Showing papers in "Computers in Industry in 2022"

TL;DR: In this paper , the authors review contemporary advances in Zero Defect Manufacturing using structured literature review and highlight two specific zero defect manufacturing strategy types: defect prevention, and defect compensation; as well as identify two important themes for future ZDM research, namely advancing zero-defect processes to zero-waste value chain strategies and overcoming the global application challenges of ZDM.

TL;DR: In this article , a systematic literature review of the state of the art deals with cybersecurity awareness in the context of Industrial Internet of Things (IIoT), and provides a comprehensive overview of this topic.

TL;DR: In this paper , a generic data-driven framework for automated generation of simulation models as basis for digital twins for smart factories is proposed, which exploits advancements in machine learning and process mining techniques, as well as continuous model improvement and validation.

TL;DR: In this paper, the authors organize the existing studies on DTs with a focus on barriers and enablers, and propose conceptual models describing enabler of and barrier to DT implementation, as well as their mutual relationships.

TL;DR: In this paper , a model connecting barriers and enablers for implementing digital twins is introduced, and challenges to digital twin implementation are identified and categorized, as well as their mutual relationships.

TL;DR: In this paper , a digital twin-enabled smart modular integrated construction system (DT-SMiCS) with a robotic demonstration for reengineered on-site assembly is presented, where onsite resources are converted into Smart MiC Objects (SMiCOs) attaching with UWB and RFID devices to collect and integrate real-time nD data, such as identity, location, cost and construction progress.

TL;DR: Wang et al. as discussed by the authors developed a blockchain-enabled IoT-BIM platform (BIBP) for off-site production management in modular construction (OPM-MC) that can overcome the shortcomings.

TL;DR: Wang et al. as mentioned in this paper developed a blockchain-enabled IoT-BIM platform (BIBP) for off-site production management in modular construction (OPM-MC) that can overcome the shortcomings.

TL;DR: In this article , the authors improved the Faster Region-based Convolutional Neural Network (Faster R-CNN) model by embedding Gabor kernels into the network, which is termed the Genetic Algorithm Gabor Faster-R-CNN.

TL;DR: In this article, the authors improved the Faster Region-based Convolutional Neural Network (Faster R-CNN) model by embedding Gabor kernels into the network, which is termed the Genetic Algorithm Gabor Faster-R-CNN.

TL;DR: In this paper , the authors present an end-to-end platform for collecting, managing, and routing data streams from heterogeneous cyber physical production systems, in configurable and interoperable ways.

TL;DR: Wang et al. as discussed by the authors proposed a novel and lightweight detection method based on attention mechanism, and focused on the industrial application of aluminum strip defect inspection, which is trained and tested on the straightening aluminum strip surface data collected from the cold rolling workshop of Liuzhou Yinhai Aluminum Co., Ltd.

TL;DR: In this paper , the authors systematically reviewed and presented studies that integrated augmented/mixed reality and deep learning for object detection over the past decade, and a total of sixtynine 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.

TL;DR: In this article , a survey of smart farming big data applications is presented, which highlights various types of big data generated through smart farming and makes a broad categorization of such data and identifies the principal big data and machine learning techniques that are utilized in smart farming data analysis.

TL;DR: In this paper , a blockchain-based Digital Twins (DT) framework for Cyber-Physical Systems (TTS-CPS) is proposed to provide actionable insights through monitoring, simulating, predicting, and optimizing the state of CPSs.

TL;DR: In this paper , the authors present an integrated review combining quantitative and qualitative analyses to clarify the development roadmap of BIM-enabled building automation and robotics, and propose a new unified robot-oriented BIM framework, namely BIMfAR, to provide guidelines for future applications.

TL;DR: In this article , the authors present the architectural design and implementation of DIGICOR, a collaborative Industry 4.0 (I4.0) platform aimed at enabling SMEs to dynamically form supply-chain collaborations so as to pool production capacities and capabilities and jointly address complex supply chain requests.

TL;DR: In this paper, the authors provide a literature overview of the current trends in the zero-defect manufacturing (ZDM) field from 2018 to 2020, by analyzing the related most significant works, thus providing a single-strategy analysis and corresponding most frequently used methods.

TL;DR: Wang et al. as mentioned in this paper designed a new window shift scheme that further strengthened the feature transfer between windows and made the framework more capable of serving as a backbone for defect detection, and they also verified the superiority of transfer learning in training small-scale datasets.

TL;DR: In this article , the authors provide a literature overview of the current trends in the zero-defect manufacturing (ZDM) field from 2018 to 2020, by analyzing the related most significant works, thus providing a single-strategy analysis and corresponding most frequently used methods.

TL;DR: In this paper , the authors propose an analysis framework that enables the characteristics of all digital twins to be matched to this framework, using this framework a digital twin may be characterised, or two or more digital twins may be compared.

TL;DR: In this paper , the authors proposed a structured threat modeling approach for ICPS that enables prediction and analysis of cyber risks to protect industrial assets from potential cyber-attacks, and the proposed methodology enables end-to-end threat modelling through the development of a new framework that is integrated with VueOne digital twin tool to model and analyse threats throughout ICPS lifecycle.

TL;DR: In this paper , the authors present a digital twin hierarchy for metal additive manufacturing (AM) based on surrogate modeling, in-situ sensing, hardware control systems and intelligent control policies.

TL;DR: In this paper , a structured review of the literature and an analysis of 19 expert interviews is used to identify 32 Critical Success Factors (CSF) for RPA and subsume them into several contextual clusters.

TL;DR: A systematic literature review of the main applications of Industry 4.0 technologies in the wood sector, from forest management and raw materials production to the manufacturing of finished wood and paper products is presented in this article .

TL;DR: In this paper , a model-based approach including digital twinning is applied to bridge the gap with respect to data integration between the manufacturing and the usage of products and services, and how data can be integrated along the product & service life cycle.

TL;DR: In this article , a systematic literature review combined with a mapping study reveals how only a minimal part of the existing literature is able to demonstrate how real-time physicalto-virtual and virtual-to-physical connections can be used to improve the design of servitized solutions.

TL;DR: In this paper , a systematic review of 60 representative studies enabled the definition of the operational scenario that comprises 4 dimensions of data and 10 classes of data within these dimensions to generically identify what kind of data is being collected.

TL;DR: In this article , a generalized rule interpretation framework was proposed to parse regulatory text like a domain-specific language, and a set of context-free grammar (CFG) was built to parse a labeled sentence into the language-independent tree structure, from which computable checking rules can be generated.

TL;DR: In this article , a novel prototypical network is presented for improving the fabric defect classification performance, especially in the case of an imbalanced distribution over the number of class samples, where the training set is split into a support set and query set, and the loss function is designed to match them with the corresponding prototypes as accurately as possible.