Journal of Applied Research on Industrial Engineering
Volume:7 Issue: 2, Spring 2020

There have been several major global outbreaks during the past decades, with the latest being the worst. The COVID-19 pandemic has infected hundreds of thousands and killed thousands in the world affecting most countries in around the globe. Outbreak response management efficiency can have a major impact on the outcome of the pandemic. Therefore, in this paper, the performance of most seriously affected countries regarding contagion control and medical treatment of COVID-19 is evaluated using data envelopment analysis. The efficiency values are calculated based on the conditions of the countries and the number of confirmed cases in the first step in order to create a basis for analysis according to the contagion control. In the second step the performance evaluation is done considering the total number of confirmed cases, the death cases, and the recovered cases to evaluate the efficiency of medical treatment in the countries. The countries are also classified into four groups using area chart, and for each group, some suggestions and analyses are presented. The results show the performance of the countries regarding the contagion control and medical treatment.

The aim of this study was to analyze the performance of Omotosho Phase II gas turbine power plant for improved performance. To obtain the required output performance of the gas turbine power plant, operation data from years of 2013 to 2016 was collected from Omotosho Phase II gas turbine power plant in Ondo State, Nigeria. ASPEN HYSYS 2016 version was used to create two models, with one representing Omotosho Phase II gas turbine power plant with fogging unit incorporated while the other represented the power plant without fogging unit. The data was fed as input variables into the models in ASPEN HYSYS 2016 version which simulated the power plant process Specific Fuel Consumption (SFC) obtained from the power plant simulation when fogging is not incorporated was 0.199 kg/kwh, whereas, SFC of the plant with fogging was 0.179 kg/kwh. Thermal efficiency of 43.93% was obtained from the result of the simulated power plant with fogging system, whereas, thermal efficiency of 39.39% obtained from the result of the simulated power plant without fogging system. Net power of 131 MW was obtained from the simulation of the power plant with fogging system while net power of 117.46 MW was obtained when the plant operates without fogging system installed. For the compressor work, 82 MW/h was obtained from the simulation of the power plant with fogging system, whereas, 112.11 MW/h was obtained from the simulation of the power plant without fogging system. Furthermore, turbine work of 213 MW/h were obtained from the simulation of the power plant operating with fogging system while turbine work of 229.57 MW/h was obtained from the power plant without fogging system. This indicates that the incorporation of fogging system into Omotosho Phase II gas turbine power plant is economically viable in terms of fuel consumption, efficiency, power requirement, and GHG emissions compared to operation of the power plant without fogging system.

Microfinance Institutions (MFIs) contribute significantly to the development of a country and many of these institutions are found in most developing countries including Ghana. However, many challenges have been alleged to stifle the efforts of microfinance companies in their attempt to make their all-important contribution to the development of nations. This study explored the effect of operational flaws on the performance of microfinance institutions in Ghana. The results discovered flaws and challenges associated with the operations of the MFIs in many areas including corporate governance, credit risk management, credit administration, regulatory challenges, and training programs. The study also revealed that such flaws and challenges do harm the overall performance of the MFIs. Based on the findings, it is recommended that MFIs put in place a well-composed and resourceful credit committee to perform the duty of credit risk management in the institutions. The institutions could also reduce their interest rates to encourage their clients to apply for more loans. Lastly, it is recommended that the MFIs take all necessary steps to ensure that they reduce the flaws and challenges they face to mitigate the negative impact of such deficiencies on their performance.

In this work, Greenland Wolf Optimization (GW) algorithm has been applied for real power loss reduction. Natural actions of the Greenland wolf have been mimicked to design the GW algorithm. Greenland wolf found in North West of green land and typical size of the pack is three. Arctic hares, musk oxen, and lemmings are main prey for green land wolf and they migrate with respect to availability of food resources. Through flag vector, position, and velocity updating property Exploration, Exploitation capability of the algorithm has been enhanced. Proposed GW algorithm has been tested in standard IEEE 118 bus test system and results show the best performance of the GW algorithm in reducing the real power loss efficiently.

Bed production has an important market in the furniture sector. In spite of the fact that sponge is generally preferred as filler in the production process of beds, increasing prices in recent years and the preference of new materials with the development of alternative filling materials have increased. Recently it is seen other than sponge, the granule, wadding, and STW are also used as filling material in bed production. From the management point of view, the choice of filler is an important decision problem that depends on the situation of the business and many objective and subjective criteria must be taken into consideration. It is appropriate to examine such a problem with the Analytical Hierarchy Method (AHP) and the ELECTRE method, which have the ability to make quantitative evaluations and synthesize factor weights from subjective judgments. The criteria for selection of the filler material and the extent to which the criterion will affect the evaluation are important decision points. The opinions of experts in bed production were consulted to determine the criteria to be used in the evaluation. The obtained results show that four basic criteria must be taken into consideration in the selection of filler material. In this study, AHP was used for determining the criteria weights, and ELECTRE methods were used for the selection of the best filling material. The results showed that wadding is the optimum filler material for bed production.

Demand forecasting is a vital task for firms to manage the optimum quantity of raw material and products. The demand forecasting task can be formulated as a time series forecasting problem by measuring historical demand data at equal intervals. Demand time series usually exhibit a seasonal pattern. The principle idea of this study is to propose a method that predicts the demand for every different season using a specialized forecaster. In this study, we test our proposal using the Long Short-Term Memory (LSTM) which is a deep learning technique for time series forecasting. Specifically, the proposed method instead of learning an LSTM model using the whole demand data builds a specialized LSTM model corresponding to each season. The proposed method is evaluated using different topologies of the LSTM model. The results of experiments indicated that the proposed method outperforms the regular method considering the performance measures. The proposed method can be used in other domains for demand forecasting.

Wind energy is abundant, inexhaustible, affordable, environmentally preferable, and equally sustainable. More researches are emerging in the analysis of wind energy in Nigeria and each have proven that great potential exist for wind power generation in Nigeria but sufficient results is yet to be achieved in terms of application. The present research is intended to apply the technology of wind energy for pumping of water in rural Nigeria. To achieve this, a savonius vertical axis wind turbine is developed. To ensure, an optimum functioning system was developed and design consideration and conceptual design were drawn. The best conceptual design was selected for development using decision matrix. The system was evaluated for performance and UT363 Anemometer was used to measure the wind speed. Results obtained indicate a swept area of 3.41 m2, power of wind of 31.46 watts, blade tip speed and rotational speed wind of 7.38 rpm and 5.05 rpm were required for effective wind turbine operation. Besides, an average wind speed of 3.49 m/sec was required to pump an average 47.77 litres of water at an average time of 3.08 minutes