ESS: Scheduling, Inventory Optimization, and Coordination of Maintenance Networks

ESS：调度、库存优化和维护网络协调

• 批准号: 0223443
• 负责人: Peter Luh
• 金额: $ 14.95万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2005-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0223443&HistoricalAwards=false
• 关键词: ESS; Scheduling; Inventory; Optimization; Coordination

Many industries rely on the proper functioning of their key assets, such as airlines on jet engines, electric utilities on generators, and army on helicopters. A major obstacle on operation efficiency is asset unavailability due to forced outages and regular maintenance operations. The latter, although planned, are generally characterized by long and uncertain durations. Instead of embarking on more intensive preventative maintenance programs, the trend is to monitor asset conditions, and perform maintenance operations based on conditions to increase asset availability and reliability. This imposes major challenges on the networks of maintenance service providers, including overhaul shops, repair shops, part distributors, and spare part manufacturers, to have short and predictable turn-around-times while reducing inventory in systems traditionally characterized by massive uncertainties.The research is on scheduling, inventory optimization, and coordination of maintenance service networks under dynamic and uncertain environments to meet the challenges of condition-based maintenance. By closely collaborating with our industrial partners United Technologies Research Center and i2 Technologies, Inc., three tasks will be performed. The first is to develop stochastic scheduling models for large-scale maintenance service networks based on a realistic discrete event simulation model provided by our industrial partners. A solution methodology that synergistically combines Lagrangian relaxation, stochastic optimization, and simulation will be developed to provide near-optimal solutions with quantifiable quality and confidence. The second task is to optimize part inventory, balancing inventory costs and part availability for the scheduling method developed in Task 1. Continuous and periodic review policies will be examined, and ordinal optimization will be used to optimize policy parameters. In the third task, the autonomous nature of various organizations within a maintenance service network will be investigated. The models of Tasks 1 and 2 will be decentralized. A distributed and asynchronous coordination mechanism will be established, building on the pricing concept that is consistent with the methods developed in Task 1. A mobile multi-agent system will then be designed and implemented for Internet-based deployment of the methods, paving the way for the next generation e-maintenance service networks. Our goal is to reap the full benefit of the new maintenance service paradigm by having short and predictable turn-around-times while reducing inventory levels, making the best use of asset condition information and the information technology infrastructure. The research shall also significantly contribute to the fundamental theory and practice of scheduling, inventory management, and supply chain management, improving the competitiveness and reliability of service enterprises.

许多行业依靠其主要资产的正常运作，例如喷气发动机上的航空公司，发电机上的电力公司和直升机上的陆军。 由于强迫停电和定期维护操作，运营效率的主要障碍是资产不可用。 后者虽然有计划，但通常以较长且不确定的持续时间为特征。 趋势不是启动更密集的预防性维护计划，而是监视资产条件，并根据条件进行维护操作，以提高资产可用性和可靠性。 这在维护服务提供商的网络上构成了主要挑战，包括大修商店，维修店，零件分销商和备件制造商，具有短暂而可预测的转折时间，同时减少传统上的库存，传统上以大规模的不确定性为特征。该研究是在调度，既定不确定性的构建，构成的维护范围和不在维护的环境中，并构成了不确定的维护和不确定性的态度，并确定了态度的动态范围。 通过与我们的工业合作伙伴联合技术研究中心和I2 Technologies，Inc。密切合作，将执行三个任务。 首先是基于我们工业合作伙伴提供的现实离散事件仿真模型，为大规模维护服务网络开发随机调度模型。 将开发一种协同结合拉格朗日放松，随机优化和模拟的解决方案方法，以提供可量化的质量和信心提供近乎最佳的解决方案。 第二个任务是优化零件库存，平衡库存成本和任务1中开发的调度方法的零件可用性。将检查连续和定期的审查策略，并将使用顺序优化来优化策略参数。 在第三个任务中，将研究维护服务网络中各种组织的自治性。 任务1和2的模型将分散。 将建立分布式和异步协调机制，建立在定价概念的基础上，该概念与任务1中开发的方法一致。然后将设计和实施一种移动多机构系统，用于基于Internet的方法部署，为下一代电子欣赏服务网络铺平了道路。 我们的目标是通过缩短库存水平，充分利用资产条件信息和信息技术基础架构，从而充分利用新的维护服务范式。 这项研究还应为调度，库存管理和供应链管理的基本理论和实践做出重大贡献，从而提高服务企业的竞争力和可靠性。