Despite the proven evidence of ever-growing productivity gains in the manufacturing industry as a result of years of research and investment in advanced technologies, such as robotics, the adoption of robots in construction is still lagging. The existing literature lacks technical frameworks and guidelines that account for the one-of-a-kind nature of construction projects and the myriad of materials and dimensional components in construction activities. This study seeks to address existing technical uncertainty and productivity issues associated with the application of robotics in the assembly-type manufacturing of industrialized construction.
To facilitate the selection of suitable robotic arms for industrialized construction activities, primarily assembly-type manufacturing tasks of offsite production processes, an activity-based ranking system based on axiomatic design principles is proposed. The proposed ranking system utilizes five functional requirements derived from robot characteristics—speed, payload, reach, degrees of freedom and position repeatability—to evaluate robot performance in an industrialized construction task using simulations of a framing station.
Based on design parameters obtained from activity-based simulations, seventy six robotic arms suitable for the framing task were scored and ranked. According to the sensitivity analysis of proposed functional requirements, speed is the key functional requirement that has a notable effect on productivity of a framing station and is thus the determinant in robot performance assessment for framing tasks.
The proposed ranking system is expected to augment automation in construction and serve as a preliminary guideline to help construction professionals in making informed decisions regarding the adoption of robotic arms.
Tehrani, B.M., BuHamdan, S. and Alwisy, A. (2022), "Robotics in industrialized construction: an activity-based ranking system for assembly manufacturing tasks", Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-02-2022-0143
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