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Records with Keyword: Industry 4.0
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Design and Optimization Technologies of Permanent Magnet Machines and Drive Systems Based on Digital Twin Model
Lin Liu, Youguang Guo, Wenliang Yin, Gang Lei, Jianguo Zhu
February 27, 2023 (v1)
Keywords: data-driven modelling, digital twin (DT), electrical drive system, Industry 4.0, permanent magnet synchronous motor (PMSM), system-level optimization
One of the keys to the success of the fourth industrial revolution (Industry 4.0) is to empower machinery with cyber−physical systems connectivity. The digital twin (DT) offers a promising solution to tackle the challenges for realizing digital and smart manufacturing which has been successfully projected in many scenes. Electrical machines and drive systems, as the core power providers in many appliances and industrial equipment, are supposed to be reinforced on the verge of Industry 4.0 in the fields of design optimization, fault prognostic and coordinated control. Therefore, this paper aims to investigate the DT modelling method and the applications in electrical drive systems. Firstly, taking the high-speed permanent-magnet machine drive system as an example, multi-disciplinary design fundamentals and technologies, aiming at building initial mechanism and simulation models, are reviewed. The state-of-the-art of DT technologies is figured out to serve for high-precision and multi-sc... [more]
Facing Environmental Goals for Energy-Efficiency Improvements in Micro and Small Enterprises Operating in the Age of Industry 4.0
Tomasz Bernat, Sylwia Flaszewska, Bartłomiej Lisowski, Renata Lisowska, Katarzyna Szymańska
February 27, 2023 (v1)
Subject: Environment
Keywords: Energy Efficiency, environmental objectives, Industry 4.0, micro and small enterprises, Renewable and Sustainable Energy
One of the biggest challenges of a modern enterprise is finding a balance between achieving environmental goals and being competitive in the era of Industry 4.0 requirements. The digital revolution is forcing companies to overcome various challenges that contribute to reducing energy consumption. Micro and small enterprises carry out activities in the field of energy efficiency by implementing measures to save energy and reduce total energy consumption. However, these activities are limited by many barriers to resources, which means that these activities are much smaller than those in large companies. The purpose of this study was to assess the performance of micro and small enterprises following environmental objectives in improving energy efficiency. The research study, based on a structured and standardized survey questionnaire, was conducted with the use of the CATI technique between April and May 2022 among the owners of micro and small enterprises operating in Poland. The study s... [more]
Analysis of Employees’ Competencies in the Context of Industry 4.0
Barbara Kowal, Daria Włodarz, Edyta Brzychczy, Andrzej Klepka
February 27, 2023 (v1)
Keywords: competencies, employees, Industry 4.0, knowledge and skills of engineers, soft skills, technical skills
The implementation of Industry 4.0 technology and meeting the expectations of employers, the labour market, and, in fact, sustainable development are new challenges for industry employees, especially for their knowledge and skills. The changes introduced during industrial revolutions have always affected the job market and employees’ required competencies. The same can be said for the latest industrial revolution, Industry 4.0, in which the human factor plays an important role, mainly because new challenges are posed by human beings’ role in digitised reality. Our research aimed to identify the employee competencies that are required in the context of Industry 4.0. We investigated two groups of respondents (employees and students). These groups were subjected to a comparative analysis of their digital, technical, social and personal competencies. As a result of the analysis, we identified the highest-ranked competencies in defined groups. Our results show that technical and soft skills... [more]
An Econometric Model of the Operation of the Steel Industry in POLAND in the Context of Process Heat and Energy Consumption
Bożena Gajdzik, Radosław Wolniak, Wieslaw Wes Grebski
February 24, 2023 (v1)
Keywords: econometric model, energy price, heat intensity, Industry 4.0, Polish steel industry, statistical analyses, steel production
