Warning: sizeof(): Parameter must be an array or an object that implements Countable in /homepages/26/d94734260/htdocs/clickandbuilds/PSECommunity/wp-content/plugins/wpor/includes/class-wpor.php on line 4338
Records with Keyword: Industry 4.0
Integration and Evaluation of Intra-Logistics Processes in Flexible Production Systems Based on OEE Metrics, with the Use of Computer Modelling and Simulation of AGVs
Krzysztof Foit, Grzegorz Gołda, Adrian Kampa
July 29, 2021 (v1)
Keywords: AGV—Automated Guided Vehicles, DES—Discrete Event Simulation, FMS—Flexible Manufacturing Systems, Industry 4.0, OEE—Overall Equipment Efficiency, WCLcWorld Class Logistic
The article presents the problems connected with the performance evaluation of a flexible production system in the context of designing and integrating production and logistics subsystems. The goal of the performed analysis was to determine the parameters that have the most significant influence on the productivity of the whole system. The possibilities of using automated machine tools, automatic transport vehicles, as well as automated storage systems were pointed out. Moreover, the exemplary models are described, and the framework of simulation research related to the conceptual design of new production systems are indicated. In order to evaluate the system’s productivity, the use of Overall Equipment Efficiency (OEE) metrics was proposed, which is typically used for stationary resources such as machines. This paper aims to prove the hypothesis that the OEE metric can also be used for transport facilities such as Automated Guided Vehicles (AGVs). The developed models include the para... [more]
First Principles Statistical Process Monitoring of High-Dimensional Industrial Microelectronics Assembly Processes
Tiago J. Rato, Pedro Delgado, Cristina Martins, Marco S. Reis
June 10, 2021 (v1)
Keywords: artificial generation of variability, data augmentation, high-dimensional data, Industry 4.0, statistical process monitoring
Modern industrial units collect large amounts of process data based on which advanced process monitoring algorithms continuously assess the status of operations. As an integral part of the development of such algorithms, a reference dataset representative of normal operating conditions is required to evaluate the stability of the process and, after confirming that it is stable, to calibrate a monitoring procedure, i.e., estimate the reference model and set the control limits for the monitoring statistics. The basic assumption is that all relevant “common causes” of variation appear well represented in this reference dataset (using the terminology adopted by the founding father of process monitoring, Walter A. Shewhart). Otherwise, false alarms will inevitably occur during the implementation of the monitoring scheme. However, we argue and demonstrate in this article, that this assumption is often not met in modern industrial systems. Therefore, we introduce a new approach based on the r... [more]
Quantitative Methods to Support Data Acquisition Modernization within Copper Smelters
Alessandro Navarra, Ryan Wilson, Roberto Parra, Norman Toro, Andrés Ross, Jean-Christophe Nave, Phillip J. Mackey
May 27, 2021 (v1)
Keywords: adaptive finite differences, copper smelter, discrete event simulation, Industry 4.0, matte-slag chemistry, nickel-copper smelter, Peirce-smith converting, radiometric sensors
Sensors and process control systems are essential for process automation and optimization. Many sectors have adapted to the Industry 4.0 paradigm, but copper smelters remain hesitant to implement these technologies without appropriate justification, as many critical functions remain subject to ground operator experience. Recent experiments and industrial trials using radiometric optoelectronic data acquisition, coupled with advanced quantitative methods and expert systems, have successfully distinguished between mineral species in reactive vessels with high classification rates. These experiments demonstrate the increasing potential for the online monitoring of the state of a charge in pyrometallurgical furnaces, allowing data-driven adjustments to critical operational parameters. However, the justification to implement an innovative control system requires a quantitative framework that is conducive to multiphase engineering projects. This paper presents a unified quantitative framewor... [more]
Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce
Daniel I. Onwude, Guangnan Chen, Nnanna Eke-emezie, Abraham Kabutey, Alfadhl Yahya Khaled, Barbara Sturm
May 25, 2021 (v1)
Keywords: agricultural production, crop storage and processing, food distribution, food quality, food security, Industry 4.0, refrigeration, smart digital technology
Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the years been employed to reduce the quality loss of fruits and vegetables from farm to fork. However, a high amount of losses (≈50%) still occur during the packaging, pre-cooling, transportation, and storage of these fresh agricultural produce. This study highlights the current state-of-the-art of various advanced tools employed to reducing the quality loss of fruits and vegetables during the packaging, storage, and transportation cold chain operations, including the application of imaging technology, spectroscopy, multi-sensors, electronic nose, radio frequency identification, printed sensors, acoustic impulse response, and mathematical models. It is shown that computer vision, hyperspectral imaging, m... [more]
Multivariate Six Sigma: A Case Study in Industry 4.0
Daniel Palací-López, Joan Borràs-Ferrís, Larissa Thaise da Silva de Oliveria, Alberto Ferrer
March 14, 2021 (v1)
Keywords: Industry 4.0, latent variables models, multivariate data analysis, PCA, PLS, Six Sigma
The complex data characteristics collected in Industry 4.0 cannot be efficiently handled by classical Six Sigma statistical toolkit based mainly in least squares techniques. This may refrain people from using Six Sigma in these contexts. The incorporation of latent variables-based multivariate statistical techniques such as principal component analysis and partial least squares into the Six Sigma statistical toolkit can help to overcome this problem yielding the Multivariate Six Sigma: a powerful process improvement methodology for Industry 4.0. A multivariate Six Sigma case study based on the batch production of one of the star products at a chemical plant is presented.
