A thorough investigation has been carried out on the Al-12Si-1Mg-1Cu-1Ni automotive alloy considering different properties, specially mechanical properties associated with true stress and true strain with Zr addition of trace amount. A commercially available piston is melted to produce the alloy, and trace amount of Zr is added to make another. The base alloy along with the Zr added alloy had been applied to homogenization, solution treatment, quenching, and ageing in order to get the age-hardening response. The alloys have been heat-treated at 25 ºC, 200 ºC, and 300 ºC, respectively, for four hours for attaining the under, peak and over-aged states, respectively. During ageing, Al2Cu and Mg2Si phases are formed in the aluminium matrix leading to peak-aged strength, which is reduced at over-aged state because of coarsening of precipitation and recrystallizing, shown by the tensile and hardness properties. When Zr is added to the alloy, Al3Zr phases appear while casting and heat-treatment, resisting the drop of strength at over-aged state. It is visible in the stress-strain diagram that at over-aged conditions, the alloy with trace Zr shows improved strength and ductility. In the micrographs of Zr added alloy, finer distributed grains are visible through the grain refinement of Zr, which also prevents recrystallization at over-aged conditions. The homogeneity of the grains as a result of the Zr addition's microstructural change was further confirmed by fractography. It is clear that adding Zr to such alloys does not greatly increase their strength, but it does restrict the declining of strength by preventing the production of thermally stable Al3Zr precipitates, which coarsens the resisting behavior of various intermetallics in the thermally damaged alloy.

Bacterial cellulose (BC) is a widespread, low-cost biopolymer that has generally been produced from plants and biomass waste. A method for improving the range of applications for bacterial cellulose is adding graphene material. It has an outstanding feature that can increase the performance of nanocomposite materials. The research aims to observe the effect of graphene on the surface morphology, crystallinity, chemical bonding, and tensile strength of BC/CuO nanocomposite. For this study's synthesis, BC was synthesized by fermenting pineapple peel extract for 10 to 14 days. The produced BC was crushed, homogenized with a nano homogenizer machine, and filtered. Filtered BC, CuO, and graphene were added to obtain a solution, and the mixture was first stirred magnetically, followed by an ultrasonic homogenizer, and finally dried using a freeze-dry method to make a porous nanocomposite. According to SEM analysis, the addition of CuO and graphene can fill porosity nanocomposite. By XRD analysis, the addition of graphene reduces the crystallinity of BC/CuO. The FTIR data showed that adding graphene reduces hydrogen bonding and makes some Cu-O-C bonding. The tensile test has demonstrated that the tensile strength of BC-based nanocomposite with graphene reinforcement tends to decrease.

3D printing is a process of making three-dimensional solid objects from a digital file process created by laying down successive layers of material until the object is created. Many filaments can be used in 3D printing, one of which is PETG (PolyEthylene Terephthalate Glycol). PETG is a modification of PET (PolyEthylene Terephthalate) with added glycol at a molecular level to offer different chemical properties that provide significant chemical resistance, durability, and excellent formability for manufacturing. This study aims to find the most optimal parameter of surface roughness of PETG with different parameters of nozzle temperature, infill geometry, layer height and fan speed. Taguchi L16 (44), with four levels for each parameter, was used to determine the effect of each parameter. Each experiment was repeated five times to minimize the occurrence of errors. Based on the result, the effect of each parameter is nozzle temperature at 4.9%, infill geometry at 5.9%, layer height at 82.3%, and fan speed at 4.6%. Layer height has the highest effect on surface roughness, and other parameters have a low effect, under 7%. Research shows that the optimal combination of parameters is a nozzle temperature of 220 °C, infill geometry zig-zag, layer height of 0.12 mm, and a fan speed of 80 %.

Towards industry 4.0, monitoring the degradation of machine tools’ components becomes a key feature so that smooth productivity is achieved. To preserve the functionality and performance of the machine tools, proper maintenance activities must be planned and carried out. V-belt is important component in machine tools that transmits power from the electric motor spindle in order to machine to work and cut desired material properly. The purpose of this research is to develop a predictive maintenance system for v-belt milling machine Krisbow 31N2F using machine learning. The machine learning algorithm models using multiple and simple linear regression algorithm was developed in an open-source program. The test results show that the machine learning model has a high accuracy value in both the training data and the testing data. The multiple linear regression model has MSE value of 5.8830x10-6 and MAE value of 0.002. The Simple linear regression model has an MSE value of 0.0004x10-6 and MAE value of 0.162. The results shows that the use of the linear regression algorithm as a support for determining the prediction of RUL v-belt milling machine model 31N2F (BS) is successfully carried out.

Loads could affect the body gait in various ways. Backpacks, sling bags, suitcases, and even trolleys could hugely affect human gait without us realizing it. The effects of these loads have been scientifically researched in biomechanics and sports science for the past few years. For instance, the comparison of walking with and without a backpack could easily reveal significant differences in body segments, which could be utilized for therapy and medicine development. The aim of this research is to determine the differences of the spatiotemporal kinematic parameters between a conventional human gait and a backpack-loaded gait. Some parameters to be highlighted are stride lengths, stride duration, joint angles, linear and angular segment positions, velocities, and accelerations. The method used for marker data acquisition is based on the 2-dimensional Direct Linear Transformation. The results demonstrate that the backpack increases stride lengths and reduces stride duration, contrast to the expected where backpacks would reduce stride lengths. It was observed that the angle between the bag and the body posterior affects the abdomen relative angle, which directly translates to stride lengths as well. During unloaded walking, increases in pelvic rotation contribute to increases in stride length with increasing walking speed. However, in loaded walking, the back angle is also a factor in determining kinematic parameters.

