TY - JOUR
T1 - Investigation of Operational Concerns of Construction Crane Operators
T2 - An Approach Integrating Factor Clustering and Prioritization
AU - Chen, Junyu
AU - Chi, Hung Lin
AU - Du, Qianru
AU - Wu, Peng
N1 - Funding Information:
The authors would like to thank the Research Grants Council, Hong Kong, for the funding support under the Early Career Scheme (PolyU 25221519). Approval was given to the application for ethical review for teaching/research involving human subjects under the project for a period from October 1, 2019, to October 1, 2022.
Publisher Copyright:
© 2022 American Society of Civil Engineers.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - Safe operation of cranes is essential in the construction industry to ensure continuous gains in productivity and control potential hazards to workers on construction sites. In this research, which was based on human-machine-environment (HME) system thinking, a structured crane-related accident database was developed to identify and prioritize the safety concerns of construction crane operators. In order to technically investigate risk factors from accident reports, an approach was proposed in this work integrating factor clustering and prioritization. Accordingly, the research methodology was designed to first collect crane-related accident cases and determine database variables, including accident types, contributing operational factors, and accident consequences. Second, an advanced multiple correspondence analysis (MCA) method coupled with the fuzzy logic was applied to distribute the variables into different clusters and visualize their associations. Third, once the variables were well clustered, failure mode and effect analysis (FMEA) was adopted to investigate the multiscaled structure of clustering and explore the priorities of failure modes based on current legislation, regulations, and industrial codes of practice. In summary, the proposed approach integrating clustering analysis and prioritization analysis contributes to determining essential safety concerns and their potential impacts during crane operation, generating implications for construction crane safety management and eliciting detailed managerial implementation strategies for prevention measures for crane accidents in the construction industry.
AB - Safe operation of cranes is essential in the construction industry to ensure continuous gains in productivity and control potential hazards to workers on construction sites. In this research, which was based on human-machine-environment (HME) system thinking, a structured crane-related accident database was developed to identify and prioritize the safety concerns of construction crane operators. In order to technically investigate risk factors from accident reports, an approach was proposed in this work integrating factor clustering and prioritization. Accordingly, the research methodology was designed to first collect crane-related accident cases and determine database variables, including accident types, contributing operational factors, and accident consequences. Second, an advanced multiple correspondence analysis (MCA) method coupled with the fuzzy logic was applied to distribute the variables into different clusters and visualize their associations. Third, once the variables were well clustered, failure mode and effect analysis (FMEA) was adopted to investigate the multiscaled structure of clustering and explore the priorities of failure modes based on current legislation, regulations, and industrial codes of practice. In summary, the proposed approach integrating clustering analysis and prioritization analysis contributes to determining essential safety concerns and their potential impacts during crane operation, generating implications for construction crane safety management and eliciting detailed managerial implementation strategies for prevention measures for crane accidents in the construction industry.
KW - Accidents
KW - Crane operation
KW - Failure mode and effect analysis (FMEA)
KW - Multiple correspondence analysis (MCA)
KW - Safety concerns
UR - http://www.scopus.com/inward/record.url?scp=85126811438&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)ME.1943-5479.0001044
DO - 10.1061/(ASCE)ME.1943-5479.0001044
M3 - Journal article
AN - SCOPUS:85126811438
SN - 0742-597X
VL - 38
JO - Journal of Management in Engineering
JF - Journal of Management in Engineering
IS - 4
M1 - 04022020
ER -