Service Computing for Industry 4.0: State of the Art, Challenges, and Research Opportunities

2022 ◽  
Vol 54 (9) ◽  
pp. 1-38
Author(s):  
Frank Siqueira ◽  
Joseph G. Davis
Keyword(s):  
Information And Communication Technologies ◽  
Industry 4.0 ◽  
Large Scale ◽  
State Of The Art ◽  
Manufacturing Sector ◽  
Industrial Applications ◽  
Smart Manufacturing ◽  
Software Infrastructure ◽  
Research Opportunities ◽  
Service Computing

Recent advances in the large-scale adoption of information and communication technologies in manufacturing processes, known as Industry 4.0 or Smart Manufacturing, provide us a window into how the manufacturing sector will evolve in the coming decades. As a result of these initiatives, manufacturing firms have started to integrate a series of emerging technologies into their processes that will change the way products are designed, manufactured, and consumed. This article provides a comprehensive review of how service-oriented computing is being employed to develop the required software infrastructure for Industry 4.0 and identifies the major challenges and research opportunities that ensue. Particular attention is paid to the microservices architecture, which is increasingly recognized as offering a promising approach for developing innovative industrial applications. This literature review is based on the current state of the art on service computing for Industry 4.0 as described in a large corpus of recently published research papers, which helped us to identify and explore a series of challenges and opportunities for the development of this emerging technology frontier, with the goal of facilitating its widespread adoption.

scholarly journals Visible Light Communications for Industrial Applications—Challenges and Potentials

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2157
Author(s):  
Yousef Almadani ◽  
David Plets ◽  
Sander Bastiaens ◽  
Wout Joseph ◽  
Muhammad Ijaz ◽  
...  
Keyword(s):  
Visible Light ◽  
Electromagnetic Interference ◽  
Industry 4.0 ◽  
High Speed ◽  
Data Exchange ◽  
Research Work ◽  
Industrial Applications ◽  
Smart Manufacturing ◽  
Low Latency ◽  
Visible Light Communications

Visible Light Communication (VLC) is a short-range optical wireless communication technology that has been gaining attention due to its potential to offload heavy data traffic from the congested radio wireless spectrum. At the same time, wireless communications are becoming crucial to smart manufacturing within the scope of Industry 4.0. Industry 4.0 is a developing trend of high-speed data exchange in automation for manufacturing technologies and is referred to as the fourth industrial revolution. This trend requires fast, reliable, low-latency, and cost-effective data transmissions with fast synchronizations to ensure smooth operations for various processes. VLC is capable of providing reliable, low-latency, and secure connections that do not penetrate walls and is immune to electromagnetic interference. As such, this paper aims to show the potential of VLC for industrial wireless applications by examining the latest research work in VLC systems. This work also highlights and classifies challenges that might arise with the applicability of VLC and visible light positioning (VLP) systems in these settings. Given the previous work performed in these areas, and the major ongoing experimental projects looking into the use of VLC systems for industrial applications, the use of VLC and VLP systems for industrial applications shows promising potential.

scholarly journals A Critical Review of Smart Manufacturing & Industry 4.0 Maturity Models: Applicability in the O&G Upstream Industry

2021 ◽  
Author(s):  
Chinedu Onyeme ◽  
Kapila Liyanage
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Oil And Gas ◽  
Manufacturing Sector ◽  
Transition Process ◽  
Smart Manufacturing ◽  
Maturity Model ◽  
Business Organizations ◽  
Initial State ◽  
Maturity Models

The shift towards Industry 4.0 is a fundamental driver of improved changes observed in today’s business organizations. The difficulties in adapting to this new approach pose challenges for many companies especially in the oil and gas (O&G) upstream sector. To make this path much feasible for companies in this industry, Maturity Models (MMs) are very useful tools in achieving this following their use in evaluation of the initial state of a company for planned development journey towards Industry 4.0 (I4.0) readiness and implementation. Study shows that only a limited number of O&G specific roadmaps, MMs, frameworks and readiness assessments are available today. This paper aims to review the currently available Industry 4.0 MMs for manufacturing industries and analyze their applicability in the O&G upstream sector using the systematic literature review (SLR) methodology, recognizing the specific requirements of this industry. The study looks at the key characteristic for O&G sector in relation to the manufacturing sector and identifies research gaps needed to be addressed to successfully support the O&G sector in readiness for Industry 4.0 implementation. An Industry 4.0 maturity model that reflects the industrial realities for the O&G upstream sector more accurately from insights drawn from the reviews of existing MMs is proposed. This reduces the challenges of the transition process towards Industry 4.0 and provides support for the critical change desired for improved efficiency in the sector.

scholarly journals Information and communication technologies support for the participation of universities in innovation networks (comparative study)

