Studying the Physics of Design Flow Incorporating Early Information Using a Simulation Model

Abstract

Project completion time is of great importance in today¿s competitive market. In the design process, it is common to overlap design activities incorporating early information from precedent activities to shorten the project duration instead of having to wait for the confirmed parameter values to arrive after full analysis. However, the estimated preliminary information might be different from that obtained after the full analysis. Consequently, redesign may be needed in downstream activities to correct this discrepancy. Total amount of induced redesign may adversely impact loss in productivity and overall design completion. Moreover, when utilizing early information, the impact on redesign is characterized by various design factors such as number of estimable activities, time to release early information, degree of accuracy of early information and redesign duration for each activity.

The objective of this study is to achieve a better understanding of the physics of design flow incorporating early information. The concept of utilizing early information and redesign has been modeled using the simulation technique. The simulation model explicitly considers various design factors that characterize the notion of early information and redesign. Other key issues of design processes such as handling coupled activities, managing external changes, and overlapping design and construction activities have been examined incorporating the notion of early information and redesign.

The design processes have been modeled in generalized way so that the simulation network can be automatically generated for any design project based on the dependency relationships of design activities. The framework of the generalized Auto Generated Model (AGeM) uses the concepts of Activity Specific Nodes and Links to model the internal processes of design activities, and Connecting Nodes and Links to model the information flow between activities. Design attributes that make up the properties of the network are integrated with different arrays that provide significant flexibility in handling diverse types of workflow in the design process. The templates of the AGeM are found to be very apt in modeling the design process for any specific project just by changing the input matrices and form the basis for evaluating the physics of design flow.

The study characterizes the project performance metrics of design completion and loss in productivity through sensitivity studies of the parameters of the simulation model. As can be found, different factors have different impacts on project performance metrics. Nevertheless, under the right design factors, the use of early information can be exploited without compromising project performance. As can be found for the case study, early information sharing from 34 activities (out of 83) can shorten the design completion from 432 to 303 days (30% reduction) with a loss in productivity of 5% (80 man-days). The reduction could be as high as up to 56% with only 10% loss in productivity. The sensitivity studies would provide valuable insight that project managers can take into account when utilizing early information in design. Finally, the study proposes a framework of systematic overlapping strategy using genetic algorithm (GA) method. Through Overlapping Strategy Matrix (OSM), the GA model searches for an optimal combination of design activities to be overlapped eliminating unnecessary redesign so that the loss in productivity would be minimized. As depicted in the illustrative case project, optimization can save the loss in productivity as high as 80% without significant delay or even no delay in design completion time. Such optimization would further encourage project managers to overlap design activities incorporating early information.