Integrated DSS for construction cost management using relational DBMS and fuzzy logic

Abstract

Construction Cost Management encompasses and embraces estimating, scheduling, cost control, resource costing, and interim billing, which are highly interconnected to each other, and share data. Also produces very large quantity of information thus necessitates an integrated information system for effective management. Additionally, data related to progress control exhibits imprecision, vagueness and subjectivity, that demands some sophisticated approach to be introduced in the system for predictions and corrective acting in progress control. Advanced systems using current state-of-the-art could be developed to address the problems. But, construction organizations cannot afford to procure such system due to high cost involvement, therefore expects a cost effective solution. Through an extensive literature review Schedule activity as the denominator, relational DBMS, and Fuzzy logic were identified as suitable method and tools for data integration and vagueness handling. MS AccessTM', MS projectTM, and MATLABTMalso identified as cost effective software for physical design. Then, an integrated Decision Support System (DSS) complementing a common database, a scheduler, and a knowledge base was supposed to solve the problem. Interviews, documentary surveys, and questionnaire surveys were adopted as research techniques. By analyzing the survey data and information, terms and references of the proposed DSS, system architecture, process models, data models and logical models of common database, knowledge representation model for knowledgebase, and dynamic data exchange model for data transfer and conversation were designed. Then MS AccessTM, MS projectTM, and MATLABTM were used to develop the proposed DSS. Finally the developed system was tested for its feasibility in terms of technique and function, and accuracy. Data transfer between database, scheduler, and knowledgebase was very successful. The output produced by the DBMS, and Scheduler had an accuracy of 100 % while Knowledge Based System (KBS) had 80%. It is proved that general software like-MS AccessTM and MS projectTM have potential for advanced integrated system development with higher technical, functional, and cost feasibilities using relational database concept. They can also be integrated with KBS for heuristic decision making. Key Words: Cost Management ,Integration, Relational DBMS, Fuzzy Logic, Information System