Special Issue "New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes: Volume II"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: 20 May 2020.

Special Issue Editors

Prof. Dr. Luis Norberto López de Lacalle
E-Mail Website
Guest Editor
Dr.-Ing. Jorge Posada
E-Mail Website
Guest Editor
Associate Director. Vicomtech Foundation, Basque Research and Technology Alliance (BRTA). 20014 Donostia-San Sebastian, Spain
Tel. +34 943 30 92 30
Interests: Industry 4.0, industrie 4.0, virtual reality, rapid prototyping, 3d, visual computing, knowledge engineering, semantics, human computer interaction, HCI, visualization, visual analytics, virtual engineering, data analytics
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Special Issue Information

Dear Colleagues,

Over the last three years, industrial factories have been experiencing a rapid digital transformation because of the introduction of emerging ICT technologies, such as the industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, artificial intelligence, intelligent robotics, cyber-physical systems, digital twins, and visual computing (including augmented reality, visual analytics, cognitive computer vision, new HMI interfaces, and simulation and computer graphics), among others. This is evident in the global trend of Industry 4.0 and related initiatives, which are present in one way or another in many different production strategies at an international level (Industrie 4.0, Germany; industrial Internet, USA; Industrie du Futur, France; made in China 2025, China; etc.).

In the context of high performance manufacturing, the impact of these technologies is clear. Important improvements can be achieved in the productivity, systems reliability, parts quality, and human welfare.

Both classical and new manufacturing processes (such as additive manufacturing), based on advanced mecahnical principles, are being enhanced by the use of big data analytics on industrial sensor data. In the current machine tools and systems, there are complex sensors that are able to gather useful information, which can be captured, stored, and processed with edge, fog or cloud computing technologies. Manufacturing processes modeling can lead to improvements in productivity and quality and, in several cases, are implemented by means of digital twins on cyber-physical production devices and systems.

In this line, manufacturing process models (e.g., thermal, vibration, deformation) can be improved with digital monitoring, digital twins, visual data analytics, artificial intelligence, and computer vision in order to achieve a more productive and reliable smart factory.

On the other hand, the role of the human factor is absolutely fundamental in these new paradigms. Collaborative robots are spreading in several applications in order to work along with human skilful workers. New approaches for augmented reality and immersive virtual reality, as well as other multimodal ways of improving human computer interaction in manufacturing scenarios, are enhancing the capabilities of operators and engineers so as to capture and reproduce human knowledge, improve their performance in operational tasks, and seamlessly integrate their valuable experience and flexibility in smart factory scenarios for manufacturing. Visual analytics can help in decision-making by management, domain experts, operators, engineers, and so on, by providing user-specific interactive visualization and the exploration of operational data in combination with machine learning approaches.

In summary, this Special Issue is an opportunity for the scientific community to present recent research regarding industrial IoT and visual computing as key aspects of Industry 4.0 for manufacturing processes.

Prof. Dr. Luis López de Lacalle
Dr.-Ing. Jorge Posada
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Advanced manufacturing
  • Industry 4.0
  • Smart factories
  • Visual computing
  • Industrial Internet of things
  • Cyber physical systems, and cyber-physical production systems
  • Digital twins
  • Edge, fog, and cloud computing
  • Augmented reality
  • 5G in manufacturing
  • Deep analytics
  • Industrial big data
  • Workshop networks
  • High performance manufacturing
  • Manufacturing processes
  • Machine and processes monitoring
  • Knowledge-based manufacturing
  • Advances in manufacturing processes
  • Process modeling, process simulation
  • Virtual manufacturing
  • Artificial vision
  • Virtual reality
  • Collaborative robots
  • Management in new digitally powered manufacturing concepts

Published Papers (6 papers)