The analyses presented in the publication allowed, on the basis of the data collected, development of an econometric model for the Polish steel industry from the point of view of the relationship between heat and energy management in the steel production process. The developed model is the main novelty of the paper. The main objective of the study was to develop an econometric model of Poland’s heat and energy economy. The following research questions were raised: Is there an econometric model describing heat consumption (intensity) in the steel industry in Poland in relation to steel production and the energy economy? What are the relations between heat intensity and energy prices and steel production in Poland? How might the current energy crisis affect steel production? In the analysis we used data of energy and heat management in the Polish steel industry. An econometric model was developed of the dependence of heat consumption (Yt) on electricity prices (X1t) and steel production... [more]
Accuracy Analysis of the Indoor Location System Based on Bluetooth Low-Energy RSSI Measurements
Dariusz Janczak, Wojciech Walendziuk, Maciej Sadowski, Andrzej Zankiewicz, Krzysztof Konopko, Adam Idzkowski
February 24, 2023 (v1)
Subject: Environment
Keywords: Bluetooth Low Energy, evacuation system, Industry 4.0, localization, proximity tracing system, received signal strength intensity, RSSI, smart building
Systems for determining the position of objects inside buildings have a wide range of applications, such as the surveillance of people’s movements in hospitals, and of goods or mobile robots in warehouse spaces or production halls. Hence, there is a need for the development of methods that could be applied for those purposes. This paper presents the results of research on an experimental system for localizing people being evacuated from a building. The proposed solution was designed as a part of the building evacuation management system. The method used for finding location belongs to the class of proximity-type methods and is based on Received Signal Strength Indicator (RSSI) information of Bluetooth Low-Energy (BLE) devices. The devices used to build the system (BLE receivers) and the evacuee’s wristband (BLE transmitters) are low-budget electronic modules. The paper presents preliminary research and the process of selecting data processing methods, as well as the results of tests of... [more]
Charging Stations and Electromobility Development: A Cross-Country Comparative Analysis
Tomasz Zema, Adam Sulich, Sebastian Grzesiak
February 23, 2023 (v1)
Keywords: cluster analysis, electric vehicle charging, Industry 4.0, internet of vehicles
The Industry 4.0 idea influences the development of both charging stations and electromobility development, due to its emphasis on device communication, cooperation, and proximity. Therefore, in electromobility development, growing attention is paid to chargers’ infrastructure density and automotive electric vehicles’ accessibility. The main goal of this scientific paper was to present the electromobility development represented in the number of charging stations and its infrastructure development calculations. In this study, the sequence of methods was used to indicate and explore the research gap. The first was the Structured Literature Review (SLR) variation method. The second method was the classical tabular comparison of gathered results. The third research method was a cluster analysis based on secondary data with cross-country comparisons of the number of charging stations and electric cars. Therefore, this paper presents a theoretical discussion and practical business implicati... [more]
Multifunctional Technology of Flexible Manufacturing on a Mechatronics Line with IRM and CAS, Ready for Industry 4.0
Adriana Filipescu, Dan Ionescu, Adrian Filipescu, Eugenia Mincă, Georgian Simion
February 23, 2023 (v1)
Keywords: industrial robotic manipulator, Industry 4.0, mechatronics line, visual servoing system, wheeled mobile robot
A communication and control architecture of a multifunctional technology for flexible manufacturing on an assembly, disassembly, and repair mechatronics line (A/D/RML), assisted by a complex autonomous system (CAS), is presented in the paper. A/D/RML consists of a six-work station (WS) mechatronics line (ML) connected to a flexible cell (FC) equipped with a six-degree of freedom (DOF) industrial robotic manipulator (IRM). The CAS has in its structure two driving wheels and one free wheel (2 DW/1 FW)-wheeled mobile robot (WMR) equipped with a 7-DOF robotic manipulator (RM). On the end effector of the RM, a mobile visual servoing system (eye-in-hand VSS) is mounted. The multifunctionality is provided by the three actions, assembly, disassembly, and repair, while the flexibility is due to the assembly of different products. After disassembly or repair, CAS picks up the disassembled components and transports them to the appropriate storage depots for reuse. Technology operates synchronousl... [more]
Effect of Biomedical Materials in the Implementation of a Long and Healthy Life Policy
Leszek A. Dobrzański, Anna D. Dobrzańska-Danikiewicz, Lech B. Dobrzański
February 23, 2023 (v1)
Subject: Materials
Keywords: bioengineering, Bioengineering 4.0, biomedical materials, COVID-19 pandemic, dental engineering, dentistry, Dentistry 4.0, engineers’ ethics, health, Industry 4.0, long and healthy life policy, medical engineering, medical ethics, medicine, well-being
