An adaptive simulation-based optimisation approach for the scheduling and control of dynamic manufacturing systems - Phase 2

用于动态制造系统调度和控制的基于自适应仿真的优化方法 - 第 2 阶段

• 批准号: 288035798
• 负责人: Professor Dr.-Ing. Michael Freitag
• 金额: --
• 依托单位: BIBA - Bremer Institut für Produktion und Logistik GmbH an der Universität Bremen
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/288035798?language=en
• 关键词: adaptive; simulation; based; optimisation; approach

In order to assure a high performance of dynamic manufacturing systems, the currently processed project AdaptiveSBO develops a data-driven adaptive simulation-based optimisation (SBO) method that derives optimised machine assignment and dispatching rules according to the current state of a manufacturing in real-time. The approach couples an SBO method deriving optimised rules for shop floor control with a framework for the data exchange between the SBO method and the manufacturing system. In this way, the optimisation always considers the current state of the system. Until now, the approach assumes an ensured availability of raw material and does not consider possible lacks. Moreover, the current approach only takes into account maintenance indirectly by performing reactive maintenance when a machine breakdown occurs. In order to reflect the current state of a production system in a more detailed and realistic way, these aspects will be taken into account in the proposed continuation of this project. In this way, the approach will on the one hand be able to derive well-founded solutions in the unwanted case of a lack of raw material and will, on the other hand, achieve less machine downtimes and therefore save costs. The main goal of the proposed project continuation is the development of a data-driven adaptive SBO method for integrated inventory, production and maintenance control.In order to achieve the main goal of the project, the already developed SBO method has to be extended in several ways. On the one hand, the method has to be expanded to derive priorities for maintenance jobs as well as production jobs depending on the current raw material inventory levels. On the other hand, the developed data exchange framework has to be extended to include all relevant data for the bidirectional data exchange between the new adaptive SBO method and the shop floor.While the German research group develops an SBO approach for integrated production and maintenance control, the Brazilian research group develops in parallel an SBO approach for integrated production and inventory control. Subsequently, the two approaches are merged to achieve the main goal of the project. For the examination of a realistic production scenario, the approach is applied to the job shop of a Brazilian producer of mechanical parts. Based on this scenario a test bench platform is developed, which is used for the evaluation of the developed method. The results will be published as a benchmark for future research in this field.

为了确保动态制造系统的高性能，目前正在处理的项目AdaptiveSBO开发了一种数据驱动的自适应模拟优化(SBO)方法，该方法根据制造的当前状态实时得出优化的机器分配和调度规则。该方法将导出车间控制优化规则的SBO方法与SBO方法与制造系统之间的数据交换框架相结合。通过这种方式，优化始终考虑系统的当前状态。到目前为止，该方法假设原材料的可用性得到保证，而不考虑可能的短缺。此外，目前的方法只通过在机器发生故障时执行反应性维护来间接考虑维护。为了更详细、更切合实际地反映生产系统的现状，本项目的拟议续展将考虑到这些方面。通过这种方式，这种方法一方面能够在缺乏原材料的不必要情况下获得有充分依据的解决方案，另一方面将实现更少的机器停机时间，从而节省成本。提出的项目延续的主要目标是开发一种数据驱动的自适应SBO方法，用于集成库存、生产和维护控制。为了实现项目的主要目标，必须从多个方面对已开发的SBO方法进行扩展。一方面，该方法必须扩展，以根据当前的原材料库存水平得出维护作业和生产作业的优先级。另一方面，开发的数据交换框架必须扩展到包括新的自适应SBO方法和车间之间的双向数据交换的所有相关数据。德国研究小组开发了用于集成生产和维护控制的SBO方法，而巴西研究小组并行开发了用于集成生产和库存控制的SBO方法。随后，这两种方法被融合在一起，以实现项目的主要目标。为了检验一个现实的生产场景，该方法被应用于一家巴西机械零件生产商的车间。在此基础上，开发了一个测试平台，用于对所开发的方法进行评估。这些结果将作为这一领域未来研究的基准发表。