This paper presents a study on the application of the Markov Model (MM) to determine the transformer population states based on Health Index (HI). In total, 3195 oil samples from 373 transformers ranging in age from 1 to 25 years were analyzed. First, the HI of transformers was computed based on yearly individual oil condition monitoring data that consisted of oil quality, dissolved gases, and furanic compounds. Next, the average HI for each age was computed and the transition probabilities were obtained based on a nonlinear optimization technique. Finally, the future deterioration performance curve of the transformers was determined based on the MM chain algorithm. It was found that the MM can be used to predict the future transformers condition states. The chi-squared goodness-of-fit analysis revealed that the predicted HI for the transformer population obtained based on MM agrees with the average computed HI along the years, and the average error is 3.59%.

Particleboard is not entirely a wood replacement but a particular material with its properties, making it more effective at different times than heavy or solid wood. The world’s biggest concern is environmental problems with formaldehyde as a particulate board binder that can lead to human carcinogenic agents. A cradle-to-gate life cycle assessment (LCA) of particleboard production was performed using openLCA software. The impact assessment was carried out according to the software’s features. This preliminary investigation aims to analyze the chemical composition of particleboard and identify its environmental impact. The Fourier-transform infrared spectroscopy (FTIR) system was used to track the functional group of aliphatic hydrocarbons, inorganic phosphates, and main aliphatic alcohols found in particleboards made in Malaysia. Based on the FTIR results, aliphatic groups were found in numerous aggravates that the spectroscopic infrared was likely to experience. The most important vibrational modes were C–H, at approximately 3000 cm⁻¹, and –CH deformations around 1460 cm⁻¹ and 1380 cm⁻¹. Eight effect groups demonstrated that 100% of the input and all analyses produced the same relative outcome. The life cycle of a product is determined by pollution of the air, water, and soil. Thus, particleboard has a minimal impact on the environment, except for global warming.

This paper presents a fuzzy logic control for a speed control of DC induction motor. The simulation developed by using Fuzzy MATLAB Toolbox and SIMULINK. The fuzzy logic controller is also introduced to the system for keeping the motor speed to be constant when the load varies. Because of the low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. The result of the 3×3 matrix fuzzy control rules and 5×5 matrix fuzzy control rules of the theta and speed will do comparison in this paper. Observation the effects of the fuzzy control rules on the performance of the DC-induction motor-speed control.

This paper presents an investigation of the condition state distribution and performance condition curve of the transformer population under different pre-determined maintenance repair rates based on the Markov Prediction Model (MPM). In total, 3195 oil samples from 373 transformers with an age between one and 25 years were tested. The previously computed Health Index (HI) prediction model of the transformer population based on MPM utilizing the nonlinear minimization technique was employed in this study. The transition probabilities for each of the states were updated based on 10%, 20% and 30% pre-determined maintenance repair rates for the sensitivity study. Next, the HI state distribution and performance condition curve were analyzed based on the Markov chain algorithm. Based on the case study, it is found that the pre-determined maintenance repair rates can affect the HI state distribution and improve the performance condition curve. The 30% pre-determined maintenance repair rate gives the highest impact, especially for the transformer population at state 4 (poor). Overall, the average percentage of change for all HI state distributions is 16.48%. A clear improvement of HI state distribution is found at state 4 (poor) where the highest percentage can be up to 63.25%.

In this paper, a maintenance cost study of transformers based on the Markov Model (MM) utilizing the Health Index (HI) is presented. In total, 120 distribution transformers of oil type (33/11 kV and 30 MVA) are examined. The HI is computed based on condition assessment data. Based on the HI, the transformers are arranged according to its corresponding states, and the transition probabilities are determined based on frequency of a transition approach utilizing the transformer transition states for the year 2013/2014 and 2012/2013. The future states of transformers are determined based on the MM chain algorithm. Finally, the maintenance costs are estimated based on future-state distribution probabilities according to the proposed maintenance policy model. The study shows that the deterioration states of the transformer population for the year 2015 can be predicted by MM based on the transformer transition states for the year 2013/2014 and 2012/2013. Analysis on the relationship between the predicted and actual computed numbers of transformers reveals that all transformer states are still within the 95% prediction interval. There is a 90% probability that the transformer population will reach State 1 after 76 years and 69 years based on the transformer transition states for the year 2013/2014 and 2012/2013. Based on the probability-state distributions, it is found that the total maintenance cost increases gradually from Ringgit Malaysia (RM) 5.94 million to RM 39.09 million based on transformer transition states for the year 2013/2014 and RM 37.56 million for the year 2012/2013 within the 20 years prediction interval, respectively.

Conventional pseudomorphic high electron mobility transistor (pHEMTs) with lattice-matched InGaAs/InAlAs/InP structures exhibit high mobility and saturation velocity and are hence attractive for the fabrication of three-terminal low-noise and high-frequency devices, which operate at room temperature. The major drawbacks of conventional pHEMT devices are the very low breakdown voltage (<2 V) and the very high gate leakage current (∼1 mA/mm), which degrade device and performance especially in monolithic microwave integrated circuits low-noise amplifiers (MMIC LNAs). These drawbacks are caused by the impact ionization in the low band gap, i.e., the In${}_x$Ga${}_{(1-x)}$As (x = 0.53 or 0.7) channel material plus the contribution of other parts of the epitaxial structure. The capability to achieve higher frequency operation is also hindered in conventional InGaAs/InAlAs/InP pHEMTs, due to the standard 1 $\mathsf{\mu }$m flat gate length technology used. A key challenge in solving these issues is the optimization of the InGaAs/InAlAs epilayer structure through band gap engineering. A related challenge is the fabrication of submicron gate length devices using I-line optical lithography, which is more cost-effective, compared to the use of e-Beam lithography. The main goal for this research involves a radical departure from the conventional InGaAs/InAlAs/InP pHEMT structures by designing new and advanced epilayer structures, which significantly improves the performance of conventional low-noise pHEMT devices and at the same time preserves the radio frequency (RF) characteristics. The optimization of the submicron T-gate length process is performed by introducing a new technique to further scale down the bottom gate opening. The outstanding achievements of the new design approach are 90% less gate current leakage and 70% improvement in breakdown voltage, compared with the conventional design. Furthermore, the submicron T-gate length process also shows an increase of about 58% and 33% in f${}_T$ and f${}_{max}$, respectively, compared to the conventional 1 $\mathsf{\mu }$m gate length process. Consequently, the remarkable performance of this new design structure, together with a submicron gate length facilitatesthe implementation of excellent low-noise applications.