A fuzzy multi-criteria decision-making approach for power generation problem analysis

The abundance of different energy sources such as coal, natural gas, and crude oil are in the Africa region, yet one of the lowest electric energy per capita consumption. Different factors have been attributed to this abysmal energy failure in the literature, leading to her slow economic and industrial advancement. These factors include poor maintenance of power generation infrastructure and lack of policy continuity, among others. The purpose of this article is to prioritize these power generation problems for proper budgetary allocation by managers of electric power. The fuzzy VIKOR technique is presented for the evaluation and ranking of these power generation problems. The analysis showed that poor maintenance is the most critical challenge of bedeviling power generation in Nigeria. The Fuzzy VIKOR produces the same result as the classical VIKOR used previously in resolving the problem. The proposed technique addresses the challenge of uncertainty and subjectivity by applying linguistic variables in the decisionmaking process, which the classical VIKOR is incapable of handling

Methodology of Using an Integrated Averaging Technique and MAUT Method for Failure Mode and Effects Analysis

The conventional Failure Mode and Effects Analysis (FMEA) which is popularly used for prioritizing risk of failure modes of industrial products has limitations such as the inability of the technique to utilize imprecise ratings from experts. These limitations impact negatively on its effectiveness in prioritizing risk. This paper presents a technique that integrates Averaging technique with Multi Attribute Utility Theory method for Failure Mode and Effects Analysis. The objective is to develop an alternative tool that avoids the limitations of the conventional FMEA such that risk of failure mode is prioritized more efficiently. The suitability of the proposed approach is demonstrated with a case study of the rotor blades of an aircraft turbine. The results show that the proposed approach is more flexible and effective for practical application than the conventional FMEA

Selection of Optimal Process Parameters for a Mild Steel Weld using Technique for Order of Preference by Similarity to Ideal Solution

Welding is a major operation in many industries such as production and manufacturing, oil and gas, amongst others. Obtaining an optimal weld with the required properties; tensile strength and hardness is of high importance. The work used the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select the optimal process parameters for a mild steel weld by employing five (5) standard steps in ranking 30 experimental steps. The result obtained gave an optimal tensile strength and hardness of 496.5MPa and 190.2 respectively for a combined input parameters of 170Amp, 20volts, 22l/min, and 3.2mm. These data is very important as it will provide the necessary information for evaluating the durability and lifespan of the weld product which are factors considered in assessing its quality

An Integrated Statistical Variance And VIKOR Methods For Prioritising Power Generation Problems In Nigeria

The bedrock of industrialization of any nation is the supply of adequate and efficient electricity to power both homes and industries. However, electricity supply in Nigeria is grossly inadequate and inefficient, which has resulted in many local industries becoming moribund. The inadequate power supply is mainly due to power generation problems. Some of the problems identified include, among others lack of energy mix, militant activities and corruption. The purpose of this paper is to develop a tool for prioritizing these problems for power generation. Managers able to identify the more critical ones and allocate more resource in addressing them easily.  Hence, this paper presents a tool based on the integration of statistical variance and Vlsekriterijumska Optimizacija Ikompromisno Resenje (VIKOR) and compromise solution methods for prioritization of the various problems confronting power generation in Nigeria. The statistical variance method is used in the decision criteria weights determination while the VIKOR method is used in the ranking of power generation problems. The proposed technique was demonstrated with data collected from experts. The result of the analysis showed that the most critical power generation challenge is the poor maintenance of power generation infrastructure.   

Prevalence and Impact of Socio-Economic/Enviromental Factors on Soil-Transmitted Helminth Infection in Children Attending Clinic in a Tertiary Hospital in Benin City, Nigeria

Children are important risk group for soil-transmitted helminths (STH). Hence, this study was undertaken to determine the impact of mothers’ educational status, the method of fecal disposal and source of water supply on the prevalence of STH infection. Four hundred and ninety six children, aged 1-15 years, who presented at the Children Out-patient Clinic of the University of Benin Teaching Hospital (UBTH) were screened for STH in their stool, using methods of wet preparation and Stoll's technique for detection and counting of helminthes eggs. A semi-structured, researcher administered questionnaire was used to collect information on socio demographics of mother/care giver, history of de-worming, source of water supply, and method of fecal disposal. The overall prevalence of STH infections was 9.5%, corresponding to 6.9% of Ascaris lumbricoides, 2.4% of hookworm and 0.2% of Trichuris trichiuria. Infection with hookworm was of highest intensity. Age group 6 - 10 had the highest prevalence of STH. Mother/caregivers level of education, method of faecal disposal and source of water supply, all significantly influenced the prevalence of STH infection. There is need for a coordinated, multi-sectarian and multidisciplinary strategy that integrates periodic deworming, health education and environmental sanitation for effective control.Keywords: Soil-transmitted helminths; Prevalence; Children; Benin City

