The determination of economic control charts and the determination of specification limits with minimum cost are two different research topics. In this study, we first combine the design of economic control charts and the determination of specification limits to maximize the expected profit per unit time for the smaller the better quality variable following the gamma distribution. Because of the asymmetric distribution, we design the EWMA control chart with asymmetric control limits. We simultaneously determine the economic EWMA control chart and upper specification limit with maximum expected profit per unit time. Then, extend the approach to determine the economic variable sampling interval EWMA control chart and upper specification limit with maximum expected profit per unit time. In all our numerical examples of the two profit models, the optimum expected profit per unit time under inspection is higher than that of no inspection. The detection ability of the EWMA chart with an appropriate weight is always better than the X-bar probability chart. The detection ability of the VSI EWMA chart is also superior to that of the fixed sampling interval EWMA chart. Sensitivity analyses are provided to determine the significant parameters for the optimal design parameters and the optimal expected profit per unit time.

Thesis (PhD (Electrical Engineering))--Cape Peninsula University of Technology, 2019 / Energy systems based on fossil fuel have demonstrated their abilities to permit economic development. However, with the fast exhaustion of this energy source, the expansion of the world energy demand and concerns over global warming, new energy systems dependent on renewable and other sustainable energy are gaining more interests. It is a fact that future development in the energy sector is founded on the utilisation of renewable and sustainable energy sources. These energy sources can enable the world to meet the double targets of diminishing greenhouse gas emissions and ensuring reliable and cost-effective energy supply. Fuel cells are one of the advanced clean energy technologies to substitute power generation systems based on fossil fuel. They are viewed as reliable and efficient technologies to operate either tied or non-tied to the grid to power applications ranging from domestic, commercial to industrial. Multiple fuel cell stacks can be associated in series and parallel to obtain a fuel cell system with high power up to megawatts. The connection of megawatts fuel cell systems to a utility grid requires that the power condition unit serving as the interface between the fuel cell plant and the grid operates accordingly. Different power conditioning unit topologies can be adopted, this study considers a multilevel inverter. Multilevel inverters are getting more popularity and attractiveness as compared to conventional inverters in high voltage and high-power applications. These inverters are suitable for harmonic mitigation in high-power applications whereby switching devices are unable to function at high switching frequencies. For a given application, the choice of appropriate multilevel topology and its control scheme are not defined and depend on various engineering compromises, however, the most developed multilevel inverter topologies include the Diode Clamped, the Flying Capacitor and the Cascade Full Bridge inverters. On the other hand, a multilevel inverter can be either a three or a five, or a nine level, however, this research focuses on the three-level diode clamped inverters. The aim of this thesis is to model and control a three-level diode clamped inverter for the grid connection of a megawatt fuel cell stack. Besides the grid, the system consists of a 1.54 MW operating at 1400 V DC proton exchange membrane fuel cell stack, a 1.26 MW three-level diode clamped inverter with a nominal voltage of 600 V and an LCL filter which is designed to reduce harmonics and meet the standards such as IEEE 519 and IEC 61000-3-6. The inverter control scheme comprises voltage and current regulators to provide a good power factor and satisfy synchronisation requirements with the grid. The frequency and phase are synchronised with those of the grid through a phase locked loop. The modelling and simulation are performed using Matlab/Simulink. The results show good performance of the developed system with a low total harmonic distortion of about 0.35% for the voltage and 0.19% for the current.

The CUSUM control charts have been widely used in detecting small process shifts since it was first introduced by Page (1954). And recent studies have shown that adaptive charts can improve the efficiency and performance of traditional Shewhart charts. To monitor the process mean and variance in a single chart, the loss function is used as a measure statistic in this article. The loss function can measure the process quality loss while the process mean and/or variance has shifted. This study combines the three features: adaption, CUSUM and the loss function, and proposes the optimal VSSI, VSI, and FP CUSUM Loss chart. The performance of the proposed charts is measured by using Average Time to Signal (ATS) and Average Number of Observations to Signal (ANOS). The ATS and ANOS calculations are based on Markov chain approach. The performance comparisons between the proposed charts and some existing charts, such as X-bar+S^2 charts and CUSUM X-bar+S^2 charts, are illustrated by numerical analyses and some examples. From the results of the numerical analyses, it shows that the optimal VSSI CUSUM Loss chart has better performance than the optimal VSI CUSUM Loss chart, optimal FP CUSUM Loss chart, CUSUM X-bar+S^2 charts and X-bar+S^2 charts. Furthermore, using a single chart to monitor a process is not only easier but more efficient than using two charts simultaneously. Hence, the adaptive CUSUM Loss charts are recommended in real process. / The CUSUM control charts have been widely used in detecting small process shifts since it was first introduced by Page (1954). And recent studies have shown that adaptive charts can improve the efficiency and performance of traditional Shewhart charts. To monitor the process mean and variance in a single chart, the loss function is used as a measure statistic in this article. The loss function can measure the process quality loss while the process mean and/or variance has shifted. This study combines the three features: adaption, CUSUM and the loss function, and proposes the optimal VSSI, VSI, and FP CUSUM Loss chart. The performance of the proposed charts is measured by using Average Time to Signal (ATS) and Average Number of Observations to Signal (ANOS). The ATS and ANOS calculations are based on Markov chain approach. The performance comparisons between the proposed charts and some existing charts, such as X-bar+S^2 charts and CUSUM X-bar+S^2 charts, are illustrated by numerical analyses and some examples. From the results of the numerical analyses, it shows that the optimal VSSI CUSUM Loss chart has better performance than the optimal VSI CUSUM Loss chart, optimal FP CUSUM Loss chart, CUSUM X-bar+S^2 charts and X-bar+S^2 charts. Furthermore, using a single chart to monitor a process is not only easier but more efficient than using two charts simultaneously. Hence, the adaptive CUSUM Loss charts are recommended in real process.