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Research

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Open AccessArticle
Predictive Maintenance on the Machining Process and Machine Tool
Appl. Sci. 2020, 10(1), 224; https://doi.org/10.3390/app10010224 - 27 Dec 2019
Abstract
This paper presents the process required to implement a data driven Predictive Maintenance (PdM) not only in the machine decision making, but also in data acquisition and processing. A short review of the different approaches and techniques in maintenance is given. The main [...] Read more.
This paper presents the process required to implement a data driven Predictive Maintenance (PdM) not only in the machine decision making, but also in data acquisition and processing. A short review of the different approaches and techniques in maintenance is given. The main contribution of this paper is a solution for the predictive maintenance problem in a real machining process. Several steps are needed to reach the solution, which are carefully explained. The obtained results show that the Preventive Maintenance (PM), which was carried out in a real machining process, could be changed into a PdM approach. A decision making application was developed to provide a visual analysis of the Remaining Useful Life (RUL) of the machining tool. This work is a proof of concept of the methodology presented in one process, but replicable for most of the process for serial productions of pieces. Full article
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Open AccessArticle
Knowledge Absorption Capacity as a Factor for Increasing Logistics 4.0 Maturity
Appl. Sci. 2019, 9(24), 5365; https://doi.org/10.3390/app9245365 - 09 Dec 2019
Abstract
This research strives to show the importance of knowledge absorptive capacity as one of the most important determinants of successful implementation of contemporary solutions and, consequently, development of a company. In the approach presented, the development leads to excellence and is expressed with [...] Read more.
This research strives to show the importance of knowledge absorptive capacity as one of the most important determinants of successful implementation of contemporary solutions and, consequently, development of a company. In the approach presented, the development leads to excellence and is expressed with subsequent maturity levels. The research is focused on identification of the level of absorption of knowledge of contemporary solutions in logistics, grouped in a concept of Logistics 4.0, and how that upgrades the organizational maturity of a company. The research was conducted with CAWI (Computer-Assisted Web Interview), including three questions and a basic query on experts’ qualifications. The general conclusion from the research was that to reach a higher level of maturity, a higher level of knowledge absorption is required. However, searching for differences in absorption of solutions within physical flows, information flows and managerial methods seem to be an interesting issue and promising field for further research. Full article
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Open AccessArticle
Human-Machine Interaction: Adapted Safety Assistance in Mentality Using Hidden Markov Chain and Petri Net
Appl. Sci. 2019, 9(23), 5066; https://doi.org/10.3390/app9235066 - 24 Nov 2019
Abstract
This study proposes a cognition-adaptive approach for the administrative control of human-machine safety interaction through Internet of Things (IoT) data. As part of Industry 4.0, a human operator possesses various characteristics, but cannot be consistently understood as well as a machine. Thus, human-machine [...] Read more.
This study proposes a cognition-adaptive approach for the administrative control of human-machine safety interaction through Internet of Things (IoT) data. As part of Industry 4.0, a human operator possesses various characteristics, but cannot be consistently understood as well as a machine. Thus, human-machine interaction plays an important role. This study focuses on incumbent challenges on the basis of estimated mental states. Given the operation logs from data recording hardware, a Hidden Markov model on top of a human cognitive model was trained to capture a production line worker’s sequential faults. Our study found that retaining workers’ attention is insufficient and tracking the state of perception is key to accomplishing production tasks. A safe workflow policy requires attention and perception. Accordingly, our proposed Petri Net enhances operation safety and improves production efficiency. Full article
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Open AccessArticle
Flexible Framework to Model Industry 4.0 Processes for Virtual Simulators
Appl. Sci. 2019, 9(23), 4983; https://doi.org/10.3390/app9234983 - 20 Nov 2019
Abstract
Virtual reality (VR)- and augmented reality (AR)-based simulations are key technologies in Industry 4.0 which allow for testing and studying of new processes before their deployment. A simulator of industrial processes needs a flexible way in which to model the activities performed by [...] Read more.
Virtual reality (VR)- and augmented reality (AR)-based simulations are key technologies in Industry 4.0 which allow for testing and studying of new processes before their deployment. A simulator of industrial processes needs a flexible way in which to model the activities performed by the worker and other elements involved, such as robots and machinery. This work proposes a framework to model industrial processes for VR and AR simulators. The desk method was used to review previous research and extract the most important features of current approaches. Novel features include interaction among human workers and a variety of automation systems, such as collaborative robots, a broader set of tasks (including assembly and disassembly of components), flexibility of modeling industrial processes for different domains and purposes, a clear separation of process definition and simulator, and independence of specific programming languages or technologies. Three industrial scenarios modeled with this framework are presented: an aircraft assembly scenario, a guidance tool for high-voltage cell security, and an application for the training of machine-tool usage. Full article
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Open AccessArticle
Ant Colony Optimization Algorithm for Maintenance, Repair and Overhaul Scheduling Optimization in the Context of Industrie 4.0
Appl. Sci. 2019, 9(22), 4815; https://doi.org/10.3390/app9224815 - 11 Nov 2019
Abstract
Maintenance, Repair, and Overhaul (MRO) is a crucial sector in the remanufacturing industry and scheduling of MRO processes is significantly different from conventional manufacturing processes. In this study, we adopted a swarm intelligent algorithm, Ant Colony Optimization (ACO), to solve the scheduling optimization [...] Read more.
Maintenance, Repair, and Overhaul (MRO) is a crucial sector in the remanufacturing industry and scheduling of MRO processes is significantly different from conventional manufacturing processes. In this study, we adopted a swarm intelligent algorithm, Ant Colony Optimization (ACO), to solve the scheduling optimization of MRO processes with two business objectives: minimizing the total scheduling time (make-span) and total tardiness of all jobs. The algorithm also has the dynamic scheduling capability which can help the scheduler to cope with the changes in the shop floor which frequently occur in the MRO processes. Results from the developed algorithm have shown its better solution in comparison to commercial scheduling software. The dependency of the algorithm’s performance on tuning parameters has been investigated and an approach to shorten the convergence time of the algorithm is emerging. Full article
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Review

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Open AccessReview
A Review of Industry 4.0 Manufacturing Process Security Risks
Appl. Sci. 2019, 9(23), 5105; https://doi.org/10.3390/app9235105 - 26 Nov 2019
Cited by 1
Abstract
The advent of three-dimensional (3D) printing has found a unique and prominent role in Industry 4.0 and is rapidly gaining popularity in the manufacturing industry. 3D printing offers many advantages over conventional manufacturing methods, making it an attractive alternative that is more cost-effective [...] Read more.
The advent of three-dimensional (3D) printing has found a unique and prominent role in Industry 4.0 and is rapidly gaining popularity in the manufacturing industry. 3D printing offers many advantages over conventional manufacturing methods, making it an attractive alternative that is more cost-effective and efficient than conventional manufacturing methods. With the Internet of Things (IoT) at the heart of this new movement, control over manufacturing methods now enters the cyber domain, offering endless possibilities in manufacturing automation and optimization. However, as disruptive and innovative as this may seem, there is grave concern about the cyber-security risks involved. These security aspects are often overlooked, particularly by promising new start-ups and parties that are not too familiar with the risks involved in not having proper cyber-security measures in place. This paper explores some of the cyber-security risks involved in the bridge between industrial manufacturing and Industry 4.0, as well as the associated countermeasures already deployed or currently under development. These aspects are then contextualized in terms of Industry 4.0 in order to serve as a basis for and assist with future development in this field. Full article
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