Application of Waspas In Enhancing Reliability Centered Maintenance For Ship System Maintenance

The key for achieving safe and reliable ship system operation throughout a vessel’s life cycle is the continuous use of an effective maintenance methodology for the machinery systems. A typical maintenance methodology consists of three major elements which include; risk assessment, maintenance strategy selection and maintenance scheduling. The degree of ship system safety and reliability greatly depend on the successful execution of these elements. One approach for the implementation of these elements is Reliability Centred Maintenance (RCM). However, the various tools used within the RCM approach all have one limitation or another which reduces the effectiveness of the method. This paper presents the Weighted Aggregated Product Assessment (WASPAS), a Multi-Criteria Decision Making (MCDM) tool used to enhance the RCM method in order to improve its effectiveness in marine maintenance system applications. Although the typical maintenance methodology consists of three components, this paper focuses only on two of these, namely; risk assessment and maintenance strategy selection. With respect to risk assessment, WASPAS has been combined with Failure Mode and Effects Analysis (FMEA) along with Standard Deviation (SD).  The maintenance strategy selection task has also been executed using a combination of WASPAS and SD. For both components, WASPAS is applied in the ranking of alternatives whilst SD has been used in the weighting of decision criteria. To illustrate the effectiveness of the proposed enhanced RCM methodology, a case study of the central cooling system of a marine diesel engine is presented

Emergence and spread of two SARS-CoV-2 variants of interest in Nigeria.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the SARS-CoV-2 B.1.1.318 and B.1.525 (Eta) variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave in Nigeria emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Data from this study show how regional connectivity of Nigeria drove the spread of these variants of interest to surrounding countries and those connected by air-traffic. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission, as bidirectional transmission within and between African nations are grossly underestimated as seen in our import risk index estimates

Improving risk analysis capability of FMEA using evaluation based on distance from average solution (EDAS): a case study of turbocharger system

Failure Mode and Effect Analysis (FMEA) is a key risk management tool used in detecting and eradicating potential failure for the purpose of improving the reliability and safety of a system. However, the traditional FMEA in spite of its popularity has inadequacies that have hindered the effectiveness of the tool in analyzing risk of failure modes. Due to the shortcomings of the technique, different improved versions have been suggested in the literature in order for risk to be analysed more effectively but majority of these versions are computationally challenging. In this paper, a simple approach is in troduced for improving the risk analysis capability of the FMEA. The approach utilizes Evaluation based on Distance from Average Solution (EDAS) as an alternative to RPN of FMEA in analyzing risk of failure. A case study of the turbocharger system of a diesel engine is applied to demonstrate the usefulness of the method. The result obtained from the EDAS method were compared with approaches in the literature previously used to address risk analysis of a turbo charger. The result of the analysis indicated that the EDAS method is a feasible alternative technique for risk analysis

A Multi-Criteria Decision Making Approach for Analysing Prospective University Students Course Selection Decision Problem in Nigeria

Prospective university students at the end of the senior secondary school education find it challenging to choose the most suitable course to be studied at the university level. The difficulty may be attributed to numerous alternatives courses available for students to choose from while considering diverse conflicting decision attributes. This paper presents a VIKOR methodology for ease of course selection for prospective university students. The suitability of the proposed technique is illustrated with an example of a student having a challenge in selecting the best course from among medicine, engineering, and law while considering four decision criteria as the basis for evaluating the performances of each alternative course. The proposed technique was validated by comparing it with an approach used in the literature in solving a related course selection decision problem. The proposed methodology although easier in terms of computation yet produces the same result as the method in the literature. The VIKOR approach is therefore a feasible alternative for dealing with the problem of course selection for prospective university students