Computer Vision Techniques in Manufacturing

被引:36
|
作者
Zhou, Longfei [1 ]
Zhang, Lin [2 ]
Konz, Nicholas [3 ]
机构
[1] MIT, Comp Sci & Artificial Intelligence Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[2] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[3] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA
基金
中国国家自然科学基金;
关键词
Image edge detection; Image segmentation; Task analysis; Robot sensing systems; Sensors; Feature detection; Three-dimensional displays; Assembly; computer vision (CV); deep learning; inspection; machine intelligence; machine learning; manufacturing; production; robotics; survey; MACHINE-VISION; SYSTEM; INSPECTION; DESIGN; RECOGNITION; ALIGNMENT; CLASSIFICATION; IDENTIFICATION; SEGMENTATION; SERVICES;
D O I
10.1109/TSMC.2022.3166397
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Computer vision (CV) techniques have played an important role in promoting the informatization, digitization, and intelligence of industrial manufacturing systems. Considering the rapid development of CV techniques, we present a comprehensive review of the state of the art of these techniques and their applications in manufacturing industries. We survey the most common methods, including feature detection, recognition, segmentation, and three-dimensional modeling. A system framework of CV in the manufacturing environment is proposed, consisting of a lighting module, a manufacturing system, a sensing module, CV algorithms, a decision-making module, and an actuator. Applications of CV to different stages of the entire product life cycle are then explored, including product design, modeling and simulation, planning and scheduling, the production process, inspection and quality control, assembly, transportation, and disassembly. Challenges include algorithm implementation, data preprocessing, data labeling, and benchmarks. Future directions include building benchmarks, developing methods for nonannotated data processing, developing effective data preprocessing mechanisms, customizing CV models, and opportunities aroused by 5G.
引用
收藏
页码:105 / 117
页数:13
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