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Digital Transformation in Manufacturing Industry Ⅱ
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Digital Transformation in Manufacturing Industry Ⅱ

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

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 22240

Special Issue Editor

Dr. Radmehr P. Monfared

E-Mail Website
Guest Editor
School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: digitalized technologies; supply chain management; business process analysis and simulation; blockchain technologies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

During the last decade, the world has been transformed by new digital technologies. The current digital transformation has vast potential to change consumers’ lives and meet their new expectations, add further value to data-driven businesses, and create unique societal benefits.

The rate of technological innovation is exponential, to the point that change is becoming almost a new normal now, with many innovations having passed the proof-of-concept stage and entered the investment phase.

Although it has become apparent that industrial digitalization is potentially capable of improving the productivity and predictability of businesses, manufacturing industries are lagging behind and failing to keep pace with other sectors such as finance and media. This is probably due to the need for proven technological robustness and demonstratable benefits.

This Special Issue is aimed at disseminating advanced research in the theory and application of digitalization in the manufacturing industries (also known by some experts as Industry 4.0).

The scope of this Special Issue is focused on new digital technologies that can have a direct impact on various lifecycle stages of manufacturing industries. These could include marketing, design, production, quality control, resource management, supply chain, product and process tracking, and product recycling.

The potential themes include but are not limited to the application of the following technologies within manufacturing industries: cloud computing, big data, Internet of Things (IoT), blockchain in manufacturing, virtual engineering and digital twining (virtual reality and augmented reality), simulation, machine learning for analytics and predictions in industrial businesses, and industrial cybersecurity.

We also invite articles investigating the human role in digitalized manufacturing industries, the need for resource upskilling, and new business models for manufacturing industries.

 

Dr. Radmehr P. Monfared
Guest Editor

Manuscript Submission Information

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

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

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (5 papers)

