Dynamic Evaluation of Machine Tool Process Capability
机床工艺能力动态评价
基本信息
- 批准号:0322869
- 负责人:
- 金额:$ 42.82万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2003
- 资助国家:美国
- 起止时间:2003-09-01 至 2007-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The primary objective of this research is to investigate novel techniques and strategies for dynamically measuring the process capability of machine tools. A secondary purpose is to investigate the use of process capability information to accurately estimate machining costs. The research approach combines real-time sensor data with unique cutting force process models that are both accurate and computationally efficient. Process capability will be estimated by comparing measured cutting forces with concurrent model simulation results. An open-architecture machine tool controller will be used to collect and store measurement data, run model simulations, and dynamically update the process capability. Extensive experimental studies will focus on three parameters deemed to be the most difficult to characterize: tool runout, tool deflection and tool wear. Generality will be tested with an experimental matrix that includes a variety of different cutting conditions, cutter types, and ferrous and non-ferrous alloy materials.Successful completion of this research project would improve the reliability, accuracy and efficiency of machine tools by giving them self-knowledge of their process capabilities. Process capability information could also be used to accurately estimate machining costs, thereby providing valuable feedback to designers about the cost implications of their design choices. Process capabilities of a specific machine tool could be intelligently matched with part tolerance requirements to ensure defect free production. Part quality could be maintained over time by adjusting cutting strategies and conditions in response to changing process capability. This project will also support the Smart Machine Initiative of the National Institute of Standards and Technology and is consistent with the goals of the Integrated Manufacturing Initiative, a public/private consortium of industry, academic, and government partners designed to strength the nation's manufacturing community.
本研究的主要目的是探讨新的技术和策略,动态测量机床的过程能力。 第二个目的是调查使用过程能力信息来准确估计加工成本。 该研究方法将实时传感器数据与独特的切削力过程模型相结合,这些模型既准确又计算效率高。将通过比较测量的切削力与并行模型模拟结果来估计过程能力。 一个开放式结构的机床控制器将用于收集和存储测量数据,运行模型模拟,并动态更新的过程能力。 广泛的实验研究将集中在三个参数被认为是最难表征:刀具跳动,刀具偏转和刀具磨损。 通用性将通过一个实验矩阵进行测试,该矩阵包括各种不同的切削条件、刀具类型以及黑色和有色合金材料。该研究项目的成功完成将通过使机床对自己的工艺能力有自我认识来提高机床的可靠性、精度和效率。过程能力信息也可以用来准确地估计加工成本,从而为设计人员提供关于其设计选择的成本影响的有价值的反馈。 特定机床的加工能力可以与零件公差要求智能匹配,以确保无缺陷生产。 零件质量可以通过调整切割策略和条件来保持,以响应不断变化的过程能力。 该项目还将支持国家标准与技术研究所的智能机器计划,并与集成制造计划的目标一致,该计划是一个由工业,学术和政府合作伙伴组成的公共/私人联盟,旨在加强国家的制造业社区。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Robert Jerard其他文献
Robert Jerard的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Robert Jerard', 18)}}的其他基金
Dynamic Calibration of a Smart Machining System Using Robust Non-Intrusive Sensors
使用稳健的非侵入式传感器对智能加工系统进行动态校准
- 批准号:
0620996 - 财政年份:2006
- 资助金额:
$ 42.82万 - 项目类别:
Standard Grant
Toolpath Optimization by Real-time Application of an Integrated Geometric/Mechanistic Model
通过实时应用集成几何/机械模型进行刀具路径优化
