scholarly journals Immersive Technology for Human-Centric Cyberphysical Systems in Complex Manufacturing Processes: A Comprehensive Overview of the Global Patent Profile Using Collective Intelligence

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Usharani Hareesh Govindarajan ◽  
Amy J. C. Trappey ◽  
Charles V. Trappey
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Latent Dirichlet Allocation ◽  
Industrial Revolution ◽  
Smart Manufacturing ◽  
Manufacturing Processes ◽  
Cyberphysical Systems ◽  
Comprehensive Overview ◽  
Immersive Technology ◽  
Immersive Technologies

Immersive technology for human-centric cyberphysical systems includes broad concepts that enable users in the physical world to connect with the cyberworld with a sense of immersion. Complex systems such as virtual reality, augmented reality, brain-computer interfaces, and brain-machine interfaces are emerging as immersive technologies that have the potential for improving manufacturing systems. Industry 4.0 includes all technologies, standards, and frameworks for the fourth industrial revolution to facilitate intelligent manufacturing. Industrial immersive technologies will be used for smart manufacturing innovation in the context of Industry 4.0’s human machine interfaces. This research provides a thorough review of the literature, construction of a domain ontology, presentation of patent metatrend statistical analysis, and data mining analysis using a technology function matrix and highlights technical and functional development trends using latent Dirichlet allocation (LDA) models. A total of 179 references from the IEEE and IET databases and 2,672 patents are systematically analyzed to identify current trends. The paper establishes an essential foundation for the development of advanced human-centric cyberphysical systems in complex manufacturing processes.

The Application of the Positive Semi-Definite Kernel Space for SVM in Quality Prediction

2020 ◽  
Vol 13 (2) ◽  
pp. 228-233
Author(s):  
Wang Meng ◽  
Dui Hongyan ◽  
Zhou Shiyuan ◽  
Dong Zhankui ◽  
Wu Zige
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Feature Space ◽  
Mixed Data ◽  
Smart Manufacturing ◽  
Additive Constant ◽  
Kernel Space ◽  
Data Set ◽  
Low Dimensional

Background: A transformation toward 4th Generation Industrial Revolution (Industry 4.0) is being led by Germany based on Cyber-Physical System-enabled manufacturing and service innovation. Smart manufacturing is an important feature of Industry 4.0 which uses the networked manufacturing systems for smart production. Current manufacturing systems (5M1E systems) require deeper mining of the data which is generated from manufacturing process. Objective: To map low-dimensional embedding into the input space would meet the requirement of “kernel trick” to solve a problem in feature space. On the other hand, the distance can be calculated more precisely. Methods: In this research, we proposed a positive semi-definite kernel space by using a constant additive method based on a kernel view of ISOMAP. There were 6 steps in the algorithm. Results: The classification precision of KMLSVM was better than SVM in the enterprise data set, in which SVM selected the RBF kernel and optimized its parameters. Conclusion: We adopted the additive constant method in kernel space construction and the positive semi-definite kernel was built. The typical mixed data set of an enterprise was used in simulation. We compared the SVM and KMLSVM in this data set and optimized the SVM kernel function parameters. The simulation results demonstrated the KMLSVM was a better algorithm in mix type data set than SVM.

scholarly journals Systematic analysis of needs and requirements for the design of smart manufacturing systems in SMEs☆

2020 ◽  
Vol 7 (2) ◽  
pp. 129-144 ◽  
Author(s):  
Erwin Rauch ◽  
Andrew R Vickery
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Smart Manufacturing ◽  
Functional Requirements ◽  
Systematic Analysis ◽  
Fourth Industrial Revolution ◽  
Increasing Trend ◽  
Scientific Approach ◽  
Smart Manufacturing Systems

Abstract With the increasing trend of the Fourth Industrial Revolution, also known as Industry 4.0 or smart manufacturing, many companies are now facing the challenge of implementing Industry 4.0 methods and technologies. This is a challenge especially for small and medium-sized enterprises, as they have neither sufficient human nor financial resources to deal with the topic sufficiently. However, since small and medium-sized enterprises form the backbone of the economy, it is particularly important to support these companies in the introduction of Industry 4.0 and to develop appropriate tools. This work is intended to fill this gap and to enhance research on Industry 4.0 for small and medium-sized enterprises by presenting an exploratory study that has been used to systematically analyze and evaluate the needs and translate them into a final list of (functional) requirements and constraints using axiomatic design as scientific approach.

scholarly journals Open Source Control Device for Industry 4.0 Based on RAMI 4.0

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 869
Author(s):  
Pablo F. S. Melo ◽  
Eduardo P. Godoy ◽  
Paolo Ferrari ◽  
Emiliano Sisinni
Keyword(s):  
Open Source ◽  
Industry 4.0 ◽  
Product Life Cycle ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Control Device ◽  
Source Control ◽  
Reference Architecture ◽  
Architecture Model ◽  
Complex Relationships

