Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In the existent world of continuous production systems, strong attention has been waged to anonymous risk that probably generates significant apprehension. The forecast for net present value is extremely important for any production plant. The objective of this paper is to implement Monte Carlo simulation technique for perceiving the impact of risk and uncertainty in prediction and forecasting company’s profitability. The production unit under study is interested to make the initial investment by installing an additional spray dryer plant. The expressive values acquied from the Monte Carlo technique established a range of certain results. The expected net present value of the cash flow is $14,605, hence the frequency chart outcomes confirmed that there is the highest level of certainty that the company will achieve its target. To forecast the net present value for the next period, the results confirmed that there are 50.73% chances of achieving the outcomes. Considering the minimum and maximum values at 80% certainty level, it was observed that 80% chances exist that expected outcomes will be between $5,830 and $22,587. The model’s sensitivity results validated that cash inflows had a greater sensitivity level of 21.1% and the cash inflows for the next year as 19.7%. Cumulative frequency distribution confirmed that the probability to achieve a maximum value of $23,520 is 90 % and for the value of $6,244 it is about 10 %. These validations suggested that controlling the expenditures, the company’s outflows can also be controlled definitely.
Wydawca
Czasopismo
Rocznik
Tom
Strony
81--89
Opis fizyczny
Bibliogr. 21 poz., rys., tab., wykr., zdj.
Twórcy
autor
- Sarhad University of Science and Information Technology, Department of Technology, Faculty of Engineering and Technology, Ring Road, Peshawar, Pakistan.25000
Bibliografia
- [1] Choetkiertikul M., Dam H., Tran T., Ghose A., Grundy J., Predicting Delivery Capability in Iterative Software Development, IEEE Transactions on Software Engineering, 44, 6, 551–573, 2018.
- [2] Daradkeh M., Understanding the Factors Affecting the Adoption of Project Portfolio Management Software Through Topic Modeling of Online Software Reviews, International Journal of Information Technology Project Management, 10, 3, 91–114, 2019.
- [3] de Souza M., Ramos D., Pena M., Sobreiro V., Kimura H., Examination of the profitability of technical analysis based on moving average strategies in BRICS, Financial Innovation, 4, 1, 2018.
- [4] Roukny T., Battiston S., Stiglitz J., Interconnectedness as a source of uncertainty in systemic risk, Journal of Financial Stability, 35, 93–106, 2018.
- [5] Bolin J., Finch W., Stenger R., Estimation of Random Coefficient Multilevel Models in the Context of Small Numbers of Level 2 Clusters, Educational and Psychological Measurement, 79, 2, 217–248, 2018.
- [6] Rodgers T., Madison J., Tikare V., Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo, Computational Materials Science, 135, 78–89, 2017.
- [7] Giner B., Merello P., Pardo F., Assessing the impact of operating lease capitalization with dynamic Monte Carlo simulation, JournalofBusinessResearch,101, 836–845, 2019.
- [8] Katinas V., Gecevicius G., Marciukaitis M., An investigation of wind power density distribution at location with low and high wind speeds using statistical model, Applied Energy, 218, 442–451, 2018.
- [9] Hekmatnejad A., Emery X., Vallejos J., Robust estimation of the fracture diameter distribution from the true trace length distribution in the Poissondisc discrete fracture network model,Computersand Geotechnics, 95, 137–146, 2018.
- [10] Malika M., Transformation of fault tree into Bayesian Network Methodology for Fault Diagnosis, Mechanics, 23, 6, 2018.
- [11] Hussain Z., Developing a novel based productivity model by investigating potential bounds of production plant: A case study, International Journal of Production Management and Engineering, 7, 2, 151, 2019.
- [12] Blei D., Kucukelbir A., McAuliffe J., Variational Inference: A Review for Statisticians, Journal of the American Statistical Association, 112, 518, 859–877, 2017
- [13] Nordin N., Johar M., Ibrahim M., Marwah O., Advances in High Temperature Materials for Additive Manufacturing, IOP Conference Series: Materials Science and Engineering, 226, 012176, 2017.
- [14] Sarmento M., Simőes C., The evolving role of trade fairs in business: A systematic literature review and a research agenda, Industrial Marketing Management, 73, 154–170, 2018.
- [15] Graham J., Essex J., Khalid S., PyCGTOOL: Automated Generation of Coarse-Grained Molecular Dynamics Models from Atomistic Trajectories, Journal of Chemical Information and Modeling, 57, 4, 650– 656, 2017.
- [16] Sutjipto A.G.E., Hisyam A., Salim N., Ab Rahim M.H., Legowo A., Ani M.H., Development of inert ceramic for industrial application based on ternary phase diagram of potassiun oxide-aluminum oxide-silicon dioxide, 2019 Advances in Science and Engineering Technology International Conferences (ASET), IEEE, pp. 1–4, 2019.
- [17] Shao J., Qiao Q., Xu Y., Zhai S., Liu H., Operation and Maintenance Costs Allocation Model of Grid Project Based on Performance Value. 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), IEEE, pp. 1809–1812, 2019.
- [18] Huang S., Vignolles M.L., Chen X.D., Le Loir Y., Jan G., Schuck P., Jeantet R., Spray drying of probiotics and other food-grade bacteria: A review, Trends in Food Science & Technology, 63, 1–17, 2017.
- [19] Höglund E., Eliasson L., Oliveira G., Almli V.L., Sozer N., Alminger M., Effect of drying and extrusion processing on physical and nutritional characteristics of bilberry press cake extrudates, LWT, 92, 422–428, 2018.
- [20] Maslinda A.B., Majid M.A., Ridzuan M.J.M., Afendi M., Gibson A.G., Effect of water absorption on the mechanical properties of hybrid interwoven cellulosic-cellulosic fibre reinforced epoxy composites, Composite Structures, 167, 227–237, 2017.
- [21] Müller C., Grunewald M., Spengler T.S., Redundant configuration of automated flow lines based on “Industry 4.0”-technologies, Journal of Business Economics, 87, 7, 877–898, 2017.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-aa41b36e-13af-4e32-a8e4-4eb62cf84fff