Non-Antagonistic Contradictoriness of the Progress of Advanced Digitized Production with SARS-CoV-2 Virus Transmission in the Area of Dental Engineering
Leszek A. Dobrzański, Lech B. Dobrzański, Anna D. Dobrzańska-Danikiewicz, Joanna Dobrzańska, Karolina Rudziarczyk, Anna Achtelik-Franczak
March 1, 2021 (v1)
Subject: Other
Keywords: additive digital light printing, dendrological matrix, dentistry 4.0, elimination clinical aerosol at the source, Industry 4.0, photopolymer materials, SARS-CoV-2 pandemic, SPEC strategy
The general goals of advanced digitized production in the Industry 4.0 stage of the industrial revolution were presented along with the extended holistic model of Industry 4.0, introduced by the authors, indicating the importance of material design and the selection of appropriate manufacturing technology. The effect of the global lockdown caused by the SARS-CoV-2 virus transmission pandemic was a drastic decrease in production, resulting in a significant decrease in the gross domestic product GDP in all countries, and gigantic problems in health care, including dentistry. Dentists belong to the highest risk group because the doctor works in the patient’s respiratory tract. This paper presents a breakthrough authors solution, implemented by the active SPEC strategy, and aims to eliminate clinical aerosol at the source by negative pressure aspirating bioaerosol at the patient’s mouth line. The comparative benchmarking analysis and its results show that only the proprietary solution with... [more]
Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review
Yingjie Chen, Ou Yang, Chaitanya Sampat, Pooja Bhalode, Rohit Ramachandran, Marianthi Ierapetritou
February 22, 2021 (v1)
Keywords: biopharmaceutical manufacturing, digital twin, Industry 4.0, pharmaceutical manufacturing, process modeling
The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current statu... [more]
Integrating the Concept of Industry 4.0 by Teaching Methodology in Industrial Engineering Curriculum
Bashir Salah, Sajjad Khan, Muawia Ramadan, Nikola Gjeldum
December 28, 2020 (v1)
Subject: Education
Keywords: engineering education, Industry 4.0, reconfigurable manufacturing systems, smart factory, smart product
The movement to digitally transform Saudi Arabia in all sectors has already begun under the “Vision 2030” program. Consequently, renovating and standardizing production and manufacturing industries to compete with global challenges is essential. The fourth industrial revolution (Industry 4.0) triggered by the development of information and communications technologies (ICT) provides a baseline for smart automation, using decentralized control and smart connectivity (e.g., Internet of Things). Industrial engineering graduates need to have acquaintance with this industrial digital revolution. Several industries where the spirit of Industry 4.0 has been embraced and have already implemented these ideas yielded gains. In this paper, a roadmap containing an academic term course based on the concept of Industry 4.0, which our engineering graduates passed through, is presented. At first, an orientation program to students elaborating on the Industry 4.0 concept, its main pillars, the importanc... [more]
Real-Time Decision-Support System for High-Mix Low-Volume Production Scheduling in Industry 4.0
Balázs Kocsi, Michael Maiko Matonya, László Péter Pusztai, István Budai
December 17, 2020 (v1)
Keywords: decision-support system, HMLV production, Industry 4.0, real-time production-scheduling techniques, risk analysis, RPA
Numerous organizations are striving to maximize the profit of their businesses by the effective implementation of competitive advantages including cost reduction, quick delivery, and unique high-quality products. Effective production-scheduling techniques are methods that many firms use to attain these competitive advantages. Implementing scheduling techniques in high-mix low-volume (HMLV) manufacturing industries, especially in Industry 4.0 environments, remains a challenge, as the properties of both parts and processes are dynamically changing. As a reaction to these challenges in HMLV Industry 4.0 manufacturing, a newly advanced and effective real-time production-scheduling decision-support system model was developed. The developed model was implemented with the use of robotic process automation (RPA), and it comprises a hybrid of different advanced scheduling techniques obtained as the result of analytical-hierarchy-process (AHP) analysis. The aim of this research was to develop a... [more]
Quality 4.0 in Action: Smart Hybrid Fault Diagnosis System in Plaster Production
Javaneh Ramezani, Javad Jassbi
August 5, 2020 (v1)
Keywords: construction industry, control chart pattern, decision support systems, discriminant analysis, disruption management, disruptions, expert systems, failure mode and effects analysis (FMEA), fault diagnosis, Industry 4.0, neural networks, plaster production, statistical process control