This paper is divided into seven main parts. Its purpose is to review the literature to demonstrate the importance of developing bioengineering and global production of biomaterials to care for the level of healthcare in the world. First, the general description of health as a universal human value and assumptions of a long and healthy life policy is presented. The ethical aspects of the mission of medical doctors and dentists were emphasized. The coronavirus, COVID-19, pandemic has had a significant impact on health issues, determining the world’s health situation. The scope of the diseases is given, and specific methods of their prevention are discussed. The next part focuses on bioengineering issues, mainly medical engineering and dental engineering, and the need for doctors to use technical solutions supporting medicine and dentistry, taking into account the current stage Industry 4.0 of the industrial revolution. The concept of Dentistry 4.0 was generally presented, and a general... [more]
Backstepping Methodology to Troubleshoot Plant-Wide Batch Processes in Data-Rich Industrial Environments
Federico Zuecco, Matteo Cicciotti, Pierantonio Facco, Fabrizio Bezzo, Massimiliano Barolo
February 23, 2023 (v1)
Keywords: batch processes, fault diagnosis, fault identification, Industry 4.0, principal component analysis, process monitoring, statistical process control, troubleshooting
Troubleshooting batch processes at a plant-wide level requires first finding the unit causing the fault, and then understanding why the fault occurs in that unit. Whereas in the literature case studies discussing the latter issue abound, little attention has been given so far to the former, which is complex for several reasons: the processing units are often operated in a non-sequential way, with unusual series-parallel arrangements; holding vessels may be required to compensate for lack of production capacity, and reacting phenomena can occur in these vessels; and the evidence of batch abnormality may be available only from the end unit and at the end of the production cycle. We propose a structured methodology to assist the troubleshooting of plant-wide batch processes in data-rich environments where multivariate statistical techniques can be exploited. Namely, we first analyze the last unit wherein the fault manifests itself, and we then step back across the units through the proces... [more]
Magnetic Particle Inspection Optimization Solution within the Frame of NDT 4.0
Andreea Ioana Sacarea, Gheorghe Oancea, Luminita Parv
February 23, 2023 (v1)
Subject: Optimization
Keywords: Industry 4.0, magnetic particle inspection, NDT, Optimization
The quality of product and process is one of the most important factors in achieving constructively and then functionally safe products in any industry. Over the years, the concept of Industry 4.0 has emerged in all the quality processes, such as nondestructive testing (NDT). The most widely used quality control methods in the industries of mechanical engineering, aerospace, and civil engineering are nondestructive methods, which are based on inspection by detecting indications, without affecting the surface quality of the examined parts. Over time, the focus has been on research with the fourth generation in nondestructive testing, i.e., NDT 4.0 or Smart NDT, as a main topic to ensure the efficiency and effectiveness of the methods for a safe detection of all types of discontinuities. This area of research aims at the efficiency of methods, the elimination of human errors, digitalization, and optimization from a constructive point of view. In this paper, we presented a magnetic partic... [more]
Using Artificial Neural Network and Fuzzy Inference System Based Prediction to Improve Failure Mode and Effects Analysis: A Case Study of the Busbars Production
Saeed Na’amnh, Muath Bani Salim, István Husti, Miklós Daróczi
February 23, 2023 (v1)
Keywords: artificial neural network (ANN), busbars, failure mode and effects analysis (FMEA), fuzzy inference system (FIS), Industry 4.0, risk priority number (RPN)
Nowadays, Busbars have been extensively used in electrical vehicle industry. Therefore, improving the risk assessment for the production could help to screen the associated failure and take necessary actions to minimize the risk. In this research, a fuzzy inference system (FIS) and artificial neural network (ANN) were used to avoid the shortcomings of the classical method by creating new models for risk assessment with higher accuracy. A dataset includes 58 samples are used to create the models. Mamdani fuzzy model and ANN model were developed using MATLAB software. The results showed that the proposed models give a higher level of accuracy compared to the classical method. Furthermore, a fuzzy model reveals that it is more precise and reliable than the ANN and classical models, especially in case of decision making.
Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation
Stefan Kassen, Holger Tammen, Maximilian Zarte, Agnes Pechmann
February 23, 2023 (v1)
Keywords: AnyLogic™, brownfield, digital manufacturing, digital twin, generic simulation, Industry 4.0, production
Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for production optimisation and can be used to simulate production systems, which reduce necessary physical test runs and related costs. While most companies are not able to create digital twins yet, companies using enterprise resource planning (ERP) systems have the general capability to create digital shadows. This paper presents a concept and a case study for a generic simulation of production systems... [more]
A New Perspective for Solving Manufacturing Scheduling Based Problems Respecting New Data Considerations
Mohammed A. Awad, Hend M. Abd-Elaziz
February 23, 2023 (v1)
Keywords: flexible job shop scheduling, heuristics, Industry 4.0, integrated process planning and scheduling, job shop scheduling, Optimization
In order to attain high manufacturing productivity, industry 4.0 merges all the available system and environment data that can empower the enabled-intelligent techniques. The use of data provokes the manufacturing self-awareness, reconfiguring the traditional manufacturing challenges. The current piece of research renders attention to new consideration in the Job Shop Scheduling (JSSP) based problems as a case study. In that field, a great number of previous research papers provided optimization solutions for JSSP, relying on heuristics based algorithms. The current study investigates the main elements of such algorithms to provide a concise anatomy and a review on the previous research papers. Going through the study, a new optimization scope is introduced relying on additional available data of a machine, by which the Flexible Job-Shop Scheduling Problem (FJSP) is converted to a dynamic machine state assignation problem. Deploying two-stages, the study utilizes a combination of discr... [more]
Modeling and Analysis of Industry 4.0 Adoption Challenges in the Manufacturing Industry
Naif Alsaadi
February 23, 2023 (v1)
Subject: Environment
Keywords: challenges, Industry 4.0, manufacturing sector, structural model, sustainable development
The manufacturing sector is a fast-growing sector demanded by the increasing population. The adoption of information technology is a boon in the manufacturing industry. The industrial transformation from the third generation to the fourth generation has significantly impacted sustainable development. On account of this, different sectors are adopting industry 4.0 technologies to smooth their process flows. The industry 4.0 technologies implementation in the manufacturing sector will not only enhance its productivity, but also lead to sustainable growth. In this regard, this study intended to examine the challenges associated with adopting industry 4.0 technologies in the manufacturing sector. A thorough literature review was carried out from the Scopus database, and a list of ten important challenges was shortlisted for analysis. The article uses interpretive structural modeling to analyse the challenges of industry 4.0 and make a structural model between identified challenges. “Lack o... [more]
A Review on Data-Driven Quality Prediction in the Production Process with Machine Learning for Industry 4.0
Abdul Quadir Md, Keshav Jha, Sabireen Haneef, Arun Kumar Sivaraman, Kong Fah Tee
February 23, 2023 (v1)
Keywords: anomaly, Artificial Intelligence, data-driven, Industry 4.0, Machine Learning, manufacturing, quality control
The quality-control process in manufacturing must ensure the product is free of defects and performs according to the customer’s expectations. Maintaining the quality of a firm’s products at the highest level is very important for keeping an edge over the competition. To maintain and enhance the quality of their products, manufacturers invest a lot of resources in quality control and quality assurance. During the assembly line, parts will arrive at a constant interval for assembly. The quality criteria must first be met before the parts are sent to the assembly line where the parts and subparts are assembled to get the final product. Once the product has been assembled, it is again inspected and tested before it is delivered to the customer. Because manufacturers are mostly focused on visual quality inspection, there can be bottlenecks before and after assembly. The manufacturer may suffer a loss if the assembly line is slowed down by this bottleneck. To improve quality, state-of-the-a... [more]
