Data flow identification to support project automation/integration and productivity.

摘要

The Architecture-Engineering-Construction (AEC) industry is characterized as being highly fragmented. A large number of diverse organizations participate in the planning, design, and construction of each constructed project. Cooperation between project participants is essential in order to achieve the primary objective of a project--to deliver a constructed facility. This cooperation necessitates the transfer of large quantities of project information. Communication is the means for information and data exchange between participants. Availability and timeliness of data needed to perform a given task decreases the potential for project delay(s) and rework thus, increasing productivity. This dissertation primarily investigates the existing communication activities in a construction project environment. The main objective of the dissertation is to identify data that are shared between the various project participants. A data flow analysis technique, known as "Structured Analysis," is used to develop a structured specification of the project communication system. An overview of the Structured Analysis methodology is provided. Data flow diagrams (DFDs), data dictionary (DD), and transform descriptions (TDs) that comprise tools for implementing structured analysis are described with emphasis given to DFDs. The ease of use, simplicity, and flexibility are among the factors that make DFDs an effective tool to document the communication process and depict shared-data in a construction project. The scope of this dissertation is limited to utilizing DFDs to study and document the communication process in a construction project environment.;The resulting set of DFDs as well as the data dictionary are provided. The DFDs will provide participants with a guideline of what data they need to perform a specific task and where to get those data. This research also provides a framework for tracking and documenting the information flow between construction project participants. It also provides a framework for identifying communication problems using DFDs and data-participant matrices. Some communication difficulties among project participants are highlighted. Potential areas of modifications and/or automation are discussed. Additionally, questions related to the shared-data resource that uses automation technology to increase project productivity are raised. Recommendations for future studies are presented.