TY - GEN
T1 - A Novel Productivity Measure for Steel Fabrication Fitting Process
AU - Marshall, L.
AU - Suliman, A.
AU - Lei, Z.
PY - 2022/5/18
Y1 - 2022/5/18
N2 - The fitting station is an important element of the industrial steel fabrication process. The fitting process happens towards the end of the fabrication and has the potential to cause upstream backlogs if productivity is not maintained. Due to the variations of each different assembly, it is difficult to quantify the productivity at the station. To help define an accurate productivity measure at fitting stations, a time study was proposed to collect pertinent data of different fitting processes and define a metric for the productivity. After observing and breaking the process into sequential phases, a productivity dataset was collected, and a correlation analysis was performed between different input variables and time measures. It was determined that the current metric on trial of ‘parts fit per man hour’ was not an accurate representation of the productivity at the fitting station. This metric fails to capture the significant differences between the process when the workers are either bolting, tack welding, or coping the different parts of an assembly. Hence, to account for these differences, it was proposed in this research that the process should be broken down. According to a correlation analysis, it was concluded that the fitting productivity should include the number of bolts, tacked parts, and coping cuts. The corresponding new metric improved the productivity quantification and time estimation by 42% over the trial metric. With these metrics specified, the productivity will be able to be equally determined for each assembly entering the station and will minimize productivity data variations.
AB - The fitting station is an important element of the industrial steel fabrication process. The fitting process happens towards the end of the fabrication and has the potential to cause upstream backlogs if productivity is not maintained. Due to the variations of each different assembly, it is difficult to quantify the productivity at the station. To help define an accurate productivity measure at fitting stations, a time study was proposed to collect pertinent data of different fitting processes and define a metric for the productivity. After observing and breaking the process into sequential phases, a productivity dataset was collected, and a correlation analysis was performed between different input variables and time measures. It was determined that the current metric on trial of ‘parts fit per man hour’ was not an accurate representation of the productivity at the fitting station. This metric fails to capture the significant differences between the process when the workers are either bolting, tack welding, or coping the different parts of an assembly. Hence, to account for these differences, it was proposed in this research that the process should be broken down. According to a correlation analysis, it was concluded that the fitting productivity should include the number of bolts, tacked parts, and coping cuts. The corresponding new metric improved the productivity quantification and time estimation by 42% over the trial metric. With these metrics specified, the productivity will be able to be equally determined for each assembly entering the station and will minimize productivity data variations.
UR - http://www.scopus.com/inward/record.url?scp=85131118533&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-0507-0_5
DO - 10.1007/978-981-19-0507-0_5
M3 - Conference contribution
AN - SCOPUS:85131118533
SN - 9789811905063
SN - 9789811905094
VL - 2
T3 - Lecture Notes in Civil Engineering
SP - 43
EP - 55
BT - Proceedings of the Canadian Society of Civil Engineering Annual Conference 2021
A2 - Walbridge, Scott
A2 - Nik-Bakht, Mazdak
A2 - Ng, Kelvin Tsun Wai
A2 - Shome, Manas
A2 - Alam, M. Shahria
A2 - el Damatty, Ashraf
A2 - Lovegrove, Gordon
PB - Springer
CY - Singapore
T2 - Canadian Society of Civil Engineering Annual Conference, CSCE 2021
Y2 - 26 May 2021 through 29 May 2021
ER -