Investment Prediction Using Simulation
نویسنده
چکیده
A business case is a proposal for an investment initiative to satisfy business and functional requirements. The business case provides the foundation for tactical decision making and technology risk management. It helps to clarify how the organization will use its resources in the best way by providing justification for investment of resources. This paper describes how simulation was used for business case benefits and return on investment for the procurement of 8 production machines. With investment costs of about 4.7 million dollars and annual operating costs of about 1.3 million, we needed to determine if the machines would provide enough cost savings and cost avoidance. We constructed a model of the existing factory environment consisting of 8 machines and subsequently, we conducted average day simulations with light and heavy volumes to facilitate planning decisions required to be documented and substantiated in the business case. Keywords—Investment cost, business case, return on investment, simulation.
منابع مشابه
Cost Estimation Method of Power Engineering Overhead Line Based on ARIMA— RBF Neural Network Model
Factors in the unit investment forecast of overhead line engineering are various and complex, it is very difficult to get the satisfied forecasting effect using traditional econometric models. In view of this characteristic, this thesis puts forward a kind of combination forecast model, using the ARIMA model and RBF neural network model to seek for linear and nonlinear change rule of historical...
متن کاملارائه مدل تعیین میزان مخارج سرمایهای در شرکتهای پذیرفته شده در سازمان بورس اوراق بهادار تهرانبا استفادهاز اطلاعات حسابداری
Financing strategy in corporations is one of the most important subject matters among accounting and finance scholars. Investment in companies to increase profitability is one of the important purposes of financing activities. Different methods for execution of financing activities include: Internal finance, external finance and combination of these two. The problem is that whether there is...
متن کاملPrediction of Nitrogen Injection Performance in Conventional Reservoirs Using the Correlation Developed by the Incorporation of Experimental Design Techniques and Reservoir Simulation
Enhanced oil recovery using nitrogen injection is a commonly applied method for pressure maintenance in conventional reservoirs. Numerical simulations can be practiced for the prediction of a reservoir performance in the course of injection process; however, a detailed simulation might take up enormous computer processing time. In such cases, a simple statistical model may be a good approach to...
متن کامل The Quantification of Uncertainties in Production Prediction Using Integrated Statistical and Neural Network Approaches: An Iranian Gas Field Case Study
Uncertainty in production prediction has been subject to numerous investigations. Geological and reservoir engineering data comprise a huge number of data entries to the simulation models. Thus, uncertainty of these data can largely affect the reliability of the simulation model. Due to these reasons, it is worthy to present the desired quantity with a probability distribution instead of a sing...
متن کاملPrediction of Entrance Length for Magnetohydrodynamics Channels Flow using Numerical simulation and Artificial Neural Network
This paper focuses on using the numerical finite volume method (FVM) and artificial neural network (ANN) in order to propose a correlation for computing the entrance length of laminar magnetohydrodynamics (MHD) channels flow. In the first step, for different values of the Reynolds (Re) and Hartmann (Ha) numbers (600<ReL increases.
متن کامل