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We present a new method for the statistical process control of lattice structures using tools from Topological Data Analysis. Motivated by applications in additive manufacturing, such as aerospace components and biomedical implants, where…

Methodology · Statistics 2025-10-15 Yulin An , Xueqi Zhao , Enrique del Castillo

We present a new method for statistical process control (SPC) of a discrete part manufacturing system based on intrinsic geometrical properties of the parts, estimated from three-dimensional sensor data. An intrinsic method has the…

Applications · Statistics 2020-07-13 Xueqi Zhao , Enrique del Castillo

To maintain the desired quality of a product or service it is necessary to monitor the process that results in the product or service. This monitoring method is called Statistical Process Management, or Statistical Process Control. It is in…

Methodology · Statistics 2019-01-15 W. J. Conover , Victor G. Tercero , Alvaro E. Cordero-Franco

We address the Statistical Process Control (SPC) of high-dimensional, dynamic industrial processes from two complementary perspectives: manifold fitting and manifold learning, both of which assume data lies on an underlying nonlinear, lower…

Machine Learning · Statistics 2025-09-25 Burak I. Tas , Enrique del Castillo

Del Castillo and Zhao (2020, 2021, 2022, 2024) have recently proposed a new methodology for the Statistical Process Control (SPC) of discrete parts whose 3-dimensional (3D) geometrical data are acquired with non-contact sensors. The…

Applications · Statistics 2025-10-20 Yulin An , Xueqi Zhao , Enrique del Castillo

In industrial settings, surface defects on steel can significantly compromise its service life and elevate potential safety risks. Traditional defect detection methods predominantly rely on manual inspection, which suffers from low…

Machine Learning · Computer Science 2025-04-25 Cheng Shen , Yuewei Liu

Because of the curse-of-dimensionality, high-dimensional processes present challenges to traditional multivariate statistical process monitoring (SPM) techniques. In addition, the unknown underlying distribution and complicated dependency…

Methodology · Statistics 2021-01-26 Zezhong Wang , Inez Maria Zwetsloot

Modern data collecting methods and computation tools have made it possible to monitor high-dimensional processes. In this article, Phase II monitoring of high-dimensional processes is investigated when the available number of samples…

Methodology · Statistics 2023-01-24 Mohsen Ebadi , Shojaeddin Chenouri , Stefan H. Steiner

With the development and popularity of sensors installed in manufacturing systems, complex data are collected during manufacturing processes, which brings challenges for traditional process control methods. This paper proposes a novel…

Machine Learning · Statistics 2024-02-01 Yanrong Li , Juan Du , Fugee Tsung , Wei Jiang

High dimensional data has introduced challenges that are difficult to address when attempting to implement classical approaches of statistical process control. This has made it a topic of interest for research due in recent years. However,…

Applications · Statistics 2019-04-23 Mohammad Nabhan , Yajun Mei , Jianjun Shi

The surface defect detection method based on visual perception has been widely used in industrial quality inspection. Because defect data are not easy to obtain and the annotation of a large number of defect data will waste a lot of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-14 Qifan Jin , Li Chen

Industrial defect detection is vital for upholding product quality across contemporary manufacturing systems. As the expectations for precision, automation, and scalability intensify, conventional inspection approaches are increasingly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Yuqi Cheng , Yunkang Cao , Haiming Yao , Wei Luo , Cheng Jiang , Hui Zhang , Weiming Shen

Modern sensing technologies have enabled the collection of unstructured point cloud data (PCD) of varying sizes, which are used to monitor the geometric accuracy of 3D objects. PCD are widely applied in advanced manufacturing processes,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Mariafrancesca Patalano , Giovanna Capizzi , Kamran Paynabar

For large-scale industrial processes under closed-loop control, process dynamics directly resulting from control action are typical characteristics and may show different behaviors between real faults and normal changes of operating…

Systems and Control · Computer Science 2018-09-11 Wenqing Li , Chunhui Zhao , Biao Huang

Additive manufacturing (AM) is an emerging digital manufacturing technology to produce complex and freeform objects through a layer-wise deposition. High deposition rate robotic AM (HDRRAM) processes, such as cold spray additive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Subash Gautam , Alejandro Vargas-Uscategui , Peter King , Hans Lohr , Alireza Bab-Hadiashar , Ivan Cole , Ehsan Asadi

Product metrics, such as size or complexity, are often used to identify defect-prone parts or to focus quality assurance activities. In contrast, quality information that is available early, such as information provided by inspections, is…

Software Engineering · Computer Science 2013-12-04 Frank Elberzhager , Stephan Kremer , Jürgen Münch , Danilo Assmann

From a process development perspective, diamond growth via chemical vapor deposition has made significant strides. However, challenges persist in achieving high quality and large-area material production. These difficulties include…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Rohan Reddy Mekala , Elias Garratt , Matthias Muehle , Arjun Srinivasan , Adam Porter , Mikael Lindvall

Software engineering is continuously facing the challenges of growing complexity of software packages and increased level of data on defects and drawbacks from software production process. This makes a clarion call for inventions and…

Software Engineering · Computer Science 2016-11-15 R. Selvarani , T. R. Gopalakrishnan Nair , V. Kamakshi Prasad

A well-known approach for identifying defect-prone parts of software in order to focus testing is to use different kinds of product metrics such as size or complexity. Although this approach has been evaluated in many contexts, the question…

Software Engineering · Computer Science 2014-02-05 Frank Elberzhager , Stephan Kremer , Jürgen Münch , Danilo Assmann

New production techniques have emerged that have made it possible to produce metal parts with more complex shapes, making the quality control process more difficult. This implies that the visual and superficial analysis has become even more…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Francisco Javier Yagüe , Jose Francisco Diez-Pastor , Pedro Latorre-Carmona , Cesar Ignacio Garcia Osorio
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