Build E\P\C Layered Detection Model Based Four-value Analysis

Earned value analysis method has been widely used in the practice of project management abroad. The concept originated in the 1800s and was first used in the U.S. Navy Polaris program in 1960s. In 1967, the U.S Department of Defense specified the (C/SCSC) (Cost/Schedule Control Systems Criteria) and applied earned value analysis as a kind of effective tool to manage cost, schedule and technical performance in industry and government projects. Subsequently, many countries such as Australia, Canada, Sweden and the United Kingdom, combined with the guidelines issued by the U.S Department of Defense, respectively drawn up their own government and industry standards which has formed a relatively complete theoretical system with strong feasibility and operability. Earned value evaluation technology is currently seen as a mainstream method for evaluation of cost and schedule of projects and its effect can be used to promote a comprehensive assessment of the overall project.This paper, considering about the characteristics of EPC petrochemical engineering project and its existing circumstance on project management, introduces how to adjust the traditional triple-value analysis which aims at its characteristics of high-tech, high investment and high risk and how to apply "four-value analysis" to evaluate and to predict total profits of the contractor; how to build a practical E\P\C layered detection model to eliminate the focused complexity of the whole contracting project. Combine the "four-value analysis" with the layered detection to build an appropriate model to control the company profit and to monitor risk. Then, this model can be customized on the information platform to advance an analysis of test run used a company’s actual project. As a part of the project management system, it can not only solve the problem in accordance with the existing circumstance but also provide a reference for companies in the same field through comparison with the change of control indicators and the effect of risk prediction before and after use.