Data Analytics of Production Cycle Time for Offsite Construction Projects

Abstract

Offsite construction has been widely used in the construction industry. The process improves productivity that leads to shortened project schedule and lower budget. Over the decades, offsite construction industry has continuously evolved with the aspects of management and technology. However, offsite construction companies still have various challenges such as accurately obtaining productivity metrics, which helps in production planning. These challenges result from lack of understanding the process itself because of high variation of wall panel design specifications along with high variability of cycle time at each work station. To solve the problem, productivity data needs to be collected in context to offsite construction. In this paper, a time study was conducted in one of Alberta’s-based offsite construction factory. From the collected data and product design specifications, multiple linear regression models were developed to represent the actual work station time. The comparison between actual collected duration and modeled duration for assembly station demonstrate its accuracy that ranges from 80 -99%. In the near future, findings will be used for simulation to forecast factory production and optimize the utilization of the resources.