Tower Project Description - Research Paper Example

Task Tower Project Tower project involves the construction of a 340-feet television antenna tower. A building next to the tower will be constructed for house transmission and electrical equipment. The project will consist of the following: the building, the connecting cable between the tower and the building, site preparation, tower and its electrical equipments. Objective To construct television station facilities Scope 1. Construct a 340-feet television antenna tower 2. Construct a building for the transmission and electrical equipment 3. Stock electrical equipment, site preparation, the building and the connecting cable. Monte Carlo Simulation Monte Carlo simulation is a significant demonstrating and analyzing technique. This method manages project risks and poor decisions. Monte Carlo simulation uses calculated data thus allowing program managers to explain and communicate project expectations in a clear way. Monte Carlo technique if combined with training and appropriate education in risk management can lead to effective project execution. In this project of tower construction, the technique (Monte Carlo) analyzes the effects of risk and poor decisions in plan budgets of a project and project performance. For instance, project completion time and required budget are analyzed. In the construction of the tower project, Monte Carlo will be used in two key areas: Area of cost management and to calculate the risk level of the project budget (scheduled date of project completion). The method will explain how it helps the project manager in responding to queries like, how to meet project due date and how long the project will take (McLeish 87). Time Management in Tower Project Monte Carlo will be applied to the project planning to calculate the confidence of project completion. The manager, contract administrative staff, the project engineer and the industrial engineer should have the target of the project completion date (project period). The functions and the duration to each activity should be estimated properly to avoid delays. The project activities and timeframe in this project are well documented. Monte Carlo uses a three-point assessment to streamline the practice of time management. The three-point durations are: best-case durations, worst case and the expert provision (the most-likely duration). The project manager fits these three estimates to a duration possibility distribution. For instance we have normal and beta distribution for the activities. When the simulation is complete, the probability of completing the project on a certain date is communicated by the manager. This probability allows the project manager to set schedules for the project (McLeish 105). Cost Management in Tower Project Monte Carlo simulation is used by the project management to better understand the project budget and approximate the final budget. It involves the assigning of distribution to the project cost rather than assigning a probability distribution to the project activities duration. The approximations are usually formed by a project cost expert. The ultimate product is a probability distribution of the ultimate total project costs. This distribution of the ultimate total costs is used by the project manager to set aside budget reserves. Monte Carlo Simulation can also be used in project management, program and portfolio management. In the Tower project, Monte Carlo Simulation is used in the construction of the project to comprehend certain risks to this project: man-made risks, natural and environmental risks to the project (McLeish 127).This allows for early detection and mitigation of the risks before they occur. Monte Carlo points out uncertainties in this project for understanding and mitigating them. Khamooshi-Cioffi (USM) Model This is a method of presentation accepted risks, impacts and probabilities of the life in a project. Project manager and stakeholders in the Tower project can decide risk acceptance and set aside equivalent possibility funds. This method uses a binomial distribution with a probability equivalent to the risks prospects. The number of risks is determined and ranked according to the expected impacts (PMBOK Guide 57). This is a model of project accounting and scheduling with uncertainty. A focus on the distribution of the likely errors in time and cost calculations and on the consistency of the calculations suggests an approach for developing dependable schedules and budgets with shields for time and cost. This method is executed by analytical approximation hence associated with real projects and provides effective method in planning and scheduling (Deeprose 89). Khamooshi-Cioffi (USM) model has more emphasis on mitigation to lower the possibilities identified. This model states that the project is dynamic and project managers cannot mitigate all the risks alone. The accepted risk level rests on the nature of the project. The contingency risk budget is set aside to deal with the risks if they occur. In the Tower project, the contingency plan is also outlined to deal with the risks. This model also argues that Monte Carlo does not characterize reality of projects perfectly. Khamooshi-Cioffi (USM) model overwhelms shortages by use of a fixed percentage of the total project cost for its contingency fund. In this technique, two steps are preferred: First is to compute the highest number of risk events to expect during the life cycle of a project to within the anticipated confidence level. Second, the anticipated number of risk in combination with suitable sorting can be used to determine total damage of the life cycle of the project (PMBOK Guide 186). Conclusion Monte Carlo is extremely powerful tool when calculating the potential effects of indecision of the project. If there is no consideration of indecision in project budgets and schedules the project targets may exceed (Lock 129). Works Cited Deeprose, Donna. Project Management. Oxford, U.K.: Capstone Pub., 2002. Print. Lock, Dennis. Project Management. 9th ed. Aldershot, England: Gower, 2007. Print. McLeish, Don L.. Monte Carlo simulation and finance. Hoboken, NJ: J. Wiley, 2005. Print. PMBOK Guide (b). A Guide to the Project Management Body of Knowledge (PMBOK guide). 3rd ed. Newtown Square, Pa.: Project Management Institute, 2004. Print. Read More