scholarly journals Digital Twins Supporting Efficient Digital Industrial Transformation

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6829
Author(s):  
Dinithi Bamunuarachchi ◽  
Dimitrios Georgakopoulos ◽  
Abhik Banerjee ◽  
Prem Prakash Jayaraman
Keyword(s):  
Production Line ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Industrial Applications ◽  
Cost Models ◽  
Application Development ◽  
Industrial Transformation ◽  
Digital Twins ◽  
Cost Efficient ◽  
Support Cost

Industry 4.0 applications help digital industrial transformation to be achieved through smart, data-driven solutions that improve production efficiency, product consistency, preventive maintenance, and the logistics of industrial applications and related supply chains. To enable and accelerate digital industrial transformation, it is vital to support cost-efficient Industry 4.0 application development. However, the development of such Industry 4.0 applications is currently expensive due to the limitations of existing IoT platforms in representing complex industrial machines, the support of only production line-based application testing, and the lack of cost models for application cost/benefit analysis. In this paper, we propose the use of Cyber Twins (CTs), an extension of Digital Twins, to support cost-efficient Industry 4.0 application development. CTs provide semantic descriptions of the machines they represent and incorporate machine simulators that enable application testing without any production line risk and cost. This paper focuses on CT-based Industry 4.0 application development and the related cost models. Via a case study of a CT-based Industry 4.0 application from the dairy industry, the paper shows that CT-based Industry 4.0 applications can be developed with approximately 60% of the cost of IoT platform-based application development.

Industry 4.0 initiatives in EU countries: experience for Ukraine

2020 ◽  
pp. 65-70
Author(s):  
Nataliya Ryvak ◽  
Anna Kernytska
Keyword(s):  
Industry 4.0 ◽  
Business Models ◽  
Industrial Revolution ◽  
Successful Implementation ◽  
Industrial Complex ◽  
Interconnected System ◽  
Industrial Transformation ◽  
Eu Countries ◽  
European Experience ◽  
High Level

In this paper, digital technologies development was analyzed as the basis for the so-called “fourth industrial revolution” with the potential for the qualitative transformation of the Ukrainian economy based on EU countries’ experience. Industry 4.0 is a new control chain over the entire chain of creating value throughout the product lifecycle. When developing an economic policy, it is important to pay attention to Industry 4.0. It increases productivity, produces new, better, and individualized products, and implements new business models based on “undermining” innovations. A comparative analysis of national initiatives I4.0 with their characteristics according to the main dimensions, including funding, focus, direction, was conducted. Particular attention was paid to considering deterrents to the successful implementation and enforcement of the I4.0 initiative in European countries. The factors of successful implementation of I4.0 initiatives in the EU countries were analyzed. Drawing on the analysis of the European experience of digital transformations in industry and national economies in general, the necessity of critical focus of such transformations in Ukraine was highlighted, and the need for state support of industrial transformation was substantiated. The emphasis was placed on the cooperation development between stakeholders within the implementation of Industry 4.0 – it is necessary to create national and regional 4.0 platforms, following the example of EU countries, which would bring together government institutions, businesses, and academics. The successful positioning of the Ukrainian modern industrial complex on the world markets depends on the high level of the interconnected system providing factors that characterize its development process. Considering the influence of a list of inhibiting factors on implementing the country’s industry accelerated development, a set of measures needed to transform Ukraine’s industry based on European experience was substantiated.

scholarly journals Dissecting cellobiose metabolic pathway and its application in biorefinery through consolidated bioprocessing in Myceliophthora thermophila

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Jingen Li ◽  
Shuying Gu ◽  
Zhen Zhao ◽  
Bingchen Chen ◽  
Qian Liu ◽  
...  
Keyword(s):  
Malic Acid ◽  
Plant Biomass ◽  
Consolidated Bioprocessing ◽  
Cellulase Activity ◽  
Industrial Applications ◽  
Efficient Production ◽  
Myceliophthora Thermophila ◽  
Final Strain ◽  
Cellobiose Metabolism ◽  
Cost Efficient

Abstract Background Lignocellulosic biomass has long been recognized as a potential sustainable source for industrial applications. The costs associated with conversion of plant biomass to fermentable sugar represent a significant barrier to the production of cost-competitive biochemicals. Consolidated bioprocessing (CBP) is considered a potential breakthrough for achieving cost-efficient production of biomass-based fuels and commodity chemicals. During the degradation of cellulose, cellobiose (major end-product of cellulase activity) is catabolized by hydrolytic and phosphorolytic pathways in cellulolytic organisms. However, the details of the two intracellular cellobiose metabolism pathways in cellulolytic fungi remain to be uncovered. Results Using the engineered malic acid production fungal strain JG207, we demonstrated that the hydrolytic pathway by β-glucosidase and the phosphorolytic pathway by phosphorylase are both used for intracellular cellobiose metabolism in Myceliophthora thermophila, and the yield of malic acid can benefit from the energy advantages of phosphorolytic cleavage. There were obvious differences in regulation of the two cellobiose catabolic pathways depending on whether M. thermophila JG207 was grown on cellobiose or Avicel. Disruption of Mtcpp in strain JG207 led to decreased production of malic acid under cellobiose conditions, while expression levels of all three intracellular β-glucosidase genes were significantly up-regulated to rescue the impairment of the phosphorolytic pathway under Avicel conditions. When the flux of the hydrolytic pathway was reduced, we found that β-glucosidase encoded by bgl1 was the dominant enzyme in the hydrolytic pathway and deletion of bgl1 resulted in significant enhancement of protein secretion but reduction of malate production. Combining comprehensive manipulation of both cellobiose utilization pathways and enhancement of cellobiose uptake by overexpression of a cellobiose transporter, the final strain JG412Δbgl2Δbgl3 produced up to 101.2 g/L and 77.4 g/L malic acid from cellobiose and Avicel, respectively, which corresponded to respective yields of 1.35 g/g and 1.03 g/g, representing significant improvement over the starting strain JG207. Conclusions This is the first report of detailed investigation of intracellular cellobiose catabolism in cellulolytic fungus M. thermophila. These results provide insights that can be applied to industrial fungi for production of biofuels and biochemicals from cellobiose and cellulose.

