Jessica Veronica, Lidia Intan Febriani, Citra Nurhashiva, R. Ragadhita, A. Nandiyanto, T. Kurniawan
{"title":"Practical Computation in the Techno-Economic Analysis of the Production of Magnesium Oxide Nanoparticles using Sol-gel Method","authors":"Jessica Veronica, Lidia Intan Febriani, Citra Nurhashiva, R. Ragadhita, A. Nandiyanto, T. Kurniawan","doi":"10.34010/injiiscom.v2i2.5431","DOIUrl":null,"url":null,"abstract":"The purpose of this study was to determine the feasibility of a project for the manufacture of magnesium oxide nanoparticles using the sol-gel method by evaluating both technically and economically. Evaluation from the technical side is determined by stoichiometric calculations and evaluation of the initial factory design, while the evaluation from the economic side is determined by several parameters to determine the benefits of the project to be established (Gross Profit Margin, Internal Rate Return, Break-Even Point, Payback Period, and Cumulative Net Present Values). Some of these economic evaluation parameters were analyzed to inform the production potential of magnesium oxide nanoparticles, such as determining the level of profitability of a project (Gross Profit Margin), predicting the length of time required for an investment to return the initial capital expenditure (Payback Period), predicting the condition of a production project in the form of a production function in years (Cumulative Net PresentValue), etc. The results of the technical analysis show that this project can produce 1,425 kg of magnesium oxide nanoparticles per day and the total cost of the equipment purchased is 45,243 USD. Payback Period analysis shows that the investment will be profitable after more than three years. To ensure project feasibility, the project is estimated from ideal to worst-case conditions in production, including salary, sales, raw materials, utilities, as well as external conditions such as taxes","PeriodicalId":196635,"journal":{"name":"International Journal of Informatics, Information System and Computer Engineering (INJIISCOM)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Informatics, Information System and Computer Engineering (INJIISCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34010/injiiscom.v2i2.5431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The purpose of this study was to determine the feasibility of a project for the manufacture of magnesium oxide nanoparticles using the sol-gel method by evaluating both technically and economically. Evaluation from the technical side is determined by stoichiometric calculations and evaluation of the initial factory design, while the evaluation from the economic side is determined by several parameters to determine the benefits of the project to be established (Gross Profit Margin, Internal Rate Return, Break-Even Point, Payback Period, and Cumulative Net Present Values). Some of these economic evaluation parameters were analyzed to inform the production potential of magnesium oxide nanoparticles, such as determining the level of profitability of a project (Gross Profit Margin), predicting the length of time required for an investment to return the initial capital expenditure (Payback Period), predicting the condition of a production project in the form of a production function in years (Cumulative Net PresentValue), etc. The results of the technical analysis show that this project can produce 1,425 kg of magnesium oxide nanoparticles per day and the total cost of the equipment purchased is 45,243 USD. Payback Period analysis shows that the investment will be profitable after more than three years. To ensure project feasibility, the project is estimated from ideal to worst-case conditions in production, including salary, sales, raw materials, utilities, as well as external conditions such as taxes