Massively parallelized GA based optimal path planning for single and dual crane lifting in complex industrial environments

Abstract

Heavy lifting is an important task in petrochemical and pharmaceutical plants. It is frequently conducted during the time of plant construction, maintenance shutdown, and new equipment installation. Mobile cranes are lifting machines widely used in a variety of industries. The two primary issues that industries concern are safety and productivity. Accidents may happen in work sites of mobile cranes due to various reasons such as lack of operation knowledge, lack of safety awareness, lack of information about the environment, inadequate guidance, and wrong calculations in lifting. These factors may also influence the productivity by wasting time, energy and resources in unnecessary operations or stoppages. Computer-aided Lift Planning (CALP) for mobile cranes is an effective and efficient tool highly desired by industries. This research aims to develop a new CALP system for automatic lift planning in complex industrial environments such as petrochemical and pharmaceutical plants, and construction sites. The research focuses on the lifting path planning problems for single and cooperative dual mobile cranes in these complex environments. The lifting The author would like to express her sincere thanks and appreciation to her supervisor, Dr. and Associate professor Cai Yiyu (MAE), and co-supervisor, Dr. and Associate professor Zheng Jianmin (SCE) for their invaluable guidance, support and suggestions. Their knowledge, suggestions, and discussions help me to become a capable researcher. Their encouragement also helps me to overcome many difficulties encountered in my research. The author also wants to thank the colleagues in the CAE Visualization Room, for their generous help. I want to thank Dr. Indhumathi Chandrasekaran for providing the crane simulation environment and technical suggestions. I want to thank for Mr. Huang Lihui's help on converting PDMS data and the help of Dr. Ma Yuewen, Dr. Wu Xiaoqun, Dr. Zhang Yuzhe and Mr. Chen Yong on scanning and processing data in point cloud form. I also want to thank the FYP student Zhang Tianci for developing the physical model crane. My gratitude also goes to Dr. Li Qing and Dr. Chen Wenyu for their friendship and support. I am very grateful to the members of our research team in NTU. It is a pleasure to collaborate with my project team mates, particularly Dr. Indhumathi Chandrasekaran and Mr. Huang Lihui.