A Study on Data Collection and Control Model for Project –the Public Construction Management Information System

碩士 === 國立臺灣大學 === 土木工程學研究所 === 100 === The authorities of public construction should control with cautious the schedule performance and budge of public construction tenders. However, very few staff in charge from the authority emphasis on overall controlling of corrects information collection. In vi...

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Bibliographic Details
Main Authors: Sou-Jung Chou, 周壽榮
Other Authors: serng , Hui-Ping
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/k9bebf
Description
Summary:碩士 === 國立臺灣大學 === 土木工程學研究所 === 100 === The authorities of public construction should control with cautious the schedule performance and budge of public construction tenders. However, very few staff in charge from the authority emphasis on overall controlling of corrects information collection. In view of this, it is necessary to build a public construction management information system, which with simple and fast system function, to control the performance status, and provide anomaly monitoring mechanism. As far as the study method is concerned, this research, through the process of building system, studies a method of performance management and anomaly monitoring for public construction as reference to government administration. The study uses the technologies of relational database (RDB) to analyze the status of related information during the process of construction, selects the items that affect performance, then analyzes data by online analytical processing to provide hierarchical analytical of performance status, therefore establish data collecting model for construction management and confirm the relation among different items. In order to verify the evaluated items that affect the construction, the system adopts timing control to monitor the anomaly when the data of construction performing is filling, provides data filler the real-time information of data incomplete, and rules and regulations for seeking solution as a precautious. In addition, the system also employs management mechanism to integrate the models of handling anomaly, project performance evaluation, monitoring, and knowledge management, thereby to build a back-up system for supporting data management, observation, assessment and provide management analysis, further to enable governments of different levels to monitor the status of construction in a variable environment in order to enhance the performance of implementation. In recent years, the related issues of construction quality have attracted public attention gradually. By construction quality auditing and supervision, the construction authority can understand the quality and status of implementation for early detecting defect and correction as soon as possible to avoid missing the timing for improvement. Thus, quality audit is more crucial to construction quality; likewise, it is important to collect the related information completely after each quality audit, and know well of the progress and quality of high-risk indicators then to provide a framework to analyze data of progress and quality. The said analytic framework uses the data collected by system to analyze the record of performance status and quality audit to obtain quality risk model of different kinds of construction. Meanwhile, the correlation between these risk models and anomaly of construction will also available for establishing more integrated prediction models. The information provided by the system can be used as supplementary information to the project manager in government agencies, and then provides the authority with warning or appropriate management decision, in order to achieve the effectiveness of early prevention and early management. The results of this study are summarized as follows: 1. to establish a complete data collection method for administrative system in the phase of public construction. 2. to provide government agencies of all levels a construction management and control model. 3. to provide schedule management by using a variety of tables and anomaly analysis functions. 4. to collect factor information of significant impact on the progress to provide follow-up research and analysis. 5. to build a model for collecting data of the performance evaluation of quantitative analysis.