TY - JOUR
T1 - Real-time visual detection and correction of automatic screw operations in dimpled light-gauge steel framing with pre-drilled pilot holes
AU - Martinez Rodriguez, Pablo
AU - Ahmad, Rafiq
AU - Al-Hussein, Mohamed
PY - 2019/7/18
Y1 - 2019/7/18
N2 - Modular and panelized construction have been promoted and recognized globally as advanced construction techniques for residential and commercial industries alike. Light-Gauge Steel (LGS) panels have become more popular for commercial buildings and high-rise residential buildings in the last decades. When constructing such panels, for ease of manufacturing and assembling, a common practice in the construction industry is the use of dimples and pre-drilled pilot holes. Current automatic LGS machinery, however, is not designed to operate with such constraints. In this study, a real-time vision-based approach is proposed to enable current machinery to use dimpled studs with pre-drilled pilot holes. An algorithm designed for hole detection inside the dimples on LGS steel studs, based on edge detection and ellipse fitting is proposed. Finally, an adaptive approach is proposed to adjust the screw driving manipulators to ensure that the drilling operation occurs accurately, avoiding any possible damage to the LGS studs or failure of the screwing operation. The proposed algorithm is validated on a real steel assembly and a comparison is provided with other well-known algorithms for ellipse detection to demonstrate the effectiveness of the proposed method. This real-time algorithm gives real-time results for pilot hole detection and screwing location estimation within 3 mm tolerance. When compared with other well-known approaches in the literature, the proposed approach is 59% more accurate than the fastest available algorithm.
AB - Modular and panelized construction have been promoted and recognized globally as advanced construction techniques for residential and commercial industries alike. Light-Gauge Steel (LGS) panels have become more popular for commercial buildings and high-rise residential buildings in the last decades. When constructing such panels, for ease of manufacturing and assembling, a common practice in the construction industry is the use of dimples and pre-drilled pilot holes. Current automatic LGS machinery, however, is not designed to operate with such constraints. In this study, a real-time vision-based approach is proposed to enable current machinery to use dimpled studs with pre-drilled pilot holes. An algorithm designed for hole detection inside the dimples on LGS steel studs, based on edge detection and ellipse fitting is proposed. Finally, an adaptive approach is proposed to adjust the screw driving manipulators to ensure that the drilling operation occurs accurately, avoiding any possible damage to the LGS studs or failure of the screwing operation. The proposed algorithm is validated on a real steel assembly and a comparison is provided with other well-known algorithms for ellipse detection to demonstrate the effectiveness of the proposed method. This real-time algorithm gives real-time results for pilot hole detection and screwing location estimation within 3 mm tolerance. When compared with other well-known approaches in the literature, the proposed approach is 59% more accurate than the fastest available algorithm.
KW - Industry 4.0
KW - Panelized construction
KW - Machine vision
KW - Ellipse detection
KW - Light-gauge steel framing
KW - Smart drilling
U2 - 10.1016/j.promfg.2019.06.204
DO - 10.1016/j.promfg.2019.06.204
M3 - Conference article
VL - 34
SP - 798
EP - 803
JO - Procedia Manufacturing
JF - Procedia Manufacturing
SN - 2351-9789
ER -