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 >

Haiming Sun^1,3, Quande Dong^2,*, Cuixia Zhang², Jianqing Chen^3,4

Energy Engineering, Vol.117, No.3, pp. 153-164, 2020, DOI:10.32604/EE.2020.010706 - 10 July 2020

Abstract The improvement of energy efficiency is considered as one of the keys to the sustainable development of manufacturing enterprises. This paper proposes an energy efficiency improvement method for the manufacturing process. Based on the analysis of the characteristics of energy consumption in the manufacturing process, a necessary energy consumption model, an assistant energy consumption model and an ineffective energy consumption model are constructed for identifying the energy consumption attributes of the manufacturing process. Then, the relationship model of energy consumption is built, and the energy efficiency improvement method for the manufacturing process is proposed based More >

N. S. B. Yusof^1,2, S. M. Sapuan^1,3,*, M. T. H. Sultan^1,4, M. Jawaid¹

Journal of Renewable Materials, Vol.8, No.6, pp. 647-660, 2020, DOI:10.32604/jrm.2020.08309 - 12 May 2020

Abstract In this study, the best manufacturing process will be selected to build an automotive crash box using green oil palm natural fibre-reinforced polyurethane composite materials. This paper introduces an approach consist of technical aspects (T), the economic point of view (E) and availability (A), and it’s also called as TEA requirement. This approach was developed with the goal of assisting the design engineer in the selection of the best manufacturing process during the design phase at the criteria selection stage. In this study, the TEA requirement will integrate with the analytical hierarchy process (AHP) to… More >