mining industry listed on the Indonesia Stock Exchange and the National Center for Sustainability Reporting (NCSR) in 2020-2021. The data were sourced from secondary materials derived from several mining companies. The research employed Structural Equation Modeling (SEM) for data analysis. The results of the study indicate that: (1) CSR has a significant positive effect on SDGs; (2) SDGs have a significant positive effect on financial performance; (3) CSR has a significant positive effect on financial performance; and (4) SDGs can mediate CSR and financial performance. Companies should consider enhancing their CSR disclosure, as it is positively related to SDG achievement and financial performance. Moreover, regulatory bodies may encourage firms to adopt SDGs as part of their CSR initiatives, which could lead to both societal and economic benefits.

This paper presents the results of research on the vibration of the Hyundai Universe bus using an air suspension system and mechanical suspension system when it is run at different speeds on random road surface profiles according to ISO 8608:2016. The research results show that the used air suspension system ensures smooth movement and dynamic safety according to TCVN 6964:2008 (ISO 2631:2003) and VDI 2057:2017 standards. The maximum vehicle speeds on different road classes varied from 105km/h to 65km/h. A vehicle with an air suspension system provided a smaller root mean square of vibration acceleration RMS(Z) than a vehicle with a mechanical suspension system. The root means square of the wheel load RMS(Fz) of a vehicle with an air suspension system is about 99.6% of that of a vehicle with a mechanical suspension system.

In this study, the influence of the volume fraction of the martensite phase as well as the size of the martensite particles on the mechanism of particle fracture in dual-phase steel were examined. A combined continuum/dislocation based approach was used in order to model the average stress in the martensite particles. It was found that the model predictions are in accordance with the experimental results. For the same volume fraction of the martensite particles, the model predicts an increase of the internal stress and the average stress in the martensite particles with increasing the particles size. Since the fracture strength of the martensite depends on its volume fraction, the particle size has no effect on the mechanism of particle fracture. Increasing the volume fraction of the martensite particles results in the enhancement of the internal stress in the martensite particles. However, it has a slight influence on the average stress in the particles. Nevertheless, because of decreasing the fracture strength of martensite with increasing its volume fraction, this parameter has a main role in the occurrence of the particle fracture mechanism.

Calculation plate floor concrete, using a static load which is a gravity load consisting of a live load and a dead load, with various of boundary conditions, floor slabs are orthotropic plate, and rarely account for dynamic loads due to vertical seismic loads, with other boundary conditions, such as Clamped, simply supported, ES (Elastic Support), ER (Elastic Restraint), and ESR (Elastic Support and Restraint). Analytical solution based on the Modified Bolotin Method to analyze floor slab under Vertical Peak Ground Acceleration (PGAv), the natural frequency solution based on auxiliary Levy’s type problems. Dynamic vertical seismic loads using multiline, first line at 0 < t < 0.5 is linear equation, second line at 0.05 < t t 0.6 is linear equation, vertical seismic load with two conditions far fault and near fault, multi-line equation are depending on (PGAv/g). A numerical example is given, for various boundary conditions, and far fault, translational stiffness (kx, ky) and rotational stiffness (cx ,cy), from the results of plate calculations due to dynamic vertical seismic loads with 5 types of edge support, ES (elastic support) is the best result.

Nowadays, composites made of plant-based fibers may be used to polymer resin synthetic fiber reinforced composites since they are less expensive, renewable, abundant, less abrasive, and lightweight. Echinatus fiber obtained from the stem of the echinatus plant in an abundant amount. The main objective of this study was to develop echinatus polyester-resin fiber reinforced composite material and investigate its flexural strength, hardness and tensile strength. Echinatus plant was collected and echinatus fiber was extracted by the decortication process from the echinatus plants manually, and treated with 5% NaOH for the improvement of bond and interfacial shear strength. And then, the test specimens were manufactured using a mass fraction with 0 , 45 and 90 orientations using technique of hand lay-up. The tensile strength, hardness, and flexural strength were investigated using samples that were prepared according to the ASTM standards. 70% echinatus fiber to 30% polyester composite material with 0 orientation was found as the material with maximum tensile strength of 60.60 MPa, flexural strength of 96.8 MPa, and hardness values of 44.54 HRA. Considering the mechanical properties’ experimental results, echinatus fiber-reinforced composite with 70% fiber at 0 orientation can be good substitutes for synthetic materials.

