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Research about Project Controlling Decision Support System on Freeway Construction Engineering LU Yi, YANG Jian Project Management Institute, Chang sha University of Science & Technology, Hu Nan,Chang Sha 410076 Abstract The model of project controlling could increase the managing lever and controlling capacity of freeway construction engineering on owners, which could be carried out by project controlling decision support system. The paper advances the functional objective and designs the structure and key technology of project controlling decision support system. They are the theory basic and technical support for establishing the project controlling decision support system. Keywords Freeway Project Controlling Decision Support System Data Warehouse Data Mining ; ; ; ; 1 Introduction Freeway construction engineering has large construction scales, high technical demands, a long construction period and many participating units. So the project management is complex. And the project managing lever and controlling capacity of owners of is limited under the present model of freeway construction engineering. Meanwhile, the information produced by freeway construction engineering is large-scale and substantial, which couldn’t be offered timely by traditional and lagging artifices that include information gathering, processing, transmission and storage. So scientific and effective decision made by project owners is difficult. Project controlling combined with project management theory and controlling theory is a new organizational model which could provide strategic, macro and general advisory services for the highest policy-makers in owners, whose core is to guide project information flow and control material flow by DSS [1]. Decision support system could make decision more efficient by collecting and analyzing the information on freeway construction engineering effectively and rapidly. This paper is intended to research project controlling decision support system (PCDSS) on freeway construction engineering. 2 Functional objectives of PCDSS on freeway construction engineering Based on the management theory of project controlling on freeway construction engineering, the functional objective of PCDSS designed is shown in Figure 1: Progress Decision Support Owners Designers Sugared Construction side Pavement Supervisors Bridge Superiors Tunnel Model Base Data Warehouse Project Data Mining and Knowledge Discovery Methods Base Quality Decision Support Investment Decision Support Contract Decision Support The third parties Change Decision Support Figure1 The functional objective and implement procedure of PCDSS on freeway construction engineering 1219 ① The specific functional objective of each subsidiary module in Figure1 is as follows: The subsidiary module of progress decision support could establish a scientific network progress plan for freeway, provide network maps, bar charts, statistical maps and resource tables in project controlling, discover and point out the critical path, monitor the executive progress of construction, discover and solve the problem timely. So it could offer support for the plan and controlling of decision on freeway construction engineering [2]. The subsidiary module of quality decision support could master the quality of project timely based on the information offered by supervisors, analysis the hidden dangers, advance pre-control measures and put forth proposals for serious accidents. The subsidiary module of investment decision support could gather project information, such as direct costs, indirect costs, and so on. And it could supervise the process of implementation, analyze every factor and advance the controlling measures of investment. The subsidiary module of contract decision support could produce the structure of project implementation contract, manage all kinds of contracts in the form of tracking, check the implement process of each party, clean up and pigeonhole contracts and help owners deal with difficult matters, such as contract claim and contract fraud. So it could decrease the number of supervisory and increase the efficient of contract examining and approving. The subsidiary module of change decision support could offer change management for makers by the changeable services, including the application, information checking, accounting management, estimation and price management. In which, the most important is the changeable estimation and price management. DSS could help makers complete these better by using scientism estimation model [3]. ② ③ ④ ⑤ 3 Construction Design The whole structure of PCDSS on freeway construction engineering is shown in figure2, which is made up of several important subsidiary modules, such as database, model base, method base and knowledge base. Makers Project controlling units Man-machine interactive interface Method Base Knowledge Base Model Base Data mining, OLAP Data Warehouse Data extraction, purification and conversion Engineering Database Financial database External databases Figure 2 The whole structure of PCDSS 3.1 Database Database is the foundation of PCDSS on freeway construction engineering, which contains a lot of relevant information, including the designed parameters, the project progress of implementation, the quality, the investment data and the owning data of workers and resources. It could be classified into four classes according to its structure: roadbed engineering database, road surface database, bridge construction database and tunnel project database; and it could be classified into four classes also according to the different process: design database, implementation database, checking database and operating database. In the course of establishing database, we must ensure the total construction is flexible, expandable and maintainable, and the data is efficient, integrate and secure. It is necessary to 1220 satisfy the demands of users, which include checking data, showing data, science calculation and accurate precision. 