Download Research about Project Controlling Decision Support System on Freeway Construction Engineering

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
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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
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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].
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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
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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
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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.
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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
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[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].
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The author can be contacted from e-mail : [email protected]
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