Asphaltic concrete mixtures are among the most common construction materials for the pavement of roads. As a multi-phase composite mixture with randomly distributed aggregates inside the mastic part, the mechanical properties of such materials can be influenced by different factors. Cracking and induced fracture is among the common degradation and failure modes in these construction mixtures that often takes place in cold regions. In this research, the effects of some influencing parameters including temperature, air void percentage and loading rate are investigated experimentally on the fracture toughness (K_Ic) and work of fracture (W_Ic) of hot mix asphalt material. Edge notched semi-circular bend (SCB) specimen was employed to conduct mode I fracture experiments. The thickness of SCB samples were considered as variable and the HMA mixtures were tested with two SCB thicknesses of 30 and 60 mm. The experimental results showed that both fracture toughness and fracture work are increased by increasing the thickness. However, the effect of thickness on the fracture work was much more significant than the K_Ic value. Also, the fracture and cracking resistance parameters were increased by decreasing the temperature and air void content. Both K_Ic and W_Ic values were also increased by increasing the loading rate in the investigated range of 1 to 8 mm/min. The most influencing parameters on the change of fracture resistance parameters were the temperature, loading rate, air void content and thickness, respectively.

Gas Metal Arc Welding (GMAW) is an extensively implemented arc welding process through the control of input process parameters and the metal from the filler wire. Despite its popular use in various industries, the complex interrelationship between the actual bead and the varying welding parameters makes it challenging to predict appropriate bead geometries via mathematical modeling in a continually changing welding process. In this study, the Regression Learner App was used to compare the performance of supervised Machine Learning (ML) predictive models comprising the Linear Regression (LR), Regression Tree (RT), Support Vector Machine (SVM), Ensembles of Tree (ET), Gaussian Process Regression (GPR), and Artificial Neural Network (ANN) using GMAW dataset. The dataset was scaled and normalized at a range of -1 to +1 to facilitate the visualization of the variation effect. The wire feed speed, voltage, weld velocity, unmelted wire length, and melted wire volume were considered as the input parameters to predict the bead geometry. In addition, the five-fold cross-validation was employed to avoid overfitting and poor generalization. Finally, statistical indicators, namely the Coefficient of Determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were performed on all developed models to evaluate their performance. Thus, the fine tree and ANN models achieved the highest prediction accuracies of 88–91%, signifying their potential use in future research. In short, the present study demonstrated the performance of various supervised ML algorithms for bead geometry prediction, which would assist the selection of appropriately supervised ML algorithms in future studies.

Mini-Hydrostatic Pressure Apparatus (MHSPA), of spatial size 230×210×210 mm³, was developed for individual or limited number of users to promote Covid-19 social distance protocol. A solid hemisphere with an inclined circular segment made from gypsum material (CaSO₂.0.5H₂ O) and coated with filler putty and oil paint, is used in place of the regular quadrants. With the solid attached to a horizontal beam mounted over a pivot, hydrostatic forces due to liquids were measured at different heights of water. The results showed that the assembly could be used to demonstrate variation of hydrostatic pressure on circular surfaces at different heights of liquid with an average difference of 4.38% against average theoretical values. Compared to other results from the use of conventional quadrants in literature, the associated error is minimal, and indicates the possibility of adopting the apparatus in school laboratories for static pressure demonstration.

Science and technological developments in the material field have been currently dedicated to a super strong material potential based on nanotechnology. The super strong material can be created from the mixture of epoxy-resin polymer and SiO₂ (silicon dioxide) nanoparticles. Polymers exist as a nanoparticle adhesive due to nano-SiO₂, which possesses a high amorphic level, resulting in a stronger, more flexible, and stiffer combination than the current super strong material. The advantages of nanocomposite polymer using epoxy- resin and nano-SiO₂ produce strong and light products with an easier production process, utilizing local materials that can improve the following material quality. This study used four material variations, namely P30, P35, P40, and P45, combined with nanoparticles at 0%, 1%, 2%, 3%, and 4%. Based on the results, the highest compressive strength level was found on the PNK 40 EH2:1N1 mixture at 53.18 MPa with 1627 kg/m3 weight density. From the X-Ray Diffraction (XRD) test results, the following mixture had the lowest amorphic phase, while Fourier Transform Infra-Red (FTIR) test results showed that the following mixture absorbed more hydrogen elements, and Scanning Electron Microscope (SEM) observation on the following material mixture had more organized particle distribution.