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Keywords = optimized sawing production line

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26 pages, 11722 KiB  
Article
Intelligent Automation Manufacturing for Betula Solid Timber Based on Machine Vision Detection and Optimization Grading System Applied to Building Materials
by Min Ji, Wei Zhang, Xingliang Diao, Guofu Wang and Hu Miao
Forests 2023, 14(7), 1510; https://doi.org/10.3390/f14071510 - 24 Jul 2023
Cited by 9 | Viewed by 3116
Abstract
Wood material is the foundation of wood structure architecture, and its production technology and equipment technology decide the development and upgrading of modern wood structure architecture. Aiming at the problems of low automation degree, low material utilization rate, low production efficiency and high [...] Read more.
Wood material is the foundation of wood structure architecture, and its production technology and equipment technology decide the development and upgrading of modern wood structure architecture. Aiming at the problems of low automation degree, low material utilization rate, low production efficiency and high labor costs in the process of traditional wood processing, we explore the integration and innovation of the traditional wood processing industry and modern industrial Internet information technology on the basis of studying the properties of Betula (Betula costata) solid wood materials, wood comprehensive utilization rate, wood structure component development and processing technology requirements, and form an intelligent, automatic and industrial production mode for building materials. Through technology and methods such as mechanical design, automation technology, machine vision, deep learning, optimization algorithm, electronic design automation, computer aided manufacturing, etc., the key technologies of intelligent automatic optimization of wood materials were studied, and intelligent automatic production lines of Betula species identification, log optimization sawing, solid timber longitudinal multiblade sawing, sawn timber quality detection and solid timber optimizing cross-cuts are built. Based on the machine vision method, features are extracted; a tree species, defect classification and recognition model database is established; an image processing algorithm with high recognition accuracy, as well as fast processing speed and high robustness are studied; non-destructive testing and classification methods of machine vision are optimized; key problems of online rapid classification, detection and optimization of sawing are solved and production quality and processing efficiency are improved. Finally, the timber defect detection accuracy and Betula timber yield are analyzed, and the comprehensive utilization value of optimized sawing timber is compared with the comprehensive utilization value of manually marking sawing timber. The processing cost and efficiency of Betula sawing timber with an intelligent automatic production line are calculated. The test results show that the average detection accuracy of timber defect type, size and location is 89.69%, 89.69%, 92.25% and 82.29%, respectively, and the detection stability is high. By adopting intelligent automatic detection, classification and optimization sawing production line of wood, the comprehensive utilization value of optimized sawing timber is 14.13% higher than that of manual marking sawing timber, and 16,089.29 m3 more building materials can be processed annually. In the process of intelligent automatic wood processing, the intelligent detection system is used to detect defects, improve production performance and production efficiency and reduce labor costs. Compared with the traditional wood processing process, the method studied in this paper is improved to optimize the production line processing performance and processing technology. The research and development of an intelligent automatic production system for solid wood can promote the application and development of an automatic industrial production mode for sawn timber for the wood structure construction industry, deepen the integration of artificial intelligence technology, Internet technology and the whole wood processing industry and lead the upgrading of building materials for wood structures to an intelligent manufacturing production mode. Full article
(This article belongs to the Section Wood Science and Forest Products)
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12 pages, 2435 KiB  
Article
Defect Removal and Rearrangement of Wood Board Based on Genetic Algorithm
by Yutu Yang, Zilong Zhuang and Yabin Yu
Forests 2022, 13(1), 26; https://doi.org/10.3390/f13010026 - 25 Dec 2021
Cited by 8 | Viewed by 3004
Abstract
Defects on a solid wood board have a great influence on the aesthetics and mechanical properties of the board. After removing the defects, the board is no longer the standard size; manual drawing lines and cutting procedure is time-consuming and laborious; and an [...] Read more.
Defects on a solid wood board have a great influence on the aesthetics and mechanical properties of the board. After removing the defects, the board is no longer the standard size; manual drawing lines and cutting procedure is time-consuming and laborious; and an optimal solution is not necessarily obtained. Intelligent cutting of the board can be realized using a genetic algorithm. However, the global optimal solution of the whole machining process cannot be obtained by separately considering the sawing and splicing of raw materials. The integrated consideration of wood board cutting and board splicing can improve the utilization rate of the solid wood board. The effective utilization rate of the board with isolated consideration of raw material sawing with standardized dimensions of wood pieces and board splicing is 79.1%, while the shortcut splicing optimization with non-standardized dimensions for the final board has a utilization rate of 88.6% (which improves the utilization rate by 9.5%). In large-scale planning, the use of shortcut splicing optimization also increased the utilization rate by 12.14%. This has certain guiding significance for actual production. Full article
(This article belongs to the Special Issue Wood Production and Promotion)
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