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Authors = Mohammed Asmael

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42 pages, 4632 KiB  
Review
Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0
by Zeki Murat Çınar, Abubakar Abdussalam Nuhu, Qasim Zeeshan, Orhan Korhan, Mohammed Asmael and Babak Safaei
Sustainability 2020, 12(19), 8211; https://doi.org/10.3390/su12198211 - 5 Oct 2020
Cited by 564 | Viewed by 69099
Abstract
Recently, with the emergence of Industry 4.0 (I4.0), smart systems, machine learning (ML) within artificial intelligence (AI), predictive maintenance (PdM) approaches have been extensively applied in industries for handling the health status of industrial equipment. Due to digital transformation towards I4.0, information techniques, [...] Read more.
Recently, with the emergence of Industry 4.0 (I4.0), smart systems, machine learning (ML) within artificial intelligence (AI), predictive maintenance (PdM) approaches have been extensively applied in industries for handling the health status of industrial equipment. Due to digital transformation towards I4.0, information techniques, computerized control, and communication networks, it is possible to collect massive amounts of operational and processes conditions data generated form several pieces of equipment and harvest data for making an automated fault detection and diagnosis with the aim to minimize downtime and increase utilization rate of the components and increase their remaining useful lives. PdM is inevitable for sustainable smart manufacturing in I4.0. Machine learning (ML) techniques have emerged as a promising tool in PdM applications for smart manufacturing in I4.0, thus it has increased attraction of authors during recent years. This paper aims to provide a comprehensive review of the recent advancements of ML techniques widely applied to PdM for smart manufacturing in I4.0 by classifying the research according to the ML algorithms, ML category, machinery, and equipment used, device used in data acquisition, classification of data, size and type, and highlight the key contributions of the researchers, and thus offers guidelines and foundation for further research. Full article
(This article belongs to the Special Issue Machine Learning and AI Technology for Sustainability)
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25 pages, 5240 KiB  
Review
Recent Developments in Luffa Natural Fiber Composites: Review
by Mohamad Alhijazi, Babak Safaei, Qasim Zeeshan, Mohammed Asmael, Arameh Eyvazian and Zhaoye Qin
Sustainability 2020, 12(18), 7683; https://doi.org/10.3390/su12187683 - 17 Sep 2020
Cited by 119 | Viewed by 17207
Abstract
Natural fiber composites (NFCs) are an evolving area in polymer sciences. Fibers extracted from natural sources hold a wide set of advantages such as negligible cost, significant mechanical characteristics, low density, high strength-to-weight ratio, environmental friendliness, recyclability, etc. Luffa cylindrica, also termed [...] Read more.
Natural fiber composites (NFCs) are an evolving area in polymer sciences. Fibers extracted from natural sources hold a wide set of advantages such as negligible cost, significant mechanical characteristics, low density, high strength-to-weight ratio, environmental friendliness, recyclability, etc. Luffa cylindrica, also termed luffa gourd or luffa sponge, is a natural fiber that has a solid potential to replace synthetic fibers in composite materials in diverse applications like vibration isolation, sound absorption, packaging, etc. Recently, many researches have involved luffa fibers as a reinforcement in the development of NFC, aiming to investigate their performance in selected matrices as well as the behavior of the end NFC. This paper presents a review on recent developments in luffa natural fiber composites. Physical, morphological, mechanical, thermal, electrical, and acoustic properties of luffa NFCs are investigated, categorized, and compared, taking into consideration selected matrices as well as the size, volume fraction, and treatments of fibers. Although luffa natural fiber composites have revealed promising properties, the addition of these natural fibers increases water absorption. Moreover, chemical treatments with different agents such as sodium hydroxide (NaOH) and benzoyl can remarkably enhance the surface area of luffa fibers, remove undesirable impurities, and reduce water uptake, thereby improving their overall characteristics. Hybridization of luffa NFC with other natural or synthetic fibers, e.g., glass, carbon, ceramic, flax, jute, etc., can enhance the properties of the end composite material. However, luffa fibers have exhibited a profuse compatibility with epoxy matrix. Full article
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11 pages, 5486 KiB  
Article
Development of a TiC/Cr23C6 Composite Coating on a 304 Stainless Steel Substrate through a Tungsten Inert Gas Process
by Behzad Heidarshenas, Ghulam Hussain and Mohammed. Bsher. A. Asmael
Coatings 2017, 7(6), 80; https://doi.org/10.3390/coatings7060080 - 14 Jun 2017
Cited by 18 | Viewed by 6843
Abstract
The aim of this study was to develop a composite coating on 304 stainless steel employing a TIG (tungsten inert gas) process. Ti wire cored with graphite powder was used as the means of coating material. The process parameters were controlled to develop [...] Read more.
The aim of this study was to develop a composite coating on 304 stainless steel employing a TIG (tungsten inert gas) process. Ti wire cored with graphite powder was used as the means of coating material. The process parameters were controlled to develop a coating with optimum characteristics (i.e., hardness and wear resistance). The microstructure of the coating was analyzed with SEM and XRD. It was found that both the hardness and the wear resistance increase as the current increases, while both of these properties decrease as travelling speed increases. It was found that the coated samples with composite layers were harder than the substrate and can range up to 1100 HV, almost 4.5 times higher than the hardness of 304 stainless steel. Likewise, the wear resistance of the coating was observed to be 4.5 times higher than that of the substrate. The high performance of the coating, as revealed by microstructural analysis, was due to the formation of TiC and Cr23C6.The optimum conditions for producing the coating are thus proposed to include a 120 A current and a 3.17 mm/s travel speed. Full article
(This article belongs to the Special Issue Advanced Ceramic Coatings and Interfaces)
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