Cost management for concrete batch plant using stochastic mathematical models

2006 ◽  
Vol 33 (8) ◽  
pp. 1065-1074 ◽  
Author(s):  
Tarek M Zayed ◽  
Ibrahim A Nosair
Keyword(s):  
Mathematical Models ◽  
Production Efficiency ◽  
Cost Management ◽  
Unit Cost ◽  
Expected Value ◽  
Cost Models ◽  
Productivity Cost ◽  
Batch Plant ◽  
Factor Share ◽  
Construction Operation

Assessing productivity, cost, and delays are essential to manage any construction operation, particularly the concrete batch plant (CBP) operation. This paper focuses on assessing the above-mentioned items for the CBP using stochastic mathematical models. It aims at (i) identifying the potential sources of delay in the CBP operation; (ii) assessing their influence on production, efficiency, time, and cost; and (iii) determining each factor share in inflating the CBP concrete unit expense. Stochastic mathematical models were designed to accomplish the aforementioned objectives. Data were collected from five CBP sites in Indiana, USA, to implement and verify the designed models. Results show that delays due to management conditions have the highest probability of occurrence (0.43), expected value of delay percent (62.54% out of total delays), and relative delay percent. The expected value of efficiency for all plants is 86.53%; however, the average total expense is US$15.56/m3 (all currency are in US$). In addition, the expected value of effective expenses (EE) is $18.03/m3, resulting in extra expenses (XE) of $2.47/m3. This research is relevant to both industry practitioners and researchers. It develops models to determine the effect of delays on concrete unit cost. They are also beneficial to the CBP management.Key words: concrete batch plant, delays, management conditions, cost models, cost management, stochastic mathematical models.

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.

Digital Twins: Review and Challenges

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Maria G. Juarez ◽  
Vicente J. Botti ◽  
Adriana S. Giret
Keyword(s):  
Computer Science ◽  
Industry 4.0 ◽  
Multi Agent System ◽  
Agent System ◽  
Digital Twin ◽  
Digital Twins ◽  
Science Approach ◽  
Multi Agent ◽  
Current Operating

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

scholarly journals Navantia’s Shipyard 4.0 model overview

2018 ◽  
Vol 11 (22) ◽  
pp. 77 ◽  
Author(s):  
Ángel Recamán Rivas
Keyword(s):  
Industry 4.0 ◽  
Implementation Process ◽  
Special Focus ◽  
Industrial Transformation ◽  
Shipbuilding Industry ◽  
Industrial Sectors ◽  
The Future ◽  
The Government ◽  
Willingness To Cooperate ◽  
Expected Outcomes

Navantia finished the analysis of the concept Industry 4.0 in 2016 and its application to the naval shipbuilding industry, referred to herein as Shipyard 4.0. The implementation process has begun with several projects that involved various technologies. In order to incorporate them in the new project, for naval vessels and systems, special focus has been put in the future F-110 frigate.This document aims to provide an overview of the Shipyard 4.0 model and a brief discussion regarding the projects launched for its implementation in Navantia. The initiative 4.0 is a key development vector across all the industrial sectors in the future and its expected outcomes match the ones established by the Government of Colombia in its “Plan de Transformación Industrial” (Plan of Industrial Transformation). In this context, the new frigate program (PES) is a unique opportunity to engage the local industry, in which Navantia offers its willingness to cooperate.

scholarly journals Factors Affecting Fault Tolerance during Load Balancing in Cloud Computing

2021 ◽  
Vol 12 (11) ◽  
pp. 1523-1533
Author(s):  
Bidush Kumar Sahoo , Et. al.
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
South India ◽  
Analysis Tool ◽  
Factors Affecting ◽  
Software Firms ◽  
Statistical Analysis Tool ◽  
Cost Efficient ◽  
Support Cost

Cloud computing is built upon the advancement of virtualization and distributed computing to support cost-efficient usage of computing resources and to provide on demand services. After methodical analysis on various factors affecting fault tolerance during load balancing is performed and it is concluded that the factors influencing fault tolerance in load balancing are cloud security, adaptability etc. in comparatively more software firms. In this paper, we have created a model for various IT industries for checking the fault tolerance during Load balancing. An exploration is done with the help of some renowned IT farms and industries in South India. This work consists of 20 hypotheses which may affect the fault tolerance during load balancing in South India. It is verified by using potential statistical analysis tool i.e. Statistical Package for Social Science (SPSS).

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