2018 ◽  
Vol 14 (3) ◽  
pp. 17-29 ◽  
Author(s):  
Olha Prokopenko ◽  
Rurik Holmberg ◽  
Vitaliy Omelyanenko
Keyword(s):  
Information And Communication Technologies ◽  
Industry 4.0 ◽  
Innovation System ◽  
Communication Technologies ◽  
Industrial Applications ◽  
Global Environment ◽  
Knowledge Generation ◽  
Innovation Networks ◽  
Information And Communication

To ensure and strengthen the development of high-tech R&D and its industrial applications in the long-term perspective, information and communication technologies (ICT) cooperation tools with national and international institutions, network associations and firms are of great importance. To solve this problem, a joint systematic and coordinated work to develop institutions that can provide crucial support to innovation process is crucial. For these purposes, higher educational institutions (HEI) innovation activities information and communication support and technological development analysis are critically important. The purpose of this study is to analyze the existing ICT toolkit, which is used to manage R&D and various industrial applications, and to develop a conceptual framework for the implementation of these tools for the participation of universities in innovation networks. To answer this question, authors begin by taking a closer look at the new role of universities in the development of knowledge generation in a global environment, as well as problems and tendencies under conditions of postindustrial society. The new role of universities in knowledge generation in the global environment development, and problems and tendencies under the conditions of postindustrial society were outlined. Modern ICT components, which are necessary for universities to participate in the innovation networks, were analyzed. Some cases of foreign experience in the scientific and innovation networks of current prototypes of Industry 4.0 development were discussed, and the possibilities of its adaptation to national innovation system formation conditions in Ukraine were identified. By theoretical and empirical examining, the authors propose more complete understanding of modern ICT components, which are necessary for universities to participate in innovation networks. Cases of foreign experience in the scientific and innovation networks of current prototypes of Industry 4.0 development were investigated. Moreover, the evidence from this study suggests a variety of factors related to the possibilities to adapt ICT tools to national innovation system formation in Ukraine.

An Initial Framework for Implementation of Industry 4.0 in the High Technological Manufacturing Sector in Southern California

2019 ◽  
Author(s):  
Sagil James ◽  
Anupam Shetty
Keyword(s):  
Industry 4.0 ◽  
Southern California ◽  
Industrial Revolution ◽  
Manufacturing Sector ◽  
Smart Manufacturing ◽  
New Paradigm ◽  
Manufacturing Sectors ◽  
Southern California Region ◽  
The Internet Of Things ◽  
Initial Framework

Abstract The fourth industrial revolution, also known as Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Industry 4.0 synchronizes concepts such as Smart Manufacturing, Smart Factory, and the Internet of Things with existing factory automation technologies in order to improve value in manufacturing by monitoring key performance indicators and creates value in all manufacturing related aspects. Currently, several industries have started early initiatives of implementing these technologies. As the industries are evaluating their readiness for implementing the Industry 4.0 concepts, there are several challenges which need to be addressed including high initial investment, lack of standardization, data security and lack of skilled labor. A strategic roadmap towards implementing the Industry 4.0 paradigms is still unclear in the industry as well as in academia. This research develops an initial framework for the effective implementation of Industry 4.0 in the high technology manufacturing sectors in the Southern California region. The results of this study are expected to provide a platform to expand the opportunities of Industry 4.0 further and facilitate worldwide adoption.

scholarly journals The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review

2019 ◽  
Vol 9 (18) ◽  
pp. 3865 ◽  
Author(s):  
Mehrshad Mehrpouya ◽  
Amir Dehghanghadikolaei ◽  
Behzad Fotovvati ◽  
Alireza Vosooghnia ◽  
Sattar S. Emamian ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
Information Technologies ◽  
Manufacturing Systems ◽  
High Efficiency ◽  
Industrial Applications ◽  
Future Trend ◽  
Smart Manufacturing ◽  
The Future ◽  
Smart Manufacturing Systems

Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations.

scholarly journals Six-Gear Roadmap Towards the Smart Factory

2021 ◽  
Vol 11 (8) ◽  
pp. 3568
Author(s):  
Amr T. Sufian ◽  
Badr M. Abdullah ◽  
Muhammad Ateeq ◽  
Roderick Wah ◽  
David Clements
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Applications ◽  
Smart Manufacturing ◽  
Conceptual Approach ◽  
Industrial Manufacturing ◽  
Key Enabling Technologies ◽  
Manufacturing Technologies