Industry 4.0 (I4.0) represents the Fourth Industrial Revolution in manufacturing, expressing the digital transformation of industrial companies employing emerging technologies. Factories of the future will enjoy hybrid solutions, while quality is the heart of all manufacturing systems regardless of the type of production and products. Quality 4.0 is a branch of I4.0 with the aim of boosting quality by employing smart solutions and intelligent algorithms. There are many conceptual frameworks and models, while the main challenge is to have the experience of Quality 4.0 in action at the workshop level. In this paper, a hybrid model based on a neural network (NN) and expert system (ES) is proposed for dealing with control chart patterns (CCPs). The idea is to have, instead of a passive descriptive model, a smart predictive model to recommend corrective actions. A construction plaster-producing company was used to present and evaluate the advantages of this novel approach, while the result... [more]
Dentistry 4.0 Concept in the Design and Manufacturing of Prosthetic Dental Restorations
Leszek A. Dobrzański, Lech B. Dobrzański
July 2, 2020 (v1)
Subject: Other
Keywords: additive manufacturing technologies, CAD/CAM methods, CBCT tomography, dental implants, dental prosthesis restoration manufacturing center, Dentistry 4.0, hybrid multilayer biological-engineering composites biomaterials, implant-scaffolds, Industry 4.0, prosthetic restorations, selective laser sintering, stereolithography, stomatognathic system, surgical guide
The paper is a comprehensive but compact review of the literature on the state of illnesses of the human stomatognathic system, related consequences in the form of dental deficiencies, and the resulting need for prosthetic treatment. Types of prosthetic restorations, including implants, as well as new classes of implantable devices called implant-scaffolds with a porous part integrated with a solid core, as well as biological engineering materials with the use of living cells, have been characterized. A review of works on current trends in the technical development of dental prosthetics aiding, called Dentistry 4.0, analogous to the concept of the highest stage of Industry 4.0 of the industrial revolution, has been presented. Authors’ own augmented holistic model of Industry 4.0 has been developed and presented. The studies on the significance of cone-beam computed tomography (CBCT) in planning prosthetic treatment, as well as in the design and manufacture of prosthetic restorations, h... [more]
Industrial Internet of Things and Fog Computing to Reduce Energy Consumption in Drinking Water Facilities
Adrian Korodi, Ruben Crisan, Andrei Nicolae, Ioan Silea
May 8, 2020 (v1)
Keywords: data analysis, fog computing, historian, Industrial Internet of Things, Industry 4.0, water industry
The industry is generally preoccupied with the evolution towards Industry 4.0 principles and the associated advantages as cost reduction, respectively safety, availability, and productivity increase. So far, it is not completely clear how to reach these advantages and what their exact representation or impact is. It is necessary for industrial systems, even legacy ones, to assure interoperability in the context of chronologically dispersed and currently functional solutions, respectively; the Open Platform Communications Unified Architecture (OPC UA) protocol is an essential requirement. Then, following data accumulation, the resulting process-aware strategies have to present learning capabilities, pattern identification, and conclusions to increase efficiency or safety. Finally, model-based analysis and decision and control procedures applied in a non-invasive manner over functioning systems close the optimizing loop. Drinking water facilities, as generally the entire water sector, ar... [more]
Enhancing Failure Mode and Effects Analysis Using Auto Machine Learning: A Case Study of the Agricultural Machinery Industry
Sami Sader, István Husti, Miklós Daróczi
April 14, 2020 (v1)
Keywords: auto machine learning, failure mode effects analysis, Industry 4.0, risk priority number
In this paper, multiclass classification is used to develop a novel approach to enhance failure mode and effects analysis and the generation of risk priority number. This is done by developing four machine learning models using auto machine learning. Failure mode and effects analysis is a technique that is used in industry to identify possible failures that may occur and the effects of these failures on the system. Meanwhile, risk priority number is a numeric value that is calculated by multiplying three associated parameters namely severity, occurrence and detectability. The value of risk priority number determines the next actions to be made. A dataset that includes a one-year registry of 1532 failures with their description, severity, occurrence, and detectability is used to develop four models to predict the values of severity, occurrence, and detectability. Meanwhile, the resulted models are evaluated using 10% of the dataset. Evaluation results show that the proposed models have... [more]
