Technician assignment in multi-shift maintenance schedules in an offshore wind farm

被引:0
|
作者
Tusar, Md Imran Hasan [1 ,2 ]
Sarker, Bhaba R. [2 ]
机构
[1] Bowling Green State Univ, Sch Engn, 264 Technol Bldg, Bowling Green, OH 43403 USA
[2] Louisiana State Univ, Dept Mech & Ind Engn, Baton Rouge, LA 70803 USA
关键词
Offshore wind farms; Technician Assignment Problem (TAP); Mathematical optimization model; Workforce scheduling; Maintenance strategies;
D O I
10.1016/j.ref.2024.100616
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Offshore wind farms are becoming more and more important to sustainable energy strategies, yet their maintenance presents unique logistical challenges. The focus of this research is the Technician Assignment Problem (TAP) which involves a complicated and fluctuating scheduling problem. The key objective is to determine the most effective assignment of technicians to maintenance tasks to maximize operational efficiency and ensure reliable service. This study introduces a mathematical optimization model that processes numerous variables-technician availability, skill sets, and temporal constraints-to minimize unmet maintenance needs and ensure equitable workload distribution. The model is based on assumptions derived from actual operational conditions and human resource practices, guaranteeing that its results are not only theoretically valid but also practically feasible. TAP adheres to labor regulations, employs human resource capabilities, and aims for a smart assignment of workforce. It complies with restrictions that prevent excessive work, require breaks, and ensure that technicians are assigned tasks that match their skills, thus promoting the well-being of the workforce and the efficiency of operations. The computational investigation of the model shows that it has a remarkable ability to improve scheduling decisions which effectively reduce unassigned positions and uniformly distribute work hours. In essence, this research contributes a methodologically robust framework to the field of workforce scheduling, with the potential to inform the maintenance strategies of offshore wind farms and similar complex service systems.
引用
收藏
页数:17
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