Data-Driven Intelligent Model for the Classification, Identification, and Determination of Data Clusters and Defect Location in a Welded Joint
Chijioke Jerry Oleka, Daniel Osezua Aikhuele, Eseosa Omorogiuwa
February 23, 2023 (v1)
Keywords: flaws/defects, Industry 4.0, k-mean clustering, LOF model algorithm, welded joint
In this paper, a data-driven approach that is based on the k-mean clustering and local outlier factor (LOF) algorithm has been proposed and deployed for the management of non-destructive evaluation (NDE) in a welded joint. The k-mean clustering and LOF model algorithm, which was implemented for the classification, identification, and determination of data clusters and defect location in the welded joint datasets, were trained and validated such that three (3) different clusters and noise points were obtained. The noise points, which are regarded as the welded joint defects/flaws, allow for the determination of the cluster size, heterogeneity, and silhouette score of the welded joint data. Similarly, the LOF model algorithm was implemented for the detection, visualization, and management of flaws due to internal cracks, porosity, fusion, and penetration in the welded joint. It is believed that the management of welded joint flaws would aid the actualization of the Industry 4.0 concept i... [more]
From Human-Human to Human-Machine Cooperation in Manufacturing 4.0
Lydia Habib, Marie-Pierre Pacaux-Lemoine, Quentin Berdal, Damien Trentesaux
February 23, 2023 (v1)
Keywords: human-machine cooperation, Industry 4.0, intelligent manufacturing system
Humans are currently experiencing the fourth industrial revolution called Industry 4.0. This revolution came about with the arrival of new technologies that promise to change the way humans work and interact with each other and with machines. It aims to improve the cooperation between humans and machines for mutual enrichment. This would be done by leveraging human knowledge and experience, and by reactively balancing some complex or complicated tasks with intelligent systems. To achieve this objective, methodological approaches based on experimental studies should be followed to ensure a proper evaluation of human-machine system design choices. This paper proposes an experimental study based on a platform that uses an intelligent manufacturing system made up of mobile robots, autonomous shuttles using the principle of intelligent products, and manufacturing robots in the context of Manufacturing 4.0. Two experiments were conducted to evaluate the impact of teamwork human-machine coope... [more]
Value Configurations for Data and Connectivity Solutions in Digitalized Future Factories
Solmaz Mansoori, Iqra Sadaf Khan, Petri Ahokangas, Marja Matinmikko-Blue, Harri Haapasalo, Seppo Yrjölä
February 22, 2023 (v1)
Subject: Environment
Keywords: 5G, business ecosystem, digitalization, future factories, Industry 4.0, local operator, value configuration
The ongoing Industry 4.0 transformation places significant pressures on how businesses create and capture value. Technological advancements such as next-generation mobile communications are reshaping the business ecosystem of Industry 4.0, resulting in emerging business opportunities for new players, such as local operators, to collaborate and compete with mobile communications companies that are implementing I4.0. These changes raise the need to explore emerging business opportunities concerning the digitalization of future factories. New data and connectivity services are introduced to serve the needs of rapidly increasing machine-type communications that rely on connectivity, primarily through the fifth generation (5G) mobile solutions provided by local operators. Thus, this paper outlines the potential value configurations for data and connectivity solutions by identifying, matching, and bridging the utilizable resources and addressable needs within the factory processes. The resea... [more]
Digital Twins for Wind Energy Conversion Systems: A Literature Review of Potential Modelling Techniques Focused on Model Fidelity and Computational Load
Jeroen D. M. De Kooning, Kurt Stockman, Jeroen De Maeyer, Antonio Jarquin-Laguna, Lieven Vandevelde
February 22, 2023 (v1)
