Demand for eco-friendly materials increases each year due to their excellent properties, which has proved to contribute to developing a sustainable environment. One of the promising raw materials in producing Glass is rice husk, a waste product from paddy harvesting, containing about 90% of silica. Rice husks are usually burnt in an open area and contribute to severe air pollution problems. In this research, Soda-Lime-Silica Rice Husk Ash (SLRHA) glass which is a new combination of soda-lime silicate (SLS) glass and rice husk ash (RHA), was developed for building glass and window application. The hardness properties of the developed SLS-RHA glass system are presented in this paper. These glasses were investigated to determine the effect of RHA addition on the physical properties of SLS glass. The experimental works using RSM have successfully identified the significant factors and optimized the responses. Based on the Rockwell hardness test, the outcomes demonstrated that the glass sample contained 29.84% weight SLS and 0.06% weight RHA. The result indicated that crack propagation was increased with the increasing addition of RHA, which causes an increase in cracks and voids due to the creation of more debonding.

Large-scale wind turbines mostly use Continuously Variable Transmission (CVT) as the transmission system, which is highly efficient. However, it comes with high complexity and cost too. In contrast, the small-scale wind turbines that are available in the market offer a one-speed gearing system only where no gear ratios are varied, resulting in low efficiency of harvesting energy and leading to gears failure. In this research, an unsupervised machine-learning algorithm is proposed to address the energy efficiency of the automatic transmission system in vertical axis wind turbines (VAWT), to increase its efficiency in harvesting energy. The aim is to find the best adjustment for VAWT while the automatic transmission system is taken into account. For this purpose, the system is simulated and tested under various gear ratios conditions while a centrifugal clutch is applied to automatic gear shifting. The outcomes indicated that the automatic transmission system could successfully adjust the spinning in line with the wind speed. As a result, the obtained level of harvested voltage and power by VAWT with the automatic transmission system are improved significantly. Consequently, it is concluded that automatic VAWTs, equipped with the machine-learning capability can readjust themselves with the wind speed more efficiently.

In this research a new electronic based mechanism for vehicle suspension system is designd. The aims are to improve passengers’ safety and comfort. The proposed system is developed for proactive rapid reaction of suspension system which can readjust the height of chassis while confronting with wrong conditions of driving such as unflatted road, rainy or snowy road profile. The results show that the proposed mechanism can successfully increase the stability of the car by readjusting the height of the the chassis and center of the gravity of vehicle while turning.

In this paper, a new method is proposed for scheduling dynamic cellular manufacturing systems (D-CMS) in the presence of uncertain product demands. The aim of this method is to control the process of trading off between in-house manufacturing and outsourcing while product demands are uncertain and can be varied from period to period. To solve the proposed problem, a hybrid Tabu Search and Simulated Annealing are developed to overcome hardness of the proposed model and then results are compared with a Branch and Bound and Simulated Annealing algorithms. A Taguchi method (L_27 orthogonal optimization) is used to estimate parameters of the proposed method in order to solve experiments derived from literature. An in-depth analysis is conducted on the results in consideration of various factors. For evaluating the system imbalance in dynamic market demands, a new measuring index is developed. Our findings indicate that the uncertain condition of market demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. The results showed that the proposed hybrid method can provide solutions with better quality.