查看更多>>摘要：? 2022 Elsevier B.V.This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief as the reliability of the peer-review process of the article cannot be guaranteed. It was discovered post publication that the Managing Guest Editor of the Special Issue, M. Abdel-Baset, was also an author of the article: the version of the paper which was accepted by the handling Editor used the author name 'M. Metwalli', but the corresponding author was subsequently changed to “M. Abdel-Baset”. As such this represents an abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.
查看更多>>摘要：? 2022 Elsevier B.V.This article has been retracted: Please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief as the reliability of the peer-review process of the article cannot be guaranteed. It was discovered post publication that the Managing Guest Editor of the Special Issue, M. Abdel-Baset, was also an author of the article: the version of the paper which was accepted by the handling Editor used the author name 'M. Metwalli', but the corresponding author was subsequently changed to “M. Abdel-Baset”. As such this represents an abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.
查看更多>>摘要：? 2022 Elsevier B.V.Thanks to the advances in the Internet of Things (IoT), Condition-based Maintenance (CBM) has progressively become one of the most renowned strategies to mitigate the risk arising from failures. Within any CBM framework, non-linear correlation among data and variability of condition monitoring data sources are among the main reasons that lead to a complex estimation of Reliability Indicators (RIs). Indeed, most classic approaches fail to fully consider these aspects. This work presents a novel methodology that employs Accelerated Life Testing (ALT) as multiple sources of data to define the impact of relevant PVs on RIs, and subsequently, plan maintenance actions through an online reliability estimation. For this purpose, a Generalized Linear Model (GLM) is exploited to model the relationship between PVs and an RI, while a Hierarchical Bayesian Regression (HBR) is implemented to estimate the parameters of the GLM. The HBR can deal with the aforementioned uncertainties, allowing to get a better explanation of the correlation of PVs. We considered a numerical example that exploits five distinct operating conditions for ALT as a case study. The developed methodology provides asset managers a solid tool to estimate online reliability and plan maintenance actions as soon as a given condition is reached.
查看更多>>摘要：? 2022 Elsevier B.V.Hazard and operability analysis (HAZOP) is a remarkable representative in industrial safety engineering. However, a great storehouse of industrial safety knowledge (ISK) in HAZOP reports has not been thoroughly exploited. In order to reuse and unlock the value of ISK and optimize HAZOP, we have developed a novel knowledge graph for industrial safety (ISKG) with HAZOP as the carrier through bridging data science and engineering design. Specifically, firstly, considering that the knowledge contained in HAZOP reports of different processes in industry is not the same, we creatively developed a general ISK standardization framework, it provides a practical scheme for integrating HAZOP reports from various processes and uniformly representing the ISK with diverse expressions. Secondly, we conceive a novel and reliable information extraction model based on deep learning combined with data science, it can effectively mine ISK from HAZOP reports, which alleviates the obstacle of ISK extraction caused by the particularity of HAZOP text. Finally, we build ISK triples and store them in the Neo4j graph database. We take indirect coal liquefaction process as a case study to develop ISKG, and its oriented applications can optimize HAZOP and mine the potential of ISK, which is of great significance to improve the security of the system and enhance prevention awareness for people. ISKG containing the ISK standardization framework and the information extraction model sets an example of the interaction between data science and engineering design, which can enlighten other researchers and extend the perspectives of industrial safety.
查看更多>>摘要：? 2022 The Author(s)A library of prefabricated parts and assemblies, i.e. module library, can help a firm in the construction industry transition to a more industrialized and product-oriented approach. However, existing approaches to manage such libraries are oriented around single-use projects. There is need for a more flexible data structure to support storage, analysis and reuse of design information. This paper proposes a graph-based approach to develop a module library. The approach includes a graph representation of modules, a graph database development, and a graph-based similarity analysis. The proposed approach is validated using a prefabricated timber panel system via a web-based application. Implementation demonstrates a more efficient process for bill of material generation and identifying the impacts of design changes.
查看更多>>摘要：? 2022 Elsevier B.V.Recent advances in augmented reality (AR) and artificial intelligence have caused these technologies to pioneer innovation and alteration in any field and industry. The fast-paced developments in computer vision (CV) and augmented reality facilitated analyzing and understanding the surrounding environments. This paper systematically reviews and presents studies that integrated augmented/mixed reality and deep learning for object detection over the past decade. Five sources including Scopus, Web of Science, IEEE Xplore, ScienceDirect, and ACM were used to collect data. Finally, a total of sixty-nine papers were analyzed from two perspectives: (1) application analysis of deep learning-based object detection in the context of augmented reality and (2) analyzing the use of servers or local AR devices to perform the object detection computations to understand the relation between object detection algorithms and AR technology. Furthermore, the advantages of using deep learning-based object detection to solve the AR problems and limitations hindering the ultimate use of this technology are critically discussed. Our findings affirm the promising future of integrating AR and CV.
查看更多>>摘要：? 2022 The Author(s)Visual inspection is one of the most ubiquitous forms of non-destructive testing, being widely used in routine pipe inspections. For small bore pipes (centimetre diameter), inspectors often have a restricted field of view limiting overall image and inspection quality. Stitching multiple unwrapped images is a common inspection technique to provide a full view inspection image by combining multiple video frames together. A key challenge of this method is knowing the camera pose of each frame. Consequently, mechanical centralisers are often utilised to ensure the camera is located centrally. For the inspection of small-bore pipes, such mechanical centralisers are often too large to fit. This paper presents a post-processing, Structure-from-Motion (SfM) based approach to unwrap and stitch inspection images, captured by a manually deployed commercial videoscope. It advances state-of-the-art approaches which rely on the projection of a laser pattern into the field of view, thus reducing the equipment size. The process consists of camera pose estimation, preliminary point cloud generation, secondary fitting, images unwrapping and stitching to form an undistorted view of the pipe interior. Two industrial focussed demonstrators verified the successful implementation for small-bore pipe inspections. Whereby the new approach does not rely on image features to create the surface texture and is less sensitive to the image quality, more areas can be retrieved from inspections. The reconstructed area was increased by up to 87% using the new approach versus the conventional 3D model.
查看更多>>摘要：? 2022 Elsevier B.V.As the manufacturing sector enters the Industry 4.0 era, a higher level cooperative system must be established between manufacturers. Therefore, seamless sharing of information is required between companies, for instance, between an original equipment manufacturer and a parts manufacturer. However, books in PDF or image format that cannot be modified are still commonly used in the field to convey information. Moreover, locating the necessary information in documents, drafted based on unstructured data, is challenging. To overcome these drawbacks, this study proposes an end-to-end digitalization method to convert an image format catalog book into structured digital part specifications. The proposed method also defines a neutral reference data dictionary to ensure consistent digitalization to facilitate data interoperability, classifying catalog pages per part and identifying part numbers, detecting specification tables and recognizing texts in a table, and building part objects and their property objects from the texts extracted from the table. To validate our method, we conducted an experiment where catalog books for motor parts were digitalized. The experiment results exhibited excellent accuracy performance with 96.97% and 90.59%, in part object and property object conversion, respectively, when considering specifications.
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