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

最近完成的Engage赠款，标题为“针对 《分布式机队》导致了集成故障预测的数学模型的发展 由负责维护电子游戏的技术人员进行日常维护操作 由GTECH制造的机器(EGM)。数学模型及原型决策工具 能够有效地安排预防性维护(PM)访问，确定并插入机会 按照预定技术人员路线进行检查和更换。 目前的模式需要进一步发展，以包括来自最终用户的新要求和约束 并考虑从以前参与时部署的新计算机接收到的新现场数据 项目已经在进行中。延期将处理增加固定时间窗口访问的问题。 针对具体节点的网络销售情况，技术人员也进行了走访。模型 需要进行修改，以适应优化模型在一天中从不同的 起始节点(不一定是初始站点)。当前静态模型将修改为动态 计划和安排所有维护和销售访问的路线，并在地图上显示最佳路线，以便于用户使用 由技术人员使用。还将执行其他现场数据分析，以确定和设置 模型中使用的关键参数值。

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.