The technical innovation of the fourth industrial revolution (Industry 4.0—I4.0) is based on the following respective conditions: horizontal and vertical integration of manufacturing systems, decentralization of computing resources and continuous digital engineering throughout the product life cycle. The reference architecture model for Industry 4.0 (RAMI 4.0) is a common model for systematizing, structuring and mapping the complex relationships and functionalities required in I4.0 applications. Despite its adoption in I4.0 projects, RAMI 4.0 is an abstract model, not an implementation guide, which hinders its current adoption and full deployment. As a result, many papers have recently studied the interactions required among the elements distributed along the three axes of RAMI 4.0 to develop a solution compatible with the model. This paper investigates RAMI 4.0 and describes our proposal for the development of an open-source control device for I4.0 applications. The control device is one of the elements in the hierarchy-level axis of RAMI 4.0. Its main contribution is the integration of open-source solutions of hardware, software, communication and programming, covering the relationships among three layers of RAMI 4.0 (assets, integration and communication). The implementation of a proof of concept of the control device is discussed. Experiments in an I4.0 scenario were used to validate the operation of the control device and demonstrated its effectiveness and robustness without interruption, failure or communication problems during the experiments.

scholarly journals Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

2021 ◽  
Vol 11 (7) ◽  
pp. 3186
Author(s):  
Radhya Sahal ◽  
Saeed H. Alsamhi ◽  
John G. Breslin ◽  
Kenneth N. Brown ◽  
Muhammad Intizar Ali
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Interaction Mechanism ◽  
Semantic Knowledge ◽  
Smart Manufacturing ◽  
Data Detection ◽  
Workflow Model ◽  
Digital Twins ◽  
Potential Failure ◽  
Operational Data

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

scholarly journals Middleware Application, Suitable to Build an Automated and Connected Smart Manufacturing Environment

2021 ◽  
Author(s):  
Muzaffar Rao ◽  
Thomas Newe
Keyword(s):  
Mobile Robots ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Manufacturing Execution System ◽  
Manufacturing Environment ◽  
Industrial Internet ◽  
A Cell ◽  
Smart Industry ◽  
Manufacturing Execution

The current manufacturing transformation is represented by using different terms like; Industry 4.0, smart manufacturing, Industrial Internet of Things (IIoTs), and the Model-Based enterprise. This transformation involves integrated and collaborative manufacturing systems. These manufacturing systems should meet the demands changing in real-time in the smart factory environment. Here, this manufacturing transformation is represented by the term ‘Smart Manufacturing’. Smart manufacturing can optimize the manufacturing process using different technologies like IoT, Analytics, Manufacturing Intelligence, Cloud, Supplier Platforms, and Manufacturing Execution System (MES). In the cell-based manufacturing environment of the smart industry, the best way to transfer the goods between cells is through automation (mobile robots). That is why automation is the core of the smart industry i.e. industry 4.0. In a smart industrial environment, mobile-robots can safely operate with repeatability; also can take decisions based on detailed production sequences defined by Manufacturing Execution System (MES). This work focuses on the development of a middleware application using LabVIEW for mobile-robots, in a cell-based manufacturing environment. This application works as middleware to connect mobile robots with the MES system.

Analysis of Challenges Responsible for the Slow Pace of Industry 4.0 Diffusion

2021 ◽  
pp. 1737-1766
Author(s):  
Chetna Chauhan ◽  
Amol Singh
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Relative Importance ◽  
Fuzzy Analytical Hierarchy Process ◽  
Delphi Approach ◽  
Fuzzy Delphi ◽  
Privacy Risks ◽  
Smart Manufacturing Systems ◽  
Hierarchy Process

The pace of Industry 4.0 adoption in manufacturing industries has been slow as it is accompanied by several barriers, specifically in the emerging economies. The current study intends to identify and understand the landscape of these challenges. Further, this paper prioritizes the challenges on the basis of their relative importance. To achieve this objective, the authors combine the fuzzy delphi approach along with the fuzzy analytical hierarchy process. Additionally, a sensitivity analysis is done to enhance robustness of the findings. The global rankings of the challenges reveal that the most significant factors that hamper the full realization of smart manufacturing include cybersecurity, privacy risks, and enormously high number of technology choices available in the market. The analysis offers insights into the reasons for the slow diffusion of smart manufacturing systems and the results would assist managers, policymakers, and technology providers in the advent of manufacturing digitalization.

scholarly journals Insights into Mapping Solutions Based on OPC UA Information Model Applied to the Industry 4.0 Asset Administration Shell