A Hybrid Data-Based and Model-Based Approach to Process Monitoring and Control in Sheet Metal Forming
Sravan Tatipala, Johan Wall, Christian Johansson, Tobias Larsson
February 3, 2020 (v1)
Keywords: in-line measurement data, Industry 4.0, modelling and simulation, process monitoring and control, process performance, product quality, sheet metal forming
The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line... [more]
Applied Research Towards Industry 4.0: Opportunities for SMEs
Ilaria Zambon, Gianluca Egidi, Fabiano Rinaldi, Sirio Cividino
August 8, 2019 (v1)
Subject: Energy Policy
Keywords: industrial processes, Industry 4.0, job safety, Renewable and Sustainable Energy, SMEs, sustainable development, technologies
Industry 4.0 designates the recent digital revolution in the industrial sector, evolving from the comprehensive networking and automation of all the productive areas. Equipment, machinery, materials and products permit to (i) distinguish dealing out environmental settings and current status via sensors; (ii) join them through fixed software; and (iii) progress production procedures in an exclusive method. Additionally, Industry 4.0 exposes new trials to enterprises, especially small and medium-sized enterprises (SMEs). Firms should advance approaches to (i) achieve chances of innovation and digitalization; (ii) expand their processes; and (iii) define innovative business models. Based on these premises, a well-organized political, legal and infrastructural outline is essential to build up a business having an Industry 4.0 approach. Though bigger firms can get ahead through innovation processes and predicting the potential digitalization risks for their business models, SMEs may be in t... [more]
Standardizing Innovation Management: An Opportunity for SMEs in the Aerospace Industry
Alberto Cerezo-Narváez, Daniel García-Jurado, María Carmen González-Cruz, Andrés Pastor-Fernández, Manuel Otero-Mateo, Pablo Ballesteros-Pérez
July 31, 2019 (v1)
Keywords: aerospace industry, development and innovation (R+D+i), industrial processes, Industry 4.0, innovation, management system, metrology, research, small and medium-sized enterprises (SMEs)
In a globalized marketplace, the competition in the aerospace industry has increased significantly. Producers can choose between many suppliers. These suppliers have to comply with more requirements and technical specifications, as well as take on greater responsibilities that originally fell on producers. In this context, business opportunities for small and medium-sized enterprises (SMEs) are limited, but still suppliers must try to leverage the maximum strategic advantage of the few that present. Adopting research, development and innovation (R+D+i) practices has proven to bring great benefits to companies and allows them to gain significant competitive advantages. However, the process of designing, implementing and testing R+D+i-related processes is not straightforward, nor it has been addressed in the recent research on SMEs. In this paper, a case study of a Spanish innovative small company providing industrial metrology and quality services is analyzed. Thanks to an internal deci... [more]
Evaluating the Factors that are Affecting the Implementation of Industry 4.0 Technologies in Manufacturing MSMEs, the Case of Peru
Chung-Jen Huang, Elisa Denisse Talla Chicoma, Yi-Hsien Huang
July 25, 2019 (v1)
Keywords: analytic hierarchy process, developing countries, Industry 4.0, micro, small, and medium enterprises
The micro, small, and medium enterprises (MSMEs) sector plays a very crucial role in the economic and social development of Peru. Unfortunately, the tough access to the use of technologies is one of the weaknesses of this type of enterprises, which implies a low technological intensity production, according to the new technological trends. This study analyzes the factors that are affecting the implementation of Industry 4.0 technologies in Peruvian micro, small, and medium enterprises. According to the findings from the semi-structured interviews, it has identified four factors that respond to the main question of this research—lack of advanced technology, lack of financial investment, poor management vision, and lack of skilled workers. Data from 49 enterprises from the manufacturing sector were used for the assessment. The surveys conducted on business managers were evaluated using a multi-criterion decision-making method by the analytic hierarchy process. The findings of the study g... [more]
Drivers and Barriers in Using Industry 4.0: A Perspective of SMEs in Romania
Mirela Cătălina Türkeș, Ionica Oncioiu, Hassan Danial Aslam, Andreea Marin-Pantelescu, Dan Ioan Topor, Sorinel Căpușneanu
July 25, 2019 (v1)
Keywords: barriers, business, cloud computing, cyber-physical systems, digitalization, drivers, flexible manufacturing, implementation, Industry 4.0, managers, SMEs, systems