Microalgae Spirulina sp which has been cultivated by the Brackishwater Aquaculture Development Center, Situbondo Indonesia were tested for their potential energy performance using proximate analyzer, SEM-EDX, and thermogravimetry. The proximate analyzer showed volatile matter (VM), fixed carbon (FC), moisture, ash content (AC), total sulfur of microalgae Spirulina sp 68.15, 12.57, 11.22, 8.06, and 0.67 (wt%, ar), respectively, and the gross calorific value (GCV) is 4971 kcal/kg (dry basis). SEM-EDX test showed the morphology and chemical content of Spirulina sp. The content of microalgae Spirulina sp is dominated by carbon (C) and oxygen (O), then followed by chlorine (Cl), sodium (Na), potassium (K), sulfur (S), magnesium (Mg), and phosphorus (P). Thermogravimetry pyrolysis test of microalgae Spirulina sp resulted thermogravimetry (TG) analysis and derivative thermogravimetry (DTG) analysis curve, which is divided into three different steps. The moisture of microalga Spirulina sp was vaporized at the first step, started at 27°C, and finished at 173°C with a decomposed mass of about 13.81% of the total initial mass. The second step began at the end of vaporize moisture at about 173°C and ended at around 618 °C. The gasification process occurred in volatile matter content and resulted mass loss of about 57.9% of Spirulina sp total mass. The last step showed the process of gasification of residual substances, started at the end of the volatile matter step, 618°C, and stopped at 995°C with a decomposed mass of 24.6% from total mass.

The mechanized ability to specify the way surface type is a piece of key enlightenment for autonomous transportation machine navigation like wheelchairs and smart cars. In the present work, the extracted features from the object are getting based on structure and surface evidence using Gray Level Co-occurrence Matrix (GLCM). Furthermore, K-Nearest Neighbor (K-NN) Classifier was built to classify the road surface image into three classes, asphalt, gravel, and pavement. A comparison of KNN and Naïve Bayes (NB) was used in present study. We have constructed a road image dataset of 450 samples from real-world road images in the asphalt, gravel, and pavement. Experiment result that the classification accuracy using the K-NN classifier is 78%, which is better as compared to Naïve Bayes classifier which has a classification accuracy of 72%. The paving class has the smallest accuracy in both classifier methods. The two classifiers have nearly the same computing time, 3.459 seconds for the KNN Classifier and 3.464 seconds for the Naive Bayes Classifier.

Effect of the elements Fe, Ni, and Cr on the surface quality under machining of hyper-eutectic aluminium-based Al-Si automotive alloys has been carried out as the elements improve the properties of this alloy. Machining is done on a horizontal type milling machine using a high-speed steel slab milling cutter in dry condition. Only the cutting speed varies throughout the experiment, while the machining feed and depth of cut remain fixed. The experimental results show that the addition of these alloying elements increases the roughness and hardness specially due to formation of Fe-rich intermetallic . However, the needle-like has been refined with the addition of Cr, as seen by the microstructure. The SEM fractography shows a huge cleavage of the brittle phase, which initiates the crack propagation for Fe added alloys. The downward force causes compressive stress exerted in down-milling operation, so the results depict higher hardness and better surface finish. Besides, shorter chips are formed in down-milling than up-milling process, which rather causes the brittleness of the alloys. When the cutting speed is raised, the surface quality deteriorates due to high temperature, while the hardness improves initially due to formation of precipitates then decreases due to coarsening of precipitates.

Many studies were conducted to maintain the environment by reducing the waste, especially pineapple peel waste. This study aims to explore the effect of various pressure of the homogenization process on bacterial cellulose membrane surface morphology and structure produced using extract of pineapple peel waste. The methods include the preparation of pellicle samples from the product of the fermentation process of Acetobacter xylinum using a medium from the extract of pineapple peel waste. Bacterial cellulose pellicles were crushed using a blender. Mashed bacterial cellulose pellicle then homogenized in High-Pressure Homogenizer with pressure variation of 0 bar, 150 bar, 300 bar, 450 bar, dan 600 bar then cast into a mold. The bacterial cellulose solutions were dried in an oven at 60°C for 8 hours. The dried bacterial cellulose membrane was analyzed using XRD for the structure and SEM analysis for the morphology. The results indicate that the crystalline properties of BCM were shifted after being treated by various pressure processing in a High-Pressure Homogenizer. It was found that the High-Pressure Homogenizer with higher pressure reduced the peak intensity, decreased crystalline index from 87% to 70%, and decreased the degree of crystalline from 88% to 77% without changing the cellulose structure. The higher pressure of the homogenization process causes the porosity of the membrane to be decreased.

Experimental research has been conducted on the effect of ignition timings on the characteristics and performance of gasohol engines such as power, torque, specific fuel consumption, and thermal efficiency. The fuel used in this research is pure gasoline and a mixture of 50% bioethanol (BE50). The results show that the ignition timing that gives the maximum effect occurs at the top and bottom dead points of 9 degrees for gasoline and 12 degrees for BE50 fuel. Furthermore, the maximum power is obtained at 6,500 rpm, and at an ignition time of 12 degrees BTDC the maximum power generated is 4.63 hp, while for an ignition time of 9 degrees BTDC the power generated is 3.38 hp which occurs at 6500 rpm. These results indicate that there is an increase in power of 6.4%. Moreover, the results also show that for optimal gasoline conditions, the amount of energy consumed at an engine speed of 7000 rpm is around 15705.78 kcal/hour, and for BE-50 it is around 12582.03 kcal/hour, where there is a reduction of about 25.44 %. However, in general, it can be seen that during optimal ignition, there is a saving in fuel consumption in the gasoline-BE50 mixture, while at the same time producing a fairly large thermal efficiency. These results indicate that BE50 has the potential to be used as an alternative fuel in small gasoline engines.