کیفیت مدل مدیریت ریسک برای پروژه ساخت و ساز راه آهن
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|68434||2014||9 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Procedia Engineering, Volume 84, 2014, Pages 195–203
Information technology has significant potential to enhance the engineering quality of the risk management of railway construction projects. The Shanghai Railway Bureau has promoted a risk management method based on the “A Figure and Four Tables” method (AFFTM) to assess the engineering quality; however, this method still suffers from several problems in railway construction project management. In this paper, we have combined the concepts and processes of the AFFTM with those of information technology and presented the implementation scheme of a new risk management system—the railway construction project quality risk management information system (RCPQRMIS)—that can be used to design and develop workable information tools for quality risk management. The paper analyzes the data standards of RCPQRMIS and creates a model for dynamically tracking the quality risk (“quality risk dynamic tracking” model) for providing pre-warning information on quality risk (“quality risk pre-warning” model) and for automatically generating publicity parameters for quality risk (“automatically generated quality risk publicity figure” model). The proposed system enables the visualization of the quality associated with the risk control, dynamic tracking, automatic pre-warning, and closed-loop management of railway construction projects. In addition, this paper presents the functional modules of the RCPQRMIS and its practical applications. Our application results show that the system successfully realized unified management of risk source information and multi-level sharing. In this manner, by using our system, we were able to significantly improve real-time tracking and pre-warning of the risk state, automatic generation of quality risk publicity figures, efficiency, and risk management levels.