Failure Pattern Recognition and Extended Tactical Spare Parts Supply Chain Planning

拟议的项目--集成智能维修系统和备件供应链--(I2MS2C)是由一个巴西-德国研究财团响应第三次BRAGECRIM呼吁提交的。整个项目扩展旨在通过整合智能维护系统(IMS)领域的更多先进技术，在迄今开发的解决方案之外，通过数据分析和供应链规划的新方法提供信息，从而提高复杂技术系统备件供应链(SPSC)管理活动的效力和效率。在巴西方面，分布式信息管理系统的开发将提高它们对运行条件变化的适应性，从而更好地预测单机的短期和长期故障，并在维护情况下优化服务技术人员的支持。项目扩展的德国部分旨在通过纳入分布式IMS和服务技术人员提供的故障模式和状态监控信息，进一步改进关于成本和服务水平的战术SPSC规划结果。此外，将分析协作规划的概念，并使其适用于小岛屿发展中国家的具体情况。通过数据分析中采用的方法对大型状态监测数据集进行分析，以便检测源于运行条件的故障模式。将开发故障预测方法，能够将识别的故障模式和状态监测信息整合在一起，以提高故障预测的质量。这些预测是根据I2MS2C项目第一阶段开发的方法计算备件需求的基础，从而实现高质量的SPSC规划。考虑到第一阶段正在开发的战术SPSC计划方法，希望在所考虑的计划领域有更高的差异性，以实现对整个供应链更准确和更可行的计划。因此，通过集成维修服务和生产计划领域，将开发出的集成计划方法将得到扩展。此外，不应孤立地看待小岛屿发展中国家的行为者，但他们的协作是一个明确的研究主题，以实现预期的效率和效力收益。因此，将利用第一个项目阶段制定的建模和评价框架，分析现有的国家方案概念在整个方案支助中心战术和业务规划中的适用性，并进行相应的调整。所有结果的性能将基于三个工业案例的模拟进行评估。通过对这些案例的比较，可以调查德国和巴西的特殊用途化学武器之间的差异和相似之处。

The proposed extension of the project - Integrating Intelligent Maintenance Systems and Spare Parts Supply Chains - (I2MS2C) is submitted by a Brazilian-German research consortium responding to the third BRAGECRIM call. The overall project extension aims to improve the effectiveness and efficiency of spare parts supply chain (SPSC) management activities for complex technical systems by the integration of further advanced technologies in the area of Intelligent Maintenance Systems (IMS) providing information utilized by new methods from data analytics and supply chain planning in addition to the developed solutions so far. On the Brazilian side the development of a distributed IMS should improve their adaptability to change operational conditions, resulting in a better short and long term failure forecasting of a single machine and the optimized support of the service technicians during maintenance situations. The German part of the project extension is targeting at the further improvement of tactical SPSC planning results regarding costs and service level by incorporating failure patterns and condition monitoring information provided by distributed IMS and the service technicians. Furthermore, collaborative planning (CP) concepts will be analysed and adapted to the specifics of SPSC. The large condition monitoring data sets are analyzed by adapted methods from data analytics in order to detect failure patterns stemming from operational conditions. Failure forecasting methods will be developed, being able to integrate the recognized failure patterns and the condition monitoring information in order to enhance the quality of failure forecasts. These predictions serve as a foundation for the calculation of the spare parts demand based on the methods developed in the first phase of the I2MS2C project, enabling a high quality SPSC planning. In view of the tactical SPSC planning method being developed in the first project phase a higher differentiation in the considered planning domains is aspired in order to achieve a plan being more exact and feasible for the whole supply chain. For that reason, the developed integrated planning method will be extended by integrating the domains of maintenance service and production planning. Furthermore, the actors of the SPSC shall not be regarded in an isolated way, but their collaboration is an explicit research subject for achieving the intended efficiency and effectiveness gains. Therefore, existing CP concepts will be analysed regarding their applicability in tactical and operational planning across the whole SPSC and adapted accordingly, using the modelling and evaluation framework developed in the first project phase. The performance of all results will be evaluated based on a simulation of three industrial cases. A comparison between these cases will allow an investigation of the differences and similarities between German and Brazilian SPSCs.