Considering the worldwide evolutionary stage of Industry 4.0, this study wants to fill in a lack of information and decision-making, trying to answer a question about the level of preparation of Romanian Small and Medium-sized Enterprises (SMEs) regarding the implementation of the new technology. The main purpose of this article is to identify the opinions and perceptions of SME managers in Romania on the drivers and barriers of implementing Industry 4.0 technology for business development. The research method used in the study was analyzed by sampling using the questionnaire as a data collection tool. It includes closed questions, measured with a nominal and orderly scale. 176 managers provided complete and useful answers to this research. The collected data were analyzed with the Statistical Package for the Social Sciences (SPSS) package using frequency tables, contingency tables, and main component analysis. Major contributions from research have highlighted the fact that Romania is... [more]
Improvement of Temperature Control Performance of Thermoelectric Dehumidifier Used Industry 4.0 by the SF-PI Controller
Jae-Sub Ko, Jun-Ho Huh, Jong-Chan Kim
June 10, 2019 (v1)
Keywords: computer architecture, dehumidifier, fuzzy, Industry 4.0, PI controller, smart gird, temperature-control, thermoelectric element, water grid
This paper proposes the series connected fuzzy-proportional integral (SF-PI) controller, which is composed of the fuzzy control and the PI controller to improve temperature control performance of dehumidifier using a thermoelectric element. The control of conventional PI controller usually uses fixed gain. For that reason, it is limited in achieving satisfactory control performance in both transient-state and steady-state. The fuzzy control within SF-PI controller adjusts the input value of PI controller according to operating condition. The PI controller within the SF-PI controller controls the temperature of the thermoelectric element using that value. The SF-PI controller can achieve more accurate temperature control than a conventional PI controller for that reason. The SF-PI controller has been tested for various indoor environmental conditions such as temperature and relative humidity conditions. The average temperature error of the SF-PI controller between the reference temperat... [more]
Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs
Ilaria Zambon, Massimo Cecchini, Gianluca Egidi, Maria Grazia Saporito, Andrea Colantoni
April 15, 2019 (v1)
Subject: Energy Policy
Keywords: agriculture 4.0, application research, Industry 4.0, open source, SMEs, Supply Chain
The present review retraces the steps of the industrial and agriculture revolution that have taken place up to the present day, giving ideas and considerations for the future. This paper analyses the specific challenges facing agriculture along the farming supply chain to permit the operative implementation of Industry 4.0 guidelines. The subsequent scientific value is an investigation of how Industry 4.0 approaches can be improved and be pertinent to the agricultural sector. However, industry is progressing at a much faster rate than agriculture. In fact, already today experts talk about Industry 5.0. On the other hand, the 4.0 revolution in agriculture is still limited to a few innovative firms. For this reason, this work deals with how technological development affects different sectors (industry and agriculture) in different ways. In this innovative background, despite the advantages of industry or agriculture 4.0 for large enterprises, small- and medium-sized enterprises (SMEs) of... [more]
Simulation and Test Bed of a Low-Power Digital Excitation System for Industry 4.0
Jun-Ho Huh, Hoon-Gi Lee
April 8, 2019 (v1)
Keywords: computer architecture, digital excitation system, Industry 4.0, low power, operating system, Simulation, smart grid, Test Bed
Since modeling and simulation are the two most effective tools that can be used in the design or analysis process, they play a vital role in developing such system. In many cases, they are the only possible means of making a safe engineering decision for a new concept of process for a large-scale system. Elsewhere, they are used as a critical element in the analysis of energy systems or to suggest a method of developing a novel and effective energy system model. Thus, in this study, simulations and test bed experiment were carried out to assess a low-power digital excitation system in order to validate its effectiveness. The excitation systems currently used by most of the power stations in the Republic of Korea were installed during the 1970s or 1980s. Unfortunately, it is difficult to seek technical assistance for them as they depend on foreign technologies, requiring a large sum to be paid when requesting one or more engineers to be dispatched. As such, technical updates have always... [more]
Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques
Wen-Hsien Tsai
September 21, 2018 (v1)
Keywords: activity-based costing (ABC), carbon emissions, green manufacturing, Industry 4.0, mathematical programming, textile industry