3.2 Model Base Model base could store a large number of models on freeway construction engineering, including network planning model, Gray forecast model, fuzzy comprehensive evaluation model, cost building model, linear programming model, and so on. Their content is all shown in Tab 1. Model Name Network plan model Gray Forecast Model Fuzzy Comprehensive Evaluation Model Costs & Process Optimization model Linear Programming Model Table 1 Basic content of each model on PCDSS Basic content The main parameters of network plan model are the earliest starting time, the earliest closing time, the whole time, the free time differences the total time difference, the relevant time difference, the independent time difference, the last ending time and the last beginning time, and so on. By using the parameters of every process, the real starting time and ending time could be calculated and the process could be anticipated. So it could help us manage process. Gray forecast model is a gray differential prediction model based on litter and incomplete information, which could make fuzzy descriptions of the long-term development. Gray theory regard the system as an ordered whole which owned a whole function, though the phenomenon is unclear and the data is complex in the system. We could find out the rules by generating the gray data. And the state of investment, process and risk could be anticipated by gray model in the course of freeway construction engineering management. Fuzzy comprehensive evaluation model is an effective multi-factor decision method that could evaluate objects infected by lots of factors from all sides, whose results are expressed by a fuzzy set that is neither entirely positive nor negative. The model could be used in project risk evaluation, project completing evaluation and operating evaluation in freeway construction engineering management. The whole costs could be separated into direct costs and indirect costs in the construction phase. The direct costs changed as the process include material costs, labor costs and machinery costs, which are nonlinear. And the indirect costs changed as the process could be separated into construction originating costs and operating management costs. So it is necessary to establish a process optimization model to find out the best point of integration between the cost and time limit. Material cutting, task allocation and transportation planning in the course of implementation on freeway construction are all suitable to be solved by linear programming model or transportation model. Therefore, it is necessary to establish linear programming model and transportation model to make more science decisions. 3.3 Method Base Method base that could be extended and connected with other database is the combination of procedures. The controlling system of method base could convert the corresponding application-specific requirements of the system into procedures. Methods commonly used in the reservoir are shown in figure 3. 3.4 Knowledge Base Only when the users have the abundant knowledge of mathematic and computer network, the decision model could be chosen and combined best. The system establishes a repository to offer the services of expert consultation and it could help and guide the users to establish the process plan and make best decision for all preparative scheme based on the management knowledge of freeway construction engineering. Meanwhile, the experts in the system owned considerable wealth engineering skill, management knowledge and computer knowledge could make up for lack of knowledge base. Then the function of decision support system could be bang into play fully [4]. 4 The key technology in system 4.1 Real-time Technology in System The efficiency and controlling effective is determined by the accurate data sources and real-time character of data. In order to gather the accurate information timely and minimize the delays, the project implement information must be inputted timely by each parties and the min time interval must be set up 1221 to ensure the latest data is being in the system[5]. All kinds of algorithms on primary function Interpolation method Basic mathematical methods Fitting method Extrapolation method Smoothing method Regression Analysis Variance Analysis Statistical methods Bivariate Correlation Analysis Factor Analysis Methods Base Diagnosis Analysis Discriminate Analysis Forecast Method Solution Analysis Causality Analysis Planned method Time Series Analysis Vetting Law Optimization method Matrix Algorithm Figure 3 Methods commonly used in the base 4.2 Data Warehouse Technology Data Warehouse is the data source of DSS, whose structure of data storage, data inquiry and data reading is the important factor to the efficient of DSS. So data extraction, data storage, data management and multi-dimensional