- 批准号:
9872575 - 财政年份:1998
- 资助金额:
$ 42.82万 - 项目类别:
Standard Grant
FACILE: A Clean Interface Design and Fabrication of Mechanical Parts
FACILE:简洁的界面设计和机械零件制造
- 批准号:
9713906 - 财政年份:1997
- 资助金额:
$ 42.82万 - 项目类别:
Continuing Grant
Sculptured Surface Discretization for Numerically Controlled (NC) Machining
用于数控 (NC) 加工的雕刻表面离散化
- 批准号:
9301115 - 财政年份:1993
- 资助金额:
$ 42.82万 - 项目类别:
Continuing Grant
Numerically Controlled Machining of Sculptured Surfaces
雕刻表面的数控加工
- 批准号:
9015851 - 财政年份:1991
- 资助金额:
$ 42.82万 - 项目类别:
Continuing Grant
Engineering Research Equipment Award: Geometric and Mechanistic Models of Numerically Controlled Machining
工程研究装备奖:数控加工几何与机械模型
- 批准号:
8811498 - 财政年份:1988
- 资助金额:
$ 42.82万 - 项目类别:
Standard Grant
Automatic Machine Tool Path Generation
自动机床路径生成
- 批准号:
8512621 - 财政年份:1986
- 资助金额:
$ 42.82万 - 项目类别:
Standard Grant
相似国自然基金
基于重要农地保护LESA(Land Evaluation and Site Assessment)体系思想的高标准基本农田建设研究
- 批准号:41340011
- 批准年份:2013
- 资助金额:20.0 万元
- 项目类别:专项基金项目
相似海外基金
HSI Implementation and Evaluation Project: Undergraduate Research Experiences in Machine Learning for First Generation Students
HSI 实施和评估项目:第一代学生的机器学习本科研究经验
- 批准号:
2345361 - 财政年份:2024
- 资助金额:
$ 42.82万 - 项目类别:
Continuing Grant
Quantitative Study of Public Accountability based on Behavioral Public Administration: Analyzing Evaluation Reports Using Machine Learning and Experimental Method
基于行为公共管理的公共问责量化研究:利用机器学习和实验方法分析评估报告
- 批准号:
23K18770 - 财政年份:2023
- 资助金额:
$ 42.82万 - 项目类别:
Grant-in-Aid for Research Activity Start-up
Active Evaluation of Machine Learning Models
机器学习模型的主动评估
- 批准号:
23H03456 - 财政年份:2023
- 资助金额:
$ 42.82万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
The development of measurement and skill evaluation system for practical laparoscopic surgical procedure using machine learning
利用机器学习开发实用腹腔镜手术测量和技能评估系统
- 批准号:
22KJ0118 - 财政年份:2023
- 资助金额:
$ 42.82万 - 项目类别:
Grant-in-Aid for JSPS Fellows
Machine-Assisted Interdisciplinary Approach For Early Clinical Evaluation of Neurodevelopmental Disorders
机器辅助跨学科方法对神经发育障碍的早期临床评估
- 批准号:
10394658 - 财政年份:2022
- 资助金额:
$ 42.82万 - 项目类别:
Machine-Assisted Interdisciplinary Approach For Early Clinical Evaluation of Neurodevelopmental Disorders
机器辅助跨学科方法对神经发育障碍的早期临床评估
- 批准号:
10555279 - 财政年份:2022
- 资助金额:
$ 42.82万 - 项目类别:
Development of a Evaluation Support System for Strength of Pelvic Floor Muscle Based on Machine Learning of Ultrasound Image Database
基于超声图像数据库机器学习的盆底肌肉力量评估支持系统的开发
- 批准号:
22K19639 - 财政年份:2022
- 资助金额:
$ 42.82万 - 项目类别:
Grant-in-Aid for Challenging Research (Exploratory)
Evaluation of Mud Rush Risk in Block Cave Mining by Using Machine Learning Techniques
利用机器学习技术评估块洞采矿中的泥涌风险
- 批准号:
560057-2021 - 财政年份:2022
- 资助金额:
$ 42.82万 - 项目类别:
Alexander Graham Bell Canada Graduate Scholarships - Doctoral
Research on the creation and evaluation of high-performance scalable fully coupled Ising machine LSI
高性能可扩展全耦合伊辛机LSI创建与评估研究
- 批准号:
22H01559 - 财政年份:2022
- 资助金额:
$ 42.82万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
I-Corps: Machine Learning Enhanced Automated Circuit Configuration and Evaluation of Power Converters
I-Corps:机器学习增强电源转换器的自动化电路配置和评估
- 批准号:
2245187 - 财政年份:2022
- 资助金额:
$ 42.82万 - 项目类别:
Standard Grant














{{item.name}}会员




