A Responsive Process Planning System in Agile Manufacturing Using Case-Based Reasoning Approach

使用基于案例的推理方法的敏捷制造响应式流程规划系统

• 批准号: 9612067
• 负责人: Wen Lu
• 金额: $ 11.08万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-10-01 至 1998-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9612067&HistoricalAwards=false
• 关键词: Responsive; Process; Planning; System; Agile

9612067 Lu This award provides funding for research to develop a model of the responsive process planning system in agile manufacturing with a focus on automated determination of the sequence of machining operations in agile manufacturing environments for axisymmetric machined parts. An approach using case-based reasoning to support learning capability will be employed. The methodology to accomplish various issues in case-based operation sequencing will be formalized. In particular, the following issues will be tackled. First, a feature-based representation will be used for operation sequencing case representation. Then, a method called model-based similarity measurement, based on a domain-specific hierarchical model, will be applied for case indexing and case retrieval. Furthermore, the adaptation of an operation sequencing case including case modifier, plan simulator, and plan repairer will be developed. The system model will be implemented to demonstrate the learning functions of the system in response to rapidly changing markets and manufacturing environments. The generated process plans will be evaluated. If successful, this research will lead machine learning into the realm of practical application in agile manufacturing and provide a way to guide a computer-aided process planning system towards the level of human intelligence. It also offers to capture best practices through industry interaction and thus prevent the loss of knowledge through the attrition of experienced personnel. Furthermore, the proposed process planning system, with enhanced intelligence through learning, should respond rapidly to fast changing demands and enable the realization of the agile manufacturing concept of shorter time-to-market and the increase of product quality. It is expected that this model could be extended to other activities, such as product design, metal forming planning, and assembly planning, in the industry.

该奖项为开发敏捷制造中响应过程规划系统模型的研究提供资金，重点是在轴对称加工零件的敏捷制造环境中自动确定加工操作顺序。将采用基于案例的推理方法来支持学习能力。在基于案例的操作排序中，完成各种问题的方法将被正式化。重点解决以下问题：首先，将基于特征的表示用于操作排序用例表示。然后，将基于特定领域层次模型的基于模型的相似性度量方法应用于案例索引和案例检索。此外，还将开发包括案例修改器、计划模拟器和计划修复器在内的操作排序案例的适配。该系统模型将用于演示系统的学习功能，以响应快速变化的市场和制造环境。生成的工艺计划将被评估。如果成功，这项研究将引领机器学习进入敏捷制造的实际应用领域，并提供一种指导计算机辅助工艺规划系统走向人类智能水平的方法。它还提供通过行业互动获取最佳实践，从而防止因经验丰富的人员流失而导致的知识损失。此外，所提出的工艺规划系统通过学习增强智能，能够快速响应快速变化的需求，实现缩短产品上市时间和提高产品质量的敏捷制造理念。预计该模型可以扩展到工业中的其他活动，如产品设计、金属成形计划和装配计划。