Automatic Estimation of Excavator’s Actual Productivity in Trenching and Grading Operations Using Building Information Modeling (BIM)

Abstract

This paper discusses the excavator’s actual productivity in trenching and grading operations. In these tasks, the quantity of material moved is not significant; precision within specified tolerances is the key focus. The manual methods for productivity estimation and progress monitoring of these operations are highly time-consuming, costly, error-prone, and labor-intensive. An automatic method is required to estimate the excavator’s productivity in the operations. Automatic productivity tracking aids in lowering time, fuel, and operational expenses. It also enhances planning, detects project problems, and boosts management and financial performance. The productivity definitions for trenching and grading operations are the trench’s length per unit of time and graded area per unit of time, respectively. In the proposed techniques, a grid-based height map (2.5D map) from working areas is obtained using a Livox Horizon® light detection and ranging (LiDAR) sensor and localization data from the Global Navigation Satellite System (GNSS) and inertial measurement units (IMUs). Additionally, building information modeling (BIM) is utilized to acquire information regarding the target model and required accuracy. The productivity is estimated using the map comparison between the working areas and the desired model. The proposed method is implemented on a medium-rated excavator operated by an experienced operator in a private worksite. The results show that the method can effectively estimate productivity and monitor the development of operations. The obtained information can guide managers to track the productivity of each individual machine and modify planning and time scheduling.