Keywords: digital twins, direct-drive, Industry 4.0, permanent magnet synchronous generator, wind energy, wind turbines
The Industry 4.0 concept of a Digital Twin will bring many advantages for wind energy conversion systems, e.g., in condition monitoring, predictive maintenance and the optimisation of control or design parameters. A virtual replica is at the heart of a digital twin. To construct a virtual replica, appropriate modelling techniques must be selected for the turbine components. These models must be chosen with the intended use case of the digital twin in mind, finding a proper balance between the model fidelity and computational load. This review article presents an overview of the recent literature on modelling techniques for turbine aerodynamics, structure and drivetrain mechanics, the permanent magnet synchronous generator, the power electronic converter and the pitch and yaw systems. For each component, a balanced overview is given of models with varying model fidelity and computational load, ranging from simplified lumped parameter models to advanced numerical Finite Element Method (F... [more]
Energy Reduction with Super-Resolution Convolutional Neural Network for Ultrasound Tomography
Dariusz Wójcik, Tomasz Rymarczyk, Bartosz Przysucha, Michał Gołąbek, Dariusz Majerek, Tomasz Warowny, Manuchehr Soleimani
February 22, 2023 (v1)
Keywords: deep learning, energy consumption, energy optimization, Industry 4.0, inverse problems, Machine Learning, tomography
This study addresses the issue of energy optimization by investigating solutions for the reduction of energy consumption in the diagnostics and monitoring of technological processes. The implementation of advanced process control is identified as a key approach for achieving energy savings and improving product quality, process efficiency, and production flexibility. The goal of this research is to develop a cost-effective system with a minimal number of ultrasound sensors, thus reducing the energy consumption of the overall system. To accomplish this, a novel method for obtaining high-resolution reconstruction in transmission ultrasound tomography (t-UST) is proposed. The method involves utilizing a convolutional neural network to take low-resolution measurements as input and output high-resolution sinograms that are used for tomography image reconstruction. This approach allows for the construction of a super-resolution sinogram by utilizing information hidden in the low-resolution m... [more]
Wireless Technologies for Industry 4.0 Applications
Eneko Artetxe, Oscar Barambones, Isidro Calvo, Pablo Fernández-Bustamante, Imanol Martin, Jokin Uralde
February 22, 2023 (v1)
Keywords: cyber–physical systems (CPS), industrial Internet of Things (IIoT), Industry 4.0, wireless control systems, wireless sensor networks (WSNs)
Wireless technologies are increasingly used in industrial applications. These technologies reduce cabling, which is costly and troublesome, and introduce several benefits for their application in terms of flexibility to modify the layout of the nodes and scaling of the number of connected devices. They may also introduce new functionalities since they ease the connections to mobile devices or parts. Although they have some drawbacks, they are increasingly accepted in industrial applications, especially for monitoring and supervision tasks. Recently, they are starting to be accepted even for time-critical tasks, for example, in closed-loop control systems involving slow dynamic processes. However, wireless technologies have been evolving very quickly during the last few years, since several relevant technologies are available in the market. For this reason, it may become difficult to select the best alternative. This perspective article intends to guide application designers to choose t... [more]
An Enabling Open-Source Technology for Development and Prototyping of Production Systems by Applying Digital Twinning
Robert Kazała, Sławomir Luściński, Paweł Strączyński, Albena Taneva
February 22, 2023 (v1)
Keywords: Digital Twin, Industry 4.0, simulation modelling
