A KNOWLEDGE-BASED SYSTEM ENGINEERING PROCESS FOR OBTAINING ENGINEERING DESIGN SOLUTIONS-猫眼课题宝

DOI：

10.1115/detc2005-85561

发表时间：

2005

期刊：

影响因子：

通讯作者：

中科院分区：

其他

文献类型：

作者：

B. Prasad;J. Rogers

设计和开发高度工程化的产品需要客户规格和产品特征(或其行为)之间的直接(和更动态的)关联。为了满足指定的客户性能、成本和完整性目标，应该在多个层次(系统、子系统、部件和部件)执行大量专门的分析、启发式、捷径、查找表、方程、算法、有限元和材料替换。这种工程产品的产品几何形状通常很复杂，许多部件都是使用3D商业计算机辅助设计(CAD)从零开始交互设计的-最近通常被称为产品生命周期管理(PLM)系统。如今，这种非常“基于PLM”的工程化产品设计过程通常是“静态的”，非常“依赖于特征或几何”，“知识密集”，因此，工程师通常需要相当长的时间(几个月)来完成这一手动过程。如今，越来越多的公司希望从众多系列解决方案(对应于各种设计权衡研究)中快速重新设计产品。他们对某种动态形式的基于决策的系统感兴趣，该系统可以自动筛选大量历史产品解决方案，并快速重新配置一个以最少的成本、重量和时间投资满足客户要求的解决方案。这种以决策为基础的产品自动化无论如何都不是一件容易的事情。不了解特定几何图形的产品定义很难构思、获取和广泛重用(通过任何生成性工具)。典型的产品开发过程本质上是高度动态的、非线性的、离散的、依赖于功能的和依赖于部件的。解决问题并不容易，因为问题的表达是有时间限制的，有许多离散的输入、拓扑结构和几个数学上的不连续。本文讨论了2002年在帕克建立的知识驱动自动化(KDA)计划的体系结构。它解决了上述许多产品开发问题和问题。特别是，作者描述了在商业PLM环境中获得工程设计解决方案的基于知识的系统工程过程。该体系结构和解决方案使用了许多创新的基于知识的工程(KBE)概念和程序。通过战略性地使用创成式建模、电子表格、零件和装配模板、系统工程概念以及我们专有的“智能零件概念”，作者能够使用一组PLM(CATIA V5及其基础知识)工具，根据他们的客户规格自动设计和配置一系列液压执行器。版权所有？ASME？2005

Designing and developing highly engineered products requires direct (and more dynamic) associations between customers’ specifications and product characteristics (or its behaviors). In order to meet the specified customer performance, cost, and integrity goals, a multitude of specialized analyses, heuristics, shortcuts, look-up tables, equations, algorithms, finite elements, and material substitution at multiple levels (system, subsystems, components and parts) are ought to be performed. The product geometries of such engineered product are often complex and many parts are designed interactively from scratch using a 3D commercial computer-aided design (CAD) — lately often referred as Product Life-cycle Management (PLM) system. Today, this very “PLM-based” engineered product-design process is often “static”, very “feature or geometry-dependent,” “knowledge-intensive,” and therefore, engineers often takes considerable time (months) to complete this manual process. Today, more and more companies want to quickly reengineer a product from a multitude of family solutions (corresponding to various design trade-off studies). They are interested in some dynamic form of a decision-based system that could automatically filter through a multitude of historical product solutions and quickly reconfigure one that meets the customer requirements with the least cost, weight, and time investment. Such decision-based product automation is not an easy task by any means. Product definitions without knowing specific geometry are hard to conceive, capture generically, and reuse widely (via any generative tool). A typical product development process —by its nature—is highly dynamic, nonlinear, discrete, feature-dependent, and part-dependent. The solution is not easy, since problem formulation is time-bound, has numerous discrete inputs, topologies, and several mathematical discontinuities. This paper discusses the system architecture of the Knowledge-driven Automation (KDA) program — established at Parker in 2002. It addresses many of the above product development issues and problems. In particular, authors describe a Knowledge-based System Engineering Process for Obtaining Engineering Design Solutions in a Commercial PLM Setting. The architecture and solutions use a number of innovative knowledge-based engineering (KBE) concepts and procedures. Through strategic use of generative modeling, spreadsheet tables, part and assembly templates, system engineering concepts, and our proprietary “smart part concepts,” authors were able to engineer-to-configure a family of hydraulic actuators automatically from their customer specifications using a set of PLM (CATIA V5 and its underlying knowledgeware) tools.Copyright © 2005 by ASME

A KNOWLEDGE-BASED SYSTEM ENGINEERING PROCESS FOR OBTAINING ENGINEERING DESIGN SOLUTIONS

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