Development of a Decision Tool for Dynamic Scheduling and Routing of Maintenance Technicians for a Distributed Fleet of Machines

开发用于分布式机器群维护技术人员动态调度和路由的决策工具

• 批准号: 485048-2015
• 负责人: Diallo, Claver
• 金额: $ 0.91万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=584685
• 关键词: Development; Decision; Tool; Dynamic; Scheduling

A recently completed Engage grant titled "Proactive Diagnostic Process Optimization and Integration for a Distributed Fleet of Machines" led to the development of a mathematical model integrating failure predictions into the daily maintenance operations carried out by technician in charge of maintaining the Electronic Gaming Machines (EGMs) manufactured by GTECH. The mathematical model and the prototype decision-making tool are able to efficiently schedule the preventive maintenance (PM) visits, determine and insert opportunistic inspections and replacements into the scheduled technician routes. The current model needs to be further developed to include new requirements and constraints from the end-user and account for new field data received from new machines that were deployed while the previous Engage project was already in progress. The extension will deal with the addition of fixed time window visits at specific nodes of the network to account for the sales visits also carried out by the technicians. The model needs to be modified to account for multiple restarts of the optimization model during the day from different starting nodes (not necessarily the initial depot). The current static model will be modified to dynamically schedule and route all maintenance and sales visits and display the optimal routes on a map for a user-friendly utilization by the technicians. Additional field data analysis will also be performed to determine and set the values of key parameter values used in the model.

最近完成的一项名为“主动诊断过程优化和集成， 分布式机群”导致了集成故障预测的数学模型的发展 负责维护电子游戏的技术人员进行的日常维护操作 GTECH制造的机器（EGM）。数学模型与原型决策工具 能够有效地安排预防性维护（PM）访问，确定并插入机会性 检查和更换到预定的技术路线。 目前的模式需要进一步发展，以包括最终用户的新要求和限制 并说明从上一次Engage部署时部署的新机器接收的新现场数据 项目已经在进行中。延期将涉及增加固定时间窗口访视， 网络的特定节点，以说明也由技术人员执行的销售访问。模型 需要进行修改，以考虑在一天中从不同的 起始节点（不一定是初始仓库）。当前的静态模型将被修改为动态模型， 计划和安排所有维护和销售访问，并在地图上显示最佳路线， 技术人员的使用。还将进行额外的现场数据分析，以确定和设置 模型中使用的关键参数值。