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Research

14 pages, 1291 KiB  
Article
Indoor Positioning Systems Can Revolutionise Digital Lean
by Tuan-Anh Tran, Tamás Ruppert and János Abonyi
Appl. Sci. 2021, 11(11), 5291; https://doi.org/10.3390/app11115291 - 7 Jun 2021
Cited by 20 | Viewed by 4131
Abstract
The powerful combination of lean principles and digital technologies accelerates waste identification and mitigation faster than traditional lean methods. The new digital lean (also referred to as Lean 4.0) solutions incorporate sensors and digital equipment, yielding innovative solutions that extend the reach of [...] Read more.
The powerful combination of lean principles and digital technologies accelerates waste identification and mitigation faster than traditional lean methods. The new digital lean (also referred to as Lean 4.0) solutions incorporate sensors and digital equipment, yielding innovative solutions that extend the reach of traditional lean tools. The tracking of flexible and configurable production systems is not as straightforward as in a simple conveyor. This paper examines how the information provided by indoor positioning systems (IPS) can be utilised in the digital transformation of flexible manufacturing. The proposed IPS-based method enriches the information sources of value stream mapping and transforms positional data into key-performance indicators used in Lean Manufacturing. The challenges of flexible and reconfigurable manufacturing require a dynamic value stream mapping. To handle this problem, a process mining-based solution has been proposed. A case study is provided to show how the proposed method can be employed for monitoring and improving manufacturing efficiency. Full article
(This article belongs to the Special Issue Digital Transformation in Manufacturing Industry Ⅱ)
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14 pages, 1958 KiB  
Article
From Brown-Field to Future Industrial Networks, a Case Study
by Mehrzad Lavassani, Johan Åkerberg and Mats Björkman
Appl. Sci. 2021, 11(7), 3231; https://doi.org/10.3390/app11073231 - 3 Apr 2021
Cited by 6 | Viewed by 2420
Abstract
The network infrastructures in the future industrial networks need to accommodate, manage and guarantee performance to meet the converged Internet technology (IT) and operational technology (OT) traffics requirements. The pace of IT–OT networks development has been slow despite their considered benefits in optimizing [...] Read more.
The network infrastructures in the future industrial networks need to accommodate, manage and guarantee performance to meet the converged Internet technology (IT) and operational technology (OT) traffics requirements. The pace of IT–OT networks development has been slow despite their considered benefits in optimizing the performance and enhancing information flows. The hindering factors vary from general challenges in performance management of the diverse traffic for green-field configuration to lack of outlines for evolving from brown-fields to the converged network. Focusing on the brown-field, this study provides additional insight into a brown-field characteristic to set a baseline that enables the subsequent step development towards the future’s expected converged networks. The case study highlights differences between real-world network behavior and the common assumptions for analyzing the network traffic covered in the literature. Considering the unsatisfactory performance of the existing methods for characterization of brown-field traffic, a performance and dynamics mixture measurement is proposed. The proposed method takes both IT and OT traffic into consideration and reduces the complexity, and consequently improves the flexibility, of performance and configuration management of the brown-field. Full article
(This article belongs to the Special Issue Digital Transformation in Manufacturing Industry Ⅱ)
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21 pages, 1471 KiB  
Article
The Impact of Force Factors on the Benefits of Digital Transformation in Romania
by Sorinel Căpușneanu, Dorel Mateș, Mirela Cătălina Tűrkeș, Cristian-Marian Barbu, Adela-Ioana Staraș, Dan Ioan Topor, Laurențiu Stoenică and Melinda Timea Fűlöp
Appl. Sci. 2021, 11(5), 2365; https://doi.org/10.3390/app11052365 - 7 Mar 2021
Cited by 18 | Viewed by 5951
Abstract
The digital transformation has produced changes in all existing areas of activity worldwide. There are many factors that can influence the intention to use Industry 4.0 processes and solutions and change the behavior of organizations and their business models. The aim of this [...] Read more.
The digital transformation has produced changes in all existing areas of activity worldwide. There are many factors that can influence the intention to use Industry 4.0 processes and solutions and change the behavior of organizations and their business models. The aim of this study is to validate the econometric model on assessing the significant impact of distinct factors on the intention to use Industry 4.0 processes and solutions, the benefits of digital transformation perceived by organizational management and the differences between distinct groups analyzed. The research method used within the quantitative study was the sample survey, using the online questionnaire as a data collection tool. Three hundred forty-seven valid questionnaires were collected and the response rate of the respondents was 64.25%. A new structural model was generated based on the elements of the Unified Theory of Acceptance and Use of Technology (UTAUT). The results of the study indicated that Perceived competitiveness and Perceived risk have a significant impact on Intention to Use Industry 4.0 processes while Perceived vertical networking solutions and Perceived integrated engineering solutions have a significant influence on the Intention to Use Industry 4.0 solutions. In conclusion, there is a positive and significant association between Intention to Use Industry 4.0 solutions and Benefits of Digital Transformation. Full article
(This article belongs to the Special Issue Digital Transformation in Manufacturing Industry Ⅱ)
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16 pages, 1186 KiB  
Article
User-Engagement Score and SLIs/SLOs/SLAs Measurements Correlation of E-Business Projects Through Big Data Analysis
by Solomiia Fedushko, Taras Ustyianovych, Yuriy Syerov and Tomas Peracek
Appl. Sci. 2020, 10(24), 9112; https://doi.org/10.3390/app10249112 - 20 Dec 2020
Cited by 30 | Viewed by 3938
Abstract
The Covid-19 crisis lockdown caused rapid transformation to remote working/learning modes and the need for e-commerce-, web-education-related projects development, and maintenance. However, an increase in internet traffic has a direct impact on infrastructure and software performance. We study the problem of accurate and [...] Read more.
The Covid-19 crisis lockdown caused rapid transformation to remote working/learning modes and the need for e-commerce-, web-education-related projects development, and maintenance. However, an increase in internet traffic has a direct impact on infrastructure and software performance. We study the problem of accurate and quick web-project infrastructure issues/bottleneck/overload identification. The research aims to achieve and ensure the reliability and availability of a commerce/educational web project by providing system observability and Site Reliability Engineering (SRE) methods. In this research, we propose methods for technical condition assessment by applying the correlation of user-engagement score and Service Level Indicators (SLIs)/Service Level Objectives (SLOs)/Service Level Agreements (SLAs) measurements to identify user satisfaction types along with the infrastructure state. Our solution helps to improve content quality and, mainly, detect abnormal system behavior and poor infrastructure conditions. A straightforward interpretation of potential performance bottlenecks and vulnerabilities is achieved with the developed contingency table and correlation matrix for that purpose. We identify big data and system logs and metrics as the central sources that have performance issues during web-project usage. Throughout the analysis of an educational platform dataset, we found the main features of web-project content that have high user-engagement and provide value to services’ customers. According to our study, the usage and correlation of SLOs/SLAs with other critical metrics, such as user satisfaction or engagement improves early indication of potential system issues and avoids having users face them. These findings correspond to the concepts of SRE that focus on maintaining high service availability. Full article
(This article belongs to the Special Issue Digital Transformation in Manufacturing Industry Ⅱ)
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38 pages, 16864 KiB  
Article
Customer-Oriented Quality of Service Management Method for the Future Intent-Based Networking
by Mykola Beshley, Peter Veselý, Andrii Pryslupskyi, Halyna Beshley, Marian Kyryk, Vasyl Romanchuk and Ihor Kahalo
Appl. Sci. 2020, 10(22), 8223; https://doi.org/10.3390/app10228223 - 20 Nov 2020
Cited by 19 | Viewed by 4765
Abstract
The rapid development and spread of communication technologies is now becoming a global information revolution. Customers have a need for communication services, which could be flexibly configured in accordance with their Quality of Experience (QoE) requirements. Realizing the close connection between customer experience [...] Read more.
The rapid development and spread of communication technologies is now becoming a global information revolution. Customers have a need for communication services, which could be flexibly configured in accordance with their Quality of Experience (QoE) requirements. Realizing the close connection between customer experience and profitability, the service provider has been placing more and more attention on customer experience and QoE. The traditional quality of service management method based on SLA (Service Level Agreement) is not sufficient as a means to provide QoE-related contracts between service providers and customers. The current SLA method is mostly limited and focused on technical aspects of QoS (Quality of Service). Furthermore, they do not follow on the network the principles and semantic approach to the QoS specification for a communication service using QoE parameters. In this paper, we propose a customer-oriented quality of service management method for future IBN (Intent-Based Networking). It is based on a new QoE metric on a scale from 1 to 5, which allows one to take into account the commercial value of e-services for customers. Based on this approach, the network configuration and functionality of network equipment automatically changes depending on customer requirements. To implement the new method of service quality management, an algorithm for routing data packets in the network was developed, taking into account the current load of the forecast path. The algorithm of billing system functioning in conditions of customer-oriented quality management in telecommunication networks has been created. To investigate the effectiveness of the proposed method of service quality management with the traditional SLA method, we developed a simulation network model with the implementation of two approaches. By conducting a simulation, it was determined that the proposed method gives an average gain of 2–5 times for the criterion of the number of customers who require high quality of experience of the service. Full article
(This article belongs to the Special Issue Digital Transformation in Manufacturing Industry Ⅱ)
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