Design Classification and Hybrid Variant/Generative Process Planning

这笔赠款提供资金，以解决将信息技术应用于工程的两个问题领域。要解决的第一个领域是开发使用详细的产品设计属性对设计进行自动分类和检索的技术，这些属性比集团技术代码更有意义和更准确，并且可以根据数据库中存储的设计自动计算。要解决的第二个领域是开发一种混合的变型/创成式工艺设计方法，该方法将结合变型工艺设计和创成式工艺设计的最佳特点，同时避免各自的最坏限制。当新设计需要工艺计划时，混合方法将使用上述分类方案来检索与设计的相应部分相关的多个计划的部分或“切片”，然后组合这些切片并对其进行修改以产生新设计的计划。如果成功，这项工作将有以下好处。首先，它将以一种创新的方式结合变型和生成式工艺规划的优点。与传统的变型工艺规划一样，提出的工艺规划方法将构建工艺工程师可能需要改进的工艺计划。然而，通过自动使检索的计划适应新的设计要求，它将最大限度地减少对这种改进的需要，从而产生比以前的方法更成功的实施和应用。其次，这项拟议的工作将开发技术，帮助设计和制造工程师有效地利用遗留数据，并使其适应新的问题。据估计，实习工程师会花费80%以上的时间在遗留数据、目录和更早的工程项目中进行搜索，这应该会对工程实践产生重大的积极影响。

This grant provides funding to address two problem areas in the application of information technology to engineering. The first area to be addressed is the development of techniques for automatic classification and retrieval of designs using detailed product design attributes that are more meaningful and accurate than Group Technology codes and can be computed automatically from the designs stored in the database. The second area to be addressed is the development of a hybrid variant/generative approach to process planning that will combine the best characteristics of both variant and generative process planning, while avoiding the worst limitations of each. When a process plan is needed for a new design, the hybrid approach will use the above classification scheme to retrieve portions or `slices` of several plans that are relevant for corresponding portions of the design, and then will combine these slices and modify them to produce a plan for the new design. If successful, this work will have the following benefits. First, it will combine, in an innovative way, the strengths of both variant and generative process planning. Like traditional variant process planning, the proposed approach to process planning will construct process plans that the process engineer may need to improve. However, by automatically adapting the retrieved plans to the new design requirements, it will minimize the need for such improvements, thus producing more successful implementations and applications than previous methods. Second, the proposed work will develop techniques that help design and manufacturing engineers effectively use legacy data and adapt it to new problems. Since it is estimated that practicing engineers spend more than 80 percent of their time searching through legacy data, catalogs, and earlier engineering projects, this should have significant positive impact on engineering practice.