analysis are the core technology in data warehouse. (1) The entrance of data warehouse is the data extraction. Due to the data warehouse is independent, it could complete the data reading by data extraction from the joining transaction system, external data sources and off-line data storage medium. Data extraction is relevant to several key technologies, such as joining, cloning, increasing, changing, scheduling, monitoring, and so on. The date in data Warehouse needn’t being consistent with joining transaction system timely, so the data could be collected regularly. But the implementation time, mutual orders and the success or failure of it after several steps is important for the efficient of data warehouse. (2) The data stored on data warehouse is much more than the transitional traction. The relational database could store and manage a large number of data through the development of nearly 30 years, which is better than other data management system in storing and managing data. Many relational databases have the technology of data cutting at present, which could store great many data in many physical storage devices, which have strengthen the ability of managing data. The relational database can be used to manage hundreds of data with the unites named TB even GB. (3) The form of visiting data in data warehouse is different from the traditional one, which is the analysis model based on users named joining analysis, not only the simple inquiring tables and records. 1222 And it regards data as cube with multi-dimension. The inquiry implemented by users is carried out through the following steps: firstly impose proper conditions on several dimensions (prism), secondly cut and divide the cube, then input the results that are in the form of matrixes or vectors into procedures to complete data statistic or design them into figures or tables [6]. 4.3 Data Mining Techniques Data Mining (DM) is related to several technologies, such as the database, artificial intelligence, decision tree, statistical analysis, and so on. Most of these technologies have been integrated into large data warehouse and OLAP system. The technology common used is shown in table 2. Technical categories Artificial Neural Networks Decision Trees Genetic Algorithms Case-based Reasoning Association Rule Rough Set Table 2 Common used techniques in data mining Technical Notes The non-linear model based on neural network could be classified into four: feed-forward neural networks, feedback neural networks, stochastic neural networks and self-organizing neural networks. Decision trees based on samples is an analysis and concluding method of attributes by using information theory, in which, the attributes are named codes, the value of attribute is named branch and the code of leaves is named the structure of trees. Genetic algorithm is an optimization algorithm copying the course of natural selection and biological evolution, which is consisted of three basic processes: choice, crossover and mutation. Case-base reasoning could make few alterations to suit the current problem in models through comparing and modifying the most relevant examples of current problems. So it is an anticipation based on past experience. Association rule is a descript language about the laws of data in the same task. Rough set is a classification algorithm. 4.4 Integrated technology of comprehensive components If we want to integrate the independent model, data and knowledge, we must solve the questions of interface in various components. The key problem is the comprehensive language. There is not any language could satisfy the demands. But there are two ways used to solve the problem commonly, one is to design by oneself, another is to choose a powerful computer language, then add same functional language [7]. 5 Conclusions Research on theory of project controlling has a long development history at overseas, which has been applied in every walk of life and acquired a lot of experiments. But in our country the research on project controlling on freeway construction engineering is lagging. Considering the needs of freeway construction engineering, the manager and maker should think about it serious in the view of integrating the ideal, model and technological innovation. It is necessary to advance and establish the PCDSS on freeway construction engineering and make it be consistent with the project management system. References [1] Jia Guang she. Project controlling - new management model of construction [M]. Shanghai: Journal of Tongji University Press, 2003:5~79(in Chinese) [2] Lin Jie,Guo Yao huang. Construction Optimization Decision Support System [J]. Journal of Southwest Traffic University, 1999:120~125(in Chinese) [3] Blanning R W. Model management systems: an overview. Decision Support Systems, 1993, 9 (1):9 18. [4] Chen Wen wei. Development and introduction of DSS [M]. Beijing: Journal of Tsinghua University, 2000 (in Chinese) [5] Zhang Ying, Hu Minghua, Peng Ying. Air traffic management decision support system of multiple capacity [J]. Journal of traffic transportation, 2004:44~48(in Chinese) [6] DimitriTheodoratos, Timos Sellis. Designing Data warehouses [J].Data and Knowledge Engineering,1999. 31(3):279~301. [7] Ding Shi Zhao. Information introduction on construction project [M]. Beijing: Journal of China Building Industry, 2005:21~45(in Chinese) The author can be contacted from e-mail : [email protected] ~ 1223