Geunil Lee¹, Daeil Kwon^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3329-3342, 2025, DOI:10.32604/cmes.2025.069402 - 30 September 2025

Abstract Nondestructive testing (NDT) methods such as visual inspection and ultrasonic testing are widely applied in manufacturing quality control, but they remain limited in their ability to detect defect characteristics. Visual inspection depends strongly on operator experience, while ultrasonic testing requires physical contact and stable coupling conditions that are difficult to maintain in production lines. These constraints become more pronounced when defect-related information is scarce or when background noise interferes with signal acquisition in manufacturing processes. This study presents a non-contact acoustic method for diagnosing defects in scroll compressors during the manufacturing process. The diagnostic approach… More >

Seungmin Lee¹, Beomseong Kim², Heesung Lee^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1397-1415, 2025, DOI:10.32604/cmc.2025.066152 - 09 June 2025

Abstract This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing their performance to identify the most effective architecture. Input images are preprocessed using a Gaussian Mixture Model (GMM) to remove… More >

Ting-Yu Lin¹, Kuo-Chen Hung^2,*, Josef Jablonsky³, Kuo-Ping Lin¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1901-1927, 2025, DOI:10.32604/cmc.2025.063543 - 16 April 2025

Abstract VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) has been developed and applied for over twenty-five years, gaining recognition as a prominent multi-criteria decision-making (MCDM) method. Over this period, numerous studies have explored its applications, conducted comparative analyses, integrated it with other methods, and proposed various modifications to enhance its performance. This paper aims to delve into the fundamental principles and objectives of VIKOR, which aim to maximize group utility and minimize individual regret simultaneously. However, this study identifies a significant limitation in the VIKOR methodology: its process amplifies the weight of individual regret, and the calculated… More >

Lu Liu¹, Bo Li^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012741

Abstract Powder-Bed Fusion (PBF) is a prominent metal additive manufacturing technology known for its adaptability and commercial viability. However, it is often hindered by defects such as voids, un-melted particles, microcracking, and columnar grains, which are generally more pronounced than those found in traditional manufacturing methods. Microcracking, in particular, poses a significant challenge, limiting the use of PBF materials in safety-critical applications across various industries. This study presents an advanced computational framework that effectively addresses the complex interactions of thermal, fluid dynamics, structural mechanics, crystallization, and fracture phenomena at meso and macroscopic levels. This framework has More >

Yuhong Zhao^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012951

Abstract For a long time, the phase-field method has been considered as a mesoscale phenomenological method lacking physical accuracy and unable to be associated with the mechanical/functional properties of materials, etc. Some misunderstandings existing in these viewpoints need to be clarified. Therefore, it is necessary to propose or adopt the perspective of “unified or unifying phase-field modeling (UPFM)” to address these issues, which means that phase-field modeling has multiple unifications. Specifically, the phase-field method is the perfect unity of thermodynamics and kinetics, the unity of multi-scale models from micro- to meso- and then to macroscopic scale, More >

Xin Xue^1,2,3, Haitao Li^1,2,3,*, Rodolfo Lorenzo⁴

Journal of Renewable Materials, Vol.12, No.4, pp. 869-894, 2024, DOI:10.32604/jrm.2024.029602 - 12 June 2024

Abstract This review summarizes the existing knowledge about the mechanical properties of bamboo scrimber (BS) in literature. According to literature reviews, the strength of BS under different load modes is affected by a series of factors, such as the type of original bamboo, growth position, resin content, treatment method and density. Therefore, different production processes can be adopted according to different requirements, and bamboo scrimbers can also be classified accordingly. In addition, this review summarizes the changes in different factors considered by scholars in the research on the mechanical properties of BS, so that readers can More > Graphic Abstract

Chao-Lung Yang^1,*, Atinkut Atinafu Yilma^1,2, Bereket Haile Woldegiorgis², Hendrik Tampubolon^3,4, Hendri Sutrisno⁵

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 233-254, 2024, DOI:10.32604/iasc.2024.043091 - 21 May 2024

Abstract This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations. Since real-time production process monitoring is critical in today’s smart manufacturing. The more robust the monitoring model, the more reliable a process is to be under control. In the past, many researchers have developed real-time monitoring methods to detect process shifts early. However, these methods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties. In this paper, a robust monitoring model combining Gated Recurrent Unit (GRU) and Random… More >

Muhammad Imran¹, Jinsheng Sun^1,*, Fatima Sehar Zaidi², Zameer Abbas^3,4, Hafiz Zafar Nazir⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1207-1257, 2023, DOI:10.32604/cmes.2023.025492 - 06 February 2023

Abstract Control charts (CCs) are one of the main tools in Statistical Process Control that have been widely adopted in manufacturing sectors as an effective strategy for malfunction detection throughout the previous decades. Measurement errors (M.E’s) are involved in the quality characteristic of interest, which can effect the CC’s performance. The authors explored the impact of a linear model with additive covariate M.E on the multivariate cumulative sum (CUSUM) CC for a specific kind of data known as compositional data (CoDa). The average run length is used to assess the performance of the proposed chart. The… More >

Jeonghoon Choi¹, Dongjun Suh^1,*, Marc-Oliver Otto²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2945-2966, 2023, DOI:10.32604/cmc.2023.033417 - 31 October 2022

Abstract Recently, machine learning-based technologies have been developed to automate the classification of wafer map defect patterns during semiconductor manufacturing. The existing approaches used in the wafer map pattern classification include directly learning the image through a convolution neural network and applying the ensemble method after extracting image features. This study aims to classify wafer map defects more effectively and derive robust algorithms even for datasets with insufficient defect patterns. First, the number of defects during the actual process may be limited. Therefore, insufficient data are generated using convolutional auto-encoder (CAE), and the expanded data are More >

Cuicui Wang¹, Xin Wei¹, Lee M. Smith², Ge Wang¹, Shuangbao Zhang³, Haitao Cheng^1,*

Journal of Renewable Materials, Vol.10, No.7, pp. 1829-1844, 2022, DOI:10.32604/jrm.2022.018782 - 07 March 2022

Abstract In order to investigate the effect of the relative motion of nano CaCO₃ reinforced bamboo pulp fiber (BPF)/HDPE composite components on the mechanical performance, a comparative study was performed. BPF was treated by nano CaCO₃ blending (BM) and impregnation modification (IM) technology. The composites were produced using hot press (HPMP), extrusion (EMP) and injection molding process (IMP). The physical morphology of BPF was similar at different manufacturing processes. Compared to the samples manufactured by HPMP, a decrease in the (specific) flexural strength of BPF/HDPE composites and an increase in those of composites treated by nano CaCO₃ manufactured More >