Computers ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 28 ◽  
Author(s):  
Salvatore Cavalieri ◽  
Marco Giuseppe Salafia
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Information Model ◽  
Industrial Applications ◽  
Reference Architecture ◽  
Architecture Model ◽  
Open Platform ◽  
Advantages And Disadvantages ◽  
The One

In the context of Industry 4.0, lot of effort is being put to achieve interoperability among industrial applications. As the definition and adoption of communication standards are of paramount importance for the realization of interoperability, during the last few years different organizations have developed reference architectures to align standards in the context of the fourth industrial revolution. One of the main examples is the reference architecture model for Industry 4.0, which defines the asset administration shell as the corner stone of the interoperability between applications managing manufacturing systems. Inside Industry 4.0 there is also so much interest behind the standard open platform communications unified architecture (OPC UA), which is listed as the one recommendation for realizing the communication layer of the reference architecture model. The contribution of this paper is to give some insights behind modelling techniques that should be adopted during the definition of OPC UA Information Model exposing information of the very recent metamodel defined for the asset administration shell. All the general rationales and solutions here provided are compared with the current OPC UA-based existing representation of asset administration shell provided by literature. Specifically, differences will be pointed out giving to the reader advantages and disadvantages behind each solution.

scholarly journals Impact Assessment of Additive Manufacturing on Sustainable Business Models in Industry 4.0 Context

2020 ◽  
Vol 12 (17) ◽  
pp. 7066 ◽  
Author(s):  
Radu Godina ◽  
Inês Ribeiro ◽  
Florinda Matos ◽  
Bruna T. Ferreira ◽  
Helena Carvalho ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Business Models ◽  
Industrial Revolution ◽  
New Technologies ◽  
Three Dimensions ◽  
Sustainable Business ◽  
Core Element ◽  
Sustainable Business Models

Additive manufacturing has the potential to make a longstanding impact on the manufacturing world and is a core element of the Fourth Industrial Revolution. Additive manufacturing signifies a new disruptive path on how we will produce parts and products. Several studies suggest this technology could foster sustainability into manufacturing systems based on its potential of optimizing material consumption, creating new shapes, customizing designs and shortening production times that, all combined, will greatly transform some of the existing business models. Although it requires reaching a certain level of design maturity to completely insert this technology in an industrial setting, additive manufacturing has the potential to favorably impact the manufacturing sector by reducing costs in production, logistics, inventories, and in the development and industrialization of a new product. The transformation of the industry and the acceleration of the adopting rate of new technologies is driving organizational strategy. Thus, through the lenses of Industry 4.0 and its technological concepts, this paper aims to contribute to the knowledge about the impacts of additive manufacturing technology on sustainable business models. This aim is accomplished through a proposed framework, as well as the models and scales that can be used to determine these impacts. The effects are assessed by taking into account the social, environmental and economic impacts of additive manufacturing on business models and for all these three dimensions a balanced scorecard structure is proposed.

scholarly journals Special Issue on the Latest Machine Tool Technologies and Manufacturing Processes

2019 ◽  
Vol 13 (5) ◽  
pp. 573-573 ◽  
Author(s):  
Yohichi Nakao ◽  
Hayato Yoshioka
Keyword(s):  
Internet Of Things ◽  
Machine Tool ◽  
Machine Tools ◽  
Manufacturing Systems ◽  
Tool Path ◽  
Industrie 4.0 ◽  
Smart Manufacturing ◽  
Manufacturing Processes ◽  
Special Issue ◽  
Excellent Research

With the 2011 launch of Industrie 4.0, a German project aiming to promote the computerization of manufacturing, the integration of physical or actual manufacturing systems with cyber-physical systems (CPS) using various technologies, such as the Internet of things (IoT), industrial Internet of things (IIOT), and artificial intelligence, is considered to be more important than ever before. One of the goals of the Industrie 4.0 is to realize smart factories or smart manufacturing using advanced digital technologies. However, the core component in the manufacturing systems is still machine tools. This special issue, composed of eleven excellent research papers, focuses on the latest research advances in machine tools and manufacturing processes. It covers various topics, including machine tool control, tool path generation for multi-axis machining, and machine tool components. Furthermore, this special issue includes innovative machining technologies, including not only cutting and grinding processes but also the EDM process and burnishing process connected effectively with force control techniques. All the research contributions were presented at IMEC2018, a joint event with JIMTOF2018, held in Tokyo, Japan in 2018. The editors would like to sincerely thank the authors for their dedication and for their well written and illustrated manuscripts. We are also profoundly grateful for the efforts of all the reviewers who ensured their quality. Finally, we sincerely hope that studies on machine tools and related manufacturing technologies will further contribute to the development of our global society.

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