海上风电场多班维修计划中的技术人员分配

IF 4.2 Q2 ENERGY & FUELS
Md Imran Hasan Tusar , Bhaba R Sarker
{"title":"海上风电场多班维修计划中的技术人员分配","authors":"Md Imran Hasan Tusar ,&nbsp;Bhaba R Sarker","doi":"10.1016/j.ref.2024.100616","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>Technician Assignment Problem (TAP)</em> 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. <em>TAP</em> 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.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"51 ","pages":"Article 100616"},"PeriodicalIF":4.2000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755008424000802/pdfft?md5=c3372bd2c2ce9bd496f06d74dc3a53be&pid=1-s2.0-S1755008424000802-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Technician assignment in multi-shift maintenance schedules in an offshore wind farm\",\"authors\":\"Md Imran Hasan Tusar ,&nbsp;Bhaba R Sarker\",\"doi\":\"10.1016/j.ref.2024.100616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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 <em>Technician Assignment Problem (TAP)</em> 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. <em>TAP</em> 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.</p></div>\",\"PeriodicalId\":29780,\"journal\":{\"name\":\"Renewable Energy Focus\",\"volume\":\"51 \",\"pages\":\"Article 100616\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1755008424000802/pdfft?md5=c3372bd2c2ce9bd496f06d74dc3a53be&pid=1-s2.0-S1755008424000802-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Renewable Energy Focus\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1755008424000802\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable Energy Focus","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1755008424000802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

摘要

海上风电场对可持续能源战略越来越重要,但其维护工作却面临着独特的后勤挑战。本研究的重点是技术人员分配问题(TAP),它涉及一个复杂多变的调度问题。主要目标是确定最有效的技术人员维护任务分配,以最大限度地提高运营效率,确保可靠的服务。本研究引入了一个数学优化模型,对技术人员的可用性、技能组合和时间限制等众多变量进行处理,以最大限度地减少未满足的维护需求,确保工作量的公平分配。该模型基于从实际运行条件和人力资源实践中得出的假设,保证其结果不仅在理论上有效,而且在实践中可行。TAP 遵守劳动法规,利用人力资源能力,实现劳动力的智能分配。它符合防止过度工作、要求休息和确保技术人员分配到与其技能相匹配的任务等限制条件,从而促进了劳动力的福利和运营效率。对模型的计算研究表明,该模型在改进调度决策方面具有显著的能力,能有效减少未分配的岗位,并统一分配工作时间。从本质上讲,这项研究为劳动力调度领域贡献了一个方法稳健的框架,有可能为海上风电场和类似复杂服务系统的维护策略提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technician assignment in multi-shift maintenance schedules in an offshore wind farm

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Renewable Energy Focus
Renewable Energy Focus Renewable Energy, Sustainability and the Environment
CiteScore
7.10
自引率
8.30%
发文量
0
审稿时长
48 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信