The textile industry is one of the world’s major sources of industrial pollution, and related environmental issues are becoming an ever greater concern. This paper considers the environmental issues of carbon emissions, energy recycling, and waste reuse, and uses a mathematical programming model with Activity-Based Costing (ABC) and the Theory of Constraints (TOC) to achieve profit maximization. This paper discusses the combination of mathematical programming and Industry 4.0 techniques to achieve the purpose of green production planning and control for the textile industry in the new era. The mathematical programming model is used to determine the optimal product mix under various production constraints, while Industry 4.0 techniques are used to control the production progress to achieve the planning targets. With the help of an Industry 4.0 real-time sensor and detection system, it can achieve the purposes of recycling waste, reducing carbon emission, saving energy and cost, and fina... [more]
An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices
Shabir Ahmad, Sehrish Malik, Israr Ullah, Muhammad Fayaz, Dong-Hwan Park, Kwangsoo Kim, DoHyeun Kim
July 31, 2018 (v1)
Keywords: embedded devices, Industry 4.0, input tasks admission control, internet of things, IoT task scheduling, real-time systems
Embedded devices are gaining popularity day by day due to the expanded use of Internet of Things applications. However, these embedded devices have limited capabilities concerning power and memory. Thus, the applications need to be tailored in such a way to perform the specified tasks within the constrained resources with the same accuracy. In Real-Time task scheduling, one of the challenging factors is the intelligent modelling of input tasks in such a way that it produces not only logically correct output within the deadline but also consumes minimum CPU power. Algorithms like Rate Monotonic and Earliest Deadline First compute hyper-period of input tasks for periodic repetition of the same set of tasks on CPU. However, at times when the tasks are not adequately modelled, they lead to an enormously high value of hyper-period which result in more CPU cycles and power consumption. Many state-of-the-art solutions are presented in this regard, but the main problem is that they limit tasks... [more]
Effect of Cooperation on Manufacturing IT Project Development and Test Bed for Successful Industry 4.0 Project: Safety Management for Security
Sangil Park, Jun-Ho Huh
July 31, 2018 (v1)
Keywords: Bluetooth beacons, coding process, computer architecture, industrial processes, Industry 4.0, job safety, safety management, security, test bed, worker’s positional management
A new direction of the 4th industrial revolution in manufacturing and IT industries is presented in this study, wherein the manufacturing sector will be able to survive in this period by achieving rapid and flexible change through effective convergence between both industries. Under such an environment, manufacturing IT requires speedy development and a new distribution form, as well as a new method of IT project development which is adequate for that form. Thus, this study compares and analyzes the waterfall method which is being used in general manufacturing System Integration (SI) projects and the proposed DevOps method, which requires faster distribution and improvement. This study confirms that the required human resources are less than the existing SI projects when system improvement is made using the DevOps method. At the same time, this method provides much-improved quality for the same price. Therefore, future manufacturing IT projects would achieve a faster and more efficient... [more]
Design of a Shipboard Outside Communication Network and Its Testbed Using PLC: For Safety Management during the Ship Building Process
Jun-Ho Huh, Taehoon Koh, Kyungryong Seo
July 31, 2018 (v1)
Keywords: industrial processes, Industry 4.0, job safety, PLC, safety management, shadow area, ship building process, shipboard outside communication network, testbed
For the shipbuilding industry worldwide, work-related accidents at the construction site have been a major concern. Workers at the shipyards are consistently exposed to dangerous environments and their intensity of work is quite high. Considering the complexity of the shipbuilding process, efficient communications between workers are essential in the workplace, but current communication methods, which mostly use wireless technologies, are sometimes limited by the structural blocks, creating shadow areas where the radio bands cannot reach. As a countermeasure, SUNCOM Co., Ltd in the Republic of Korea has developed the PLC-based communication system followed by establishing a test-bed facility in cooperation with SK Telecom Co., Ltd and the Hyundai Heavy Industries Co., Ltd. This system and applied technologies are expected to reduce accidents in the field and be applied for other industries having the same problem, providing an uninterrupted communication environment and safer working c... [more]
[Show All Keywords]