This article presents the most valuable and applicable open-source tools and communication technologies that may be employed to create models of production processes by applying the concept of Digital Twins. In recent years, many open-source technologies, including tools and protocols, have been developed to create virtual models of production systems. The authors present the evolution and role of the Digital Twin concept as one of the key technologies for implementing the Industry 4.0 paradigm in automation and control. Based on the presented structured review of valuable open-source software dedicated to various phases and tasks that should be realised while creating the whole Digital Twin system, it was demonstrated that the available solutions cover all aspects. However, the dispersion, specialisation, and lack of integration cause this software to usually not be the first choice to implement DT. Therefore, to successfully create full-fledged models of Digital Twins by proceeding w... [more]
The Product Customization Process in Relation to Industry 4.0 and Digitalization
Martin Pech, Jaroslav Vrchota
February 21, 2023 (v1)
Subject: Environment
Keywords: customization, digitalization, e-commerce, Industry 4.0, personalization, process
Today’s customer no longer wants one-size-fits-all products but expects products and services to be as tailored as possible. Mass customization and personalization are becoming a trend in the digitalization strategy of enterprises and manufacturing in Industry 4.0. The purpose of the paper is to develop and validate a conceptual model for leveraging Industry 4.0 and digitalization to support product customization. We explored the implications and impacts of Industry 4.0 and digitalization on product customization processes and determine the importance of variables. We applied structural equation modeling (SEM) to test our hypotheses regarding the antecedents and consequences of digitalization and Industry 4.0. We estimated the process model using the partial least squares (PLS) method, and goodness of fit measures show acceptable values. The proposed model considers relationships between technology readiness, digitalization, internal and external integration, internal value chain, and... [more]
Digital Twin Applications: A Survey of Recent Advances and Challenges
Rafael da Silva Mendonça, Sidney de Oliveira Lins, Iury Valente de Bessa, Florindo Antônio de Carvalho Ayres Jr, Renan Landau Paiva de Medeiros, Vicente Ferreira de Lucena Jr
February 21, 2023 (v1)
Keywords: industrial cyber-physical system, industrial digital twin, Industry 4.0
Industry 4.0 integrates a series of emerging technologies, such as the Internet of Things (IoT), cyber-physical systems (CPS), cloud computing, and big data, and aims to improve operational efficiency and accelerate productivity inside the industrial environment. This article provides a series of information about the required structure to adopt Industry 4.0 approaches and a brief review of related concepts to finally identify challenges and research opportunities to envision the adoption of so-called digital twins. We want to pay attention to upgrading older systems aiming to provide the well-known advantages of Industry 4.0 to such legacy systems as reducing production costs, increasing efficiency, acquiring better robustness of equipment, and reaching advanced process connectivity.
A Review of Digital Transformation on Supply Chain Process Management Using Text Mining
Madjid Tavana, Akram Shaabani, Iman Raeesi Vanani, Rajan Kumar Gangadhari
February 21, 2023 (v1)
Keywords: analytics, Big Data, digital transformation, Industry 4.0, supply chain management, text mining
Industry 4.0 technologies are causing a paradigm shift in supply chain process management. The digital transformation of the supply chains provides enormous benefits to organizations by empowering collaboration among multiple internal and external organizations and systems. This study presents a narrative review explaining the existing knowledge on digital transformation in supply chain process management using text mining. It summarizes the existing literature to explain the current state of the art in supply chain digitalization. This comprehensive review identifies the most important topics and technologies and determines the future trends in this emerging field. We investigate the articles published in Web of Science and Scopus databases and use text mining techniques (clustering and topic modeling) on the article contents. Using VOS viewer, a bibliometric analysis of 395 articles with 12,700 references is analyzed. The contents of the articles are explored using text mining approa... [more]
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