为支持先进制造业的标准中的基准制定新的数学定义。

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Craig M Shakarji, Vijay Srinivasan
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引用次数: 0

摘要

制造业数字化的最新进展促使美国机械工程师学会(ASME)和国际标准化组织(ISO)的标准委员会重新审查基准的定义。标准委员会考虑的任何新的基准定义都应涵盖设计中使用的所有基准特征类型,并支持传统计量方法和新的数字测量技术。这是一项具有挑战性的任务,需要谨慎折衷。本文介绍并分析了标准委员会考虑的各种替代方案。其中包括基于约束最小二乘法拟合的新基准数学定义。它似乎提供了最佳的折衷方案,并有可能支持日益依赖数字技术的先进制造业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward a New Mathematical Definition of Datums in Standards to Support Advanced Manufacturing.

Recent advances in the digitization of manufacturing have prompted ASME and International Organization for Standardization (ISO) standards committees to reexamine the definition of datums. Any new definition of datums considered by the standards committees should cover all datum feature types used in design and support both traditional metrological methods and new digital measurement techniques. This is a challenging task that requires some careful compromise. This paper describes and analyzes various alternatives considered by the standards committees. Among them is a new mathematical definition of datums based on constrained least-squares fitting. It seems to provide the best compromise and has the potential to support advanced manufacturing that is increasingly dependent on digital technologies.

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来源期刊
CiteScore
6.30
自引率
12.90%
发文量
100
审稿时长
6 months
期刊介绍: The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications. Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping
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