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Fault Region Localization: Product and Process Improvement Based on Field Performance and Manufacturing Measurements

机译:故障区域本地化:基于现场性能和制造度量的产品和过程改进

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Customer feedback in the form of warranty/field performance is an important direct indicator of quality and robustness of a product. Linking warranty information to manufacturing measurements can identify key design and process variables that are related to warranty failures. Warranty data have been traditionally used in reliability studies to determine failure distributions and warranty cost. This paper proposes a novel fault region localization methodology to link warranty failures to manufacturing measurements (hence, to design and process parameters) for diagnosing warranty failures and to perform tolerance revaluation. The methodology consists of identifying relations between warranty failures and design/process variables using rough sets-based analysis on training data consisting of warranty information and manufacturing measurements. The methodology expands the rough set-based analysis by introducing parameters for inclusion of noise and uncertainty of warranty data classes. Based on the identified parameters related to the failure, a revaluation of the original tolerances can be performed to improve product robustness. The proposed methodology is illustrated using case studies of two warranty failures from the electronics industry. Note to Practitioners—Warranty failures are indicative of the performance and robustness of the product. Warranty failures, especially those that occur early (e.g., within six months after sale), can be caused by interactions between various design and process characteristics of the individual components of the product. Due to the large number of components and the interactions between them, it is difficult to identify all of these relations during design. Furthermore, it is difficult to replicate actual product usage in the field during the design stage. The methodology proposed in this paper integrates a product''s warranty failure information with that of measurement data collected during manufacturing, to identify relevant design and process variables related to the failures. It also identifies the warranty fault region within the original design tolerance window for the parameters. This can help in avoiding warranty failure(s) through design changes and/or tolerance revaluation. The methodology was appli-ed in the electronics and semiconductor industries.
机译:保修/现场性能形式的客户反馈是产品质量和耐用性的重要直接指标。将保修信息链接到制造度量可以识别与保修失败相关的关键设计和过程变量。传统上,在可靠性研究中使用保修数据来确定故障分布和保修成本。本文提出了一种新颖的故障区域定位方法,可将保修故障与制造度量(因此,设计和工艺参数)联系起来,以诊断保修故障并进行公差重新评估。该方法包括对包含保修信息和制造度量的培训数据使用基于粗集的分析来确定保修失败与设计/过程变量之间的关系。该方法通过引入包含噪声和保修数据类别不确定性的参数,扩展了基于粗糙集的分析。基于与故障相关的已识别参数,可以对原始公差进行重新评估以提高产品的耐用性。通过对电子行业两次保修失败的案例研究,说明了所提出的方法。从业人员注意—保修失败表示产品的性能和耐用性。保修失败,尤其是那些较早发生(例如,售后六个月内)的保修失败,可能是由产品各个组件的各种设计和工艺特性之间的相互作用引起的。由于大量的组件及其之间的相互作用,因此在设计过程中很难识别所有这些关系。此外,在设计阶段很难在现场复制实际的产品使用情况。本文提出的方法将产品的保修故障信息与制造过程中收集的测量数据相集成,以识别与故障相关的相关设计和工艺变量。它还在参数的原始设计公差窗口内标识保修故障区域。通过设计更改和/或容差重估,这可以帮助避免保修失败。该方法已应用于电子和半导体行业。

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