SGER: Identification of General Probability Models for a Taxonomy of Manufacturing Processes

SGER：制造过程分类的一般概率模型的识别

• 批准号: 0226410
• 负责人: Esma Gel
• 金额: $ 9.99万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-15 至 2004-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0226410&HistoricalAwards=false
• 关键词: SGER; Identification; General; Probability; Models

The objectives of this Small Grant for Exploratory Research (SGER) are to: 1) Create general probability models for key quality characteristics of a subset of the taxonomy of manufacturing processes. The selected taxonomy will specify the following classifications (a) the type of Geometric dimensioning and tolerancing (GD&T) requirements for form and location. (b) the type of manufacturing process and product material; and (c) the type of inspection device. The models will be chosen based on their accuracy and generality in representing the realistic behavior of process outputs; and 2) For each of the general probability models, define an appropriate summary statistic that incorporates the engineering requirements and the random nature of the process behavior. Having studied the output from various materials, processes measurement devices, complex GD&T acceptance zones, and normal/non-normal univariate/multivariate distributions in the first part of this research, we plan to define a set of statistics useful for summarizing performance and setting goals. Summary statistics will be chosen based on their distributional properties and will be used to define sample size requirements and critical acceptance values useful for supporting vendor relations and setting process performance goals. The results of this research will constitute a complete methodology for capturing and summarizing the behavior of inspection data (i.e.. probability' models). Data sets provided by industrial partners (Intel. Motorola. and Simula Safety Systems) will provide the modeling environment and validation of research. The project's deliverable will be a published catalogue of probability models that can be directly mapped to form and location GD&T requirements, manufacturing processes, materials and measurement systems for a subset of entries in the manufacturing taxonomy. Should this research prove successful. a follow-on project will be prepared for more categories in the taxonomy. In total, this research project is expected to have usable models for industrial decision-making, planning, and analysis as well as the theoretical contributions in performance summary statistics.

这项探索性研究小额补助金（SGER）的目标是：1）为制造过程分类的一个子集的关键质量特性创建通用概率模型。 所选分类将指定以下分类：（a）形状和位置的几何尺寸和公差（GD T）要求的类型。(b)制造工序及产品物料的种类;及（c）检验仪器的种类。将根据模型在代表过程输出的实际行为方面的准确性和通用性来选择模型; 2）对于每个一般概率模型，定义一个适当的汇总统计量，该统计量包含工程要求和过程行为的随机性。 在本研究的第一部分中，研究了各种材料、工艺测量设备、复杂GD T接受区以及正态/非正态单变量/多变量分布的输出后，我们计划定义一组用于总结性能和设定目标的统计数据。 将根据其分布特性选择汇总统计量，并将其用于定义样本量要求和关键验收值，这些值可用于支持供应商关系和设定工艺性能目标。 这项研究的结果将构成一个完整的方法来捕捉和总结的行为检查数据（即。概率模型）。 工业合作伙伴提供的数据集（英特尔。摩托罗拉和Simula安全系统）将提供建模环境和研究验证。该项目的可交付成果将是一个已发布的概率模型目录，可直接映射到制造分类中条目子集的形式和位置GD T要求、制造工艺、材料和测量系统。 如果这项研究成功的话。将为分类法中的更多类别准备一个后续项目。总的来说，这个研究项目预计将有可用的模型，工业决策，规划和分析，以及在性能汇总统计的理论贡献。