The fourth industrial revolution is the transformation of industrial manufacturing into smart manufacturing. The advancement of digital technologies that make the trend Industry 4.0 are considered as the transforming force that will enable this transformation. However, Industry 4.0 digital technologies need to be connected, integrated and used effectively to create value and to provide insightful information for data driven manufacturing. Smart manufacturing is a journey and requires a roadmap to guide manufacturing organizations for its adoption. The objective of this paper is to review different methodologies and strategies for smart manufacturing implementation to propose a simple and a holistic roadmap that will support the transition into smart factories and achieve resilience, flexibility and sustainability. A comprehensive review of academic and industrial literature was preformed based on multiple stage approach and chosen criteria to establish existing knowledge in the field and to evaluate latest trends and ideas of Industry 4.0 and smart manufacturing technologies, techniques and applications in the manufacturing industry. These criteria are sub-grouped to fit within various stages of the proposed roadmap and attempts to bridge the gap between academia and industry and contributes to a new knowledge in the literature. This paper presents a conceptual approach based on six stages. In each stage, key enabling technologies and strategies are introduced, the common challenges, implementation tips and case studies of industrial applications are discussed to potentially assist in a successful adoption. The significance of the proposed roadmap serve as a strategic practical tool for rapid adoption of Industry 4.0 technologies for smart manufacturing and to bridge the gap between the advanced technologies and their application in manufacturing industry, especially for SMEs.

Design Framework for Preparing Workforce Towards Industry 4.0 Implementation in Small and Medium-Sized Enterprises

2020 ◽  
Author(s):  
Sagil James ◽  
Anupam Shetty
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Manufacturing Sector ◽  
Implementation Process ◽  
Secondary Data ◽  
Smart Manufacturing ◽  
New Paradigm ◽  
Skill Gaps ◽  
Adoption And Implementation ◽  
The Internet Of Things

Abstract The fourth industrial revolution, also known as Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Industry 4.0 synchronizes concepts such as Smart Manufacturing, Smart Factory, and the Internet of Things with existing factory automation technologies in order to improve value in manufacturing by monitoring key performance indicators and creates value in all manufacturing related aspects. Currently, several large companies industries have started early initiatives for implementing these technologies. However, small and medium-sized enterprises (SMEs) face massive challenges in adopting Industry 4.0 technologies. As the SMEs are evaluating their readiness for implementing the Industry 4.0 concepts, several challenges need to be addressed, including high initial investment, lack of standardization, data security, and lack of skilled labor. A strategic roadmap towards implementing the Industry 4.0 paradigms is still unclear in the SME sector as well as in academia. This research focuses on designing a framework for training/retraining the strong workforce for SMEs to enable Industry 4.0 adoption and implementation. The framework is created using qualitative research methods followed by the secondary data collection approach. The study suggests the use of a three-step implementation process consisting of 1) creating new jobs, 2) recruiting, and 3) retraining and retaining the talent. The results of this study are expected to create a platform to train the workforce for Industry 4.0, reduce skill gaps, and retain incumbent workers in the manufacturing sector.

Analyzing Industry4.0 Implementation Barriers in Indian SMEs

2021 ◽  
pp. 1-17
Author(s):  
Girish Kumar ◽  
Arjun Bakshi ◽  
Anurag Khandelwal ◽  
Anuj Panchal ◽  
Umang Soni
Keyword(s):  
Industry 4.0 ◽  
Developing Economies ◽  
Small And Medium Enterprises ◽  
Manufacturing Sector ◽  
Risk Mitigation ◽  
Substantial Contribution ◽  
Smart Manufacturing ◽  
Implementation Barriers ◽  
It Training ◽  
Medium Enterprises

Production in small and medium enterprises (SMEs) makes a substantial contribution to the Gross Domestic Product directly and indirectly in developing economies including India. In the present time, applying Industry 4.0 to the SMEs will build a smart manufacturing system that will prove to be economically feasible as well as socially sustainable. The purpose of this study is to identify and prioritize major barriers of implementing Industry 4.0 in Indian SMEs. A questionnaire with 12 barriers which were identified based on the literature survey and expert discussion was made to be filled by industry experts of production, information technology, business and members of the top management in SMEs. Further, Multi-Criteria Decision Making (MCDM) methods like TOPSIS, VIKOR and PROMETHEE are used to find the rank for each barrier. The study reveals that the major implementation barriers of Industry4.0 in Indian SMEs are fear of unemployment, lack of IT training, poor IT infrastructure, etc. The ranking for each barrier will not only help to assess risks in manufacturing, supply chain or business initiative, but also to help the managers in devising risk mitigation plans. This study may be used by firms working under the manufacturing sector.

Scalable Fully Bayesian Gaussian Process Modeling and Calibration with Adaptive Sequential Monte Carlo for Industrial Applications

2021 ◽  
pp. 1-11
Author(s):  
Piyush Pandita ◽  
Panagiotis Tsilifis ◽  
Sayan Ghosh ◽  
Liping Wang
Keyword(s):  
Monte Carlo ◽  
Big Data ◽  
Gaussian Process ◽  
Industry 4.0 ◽  
Large Scale ◽  
Sequential Monte Carlo ◽  
Industrial Applications ◽  
Computational Time ◽  
Mcmc Sampling ◽  
Gp Model

Abstract Gaussian Process (GP) regression or kriging has been extensively applied in the engineering literature for the purposes of building a cheap-to-evaluate surrogate, within the contexts of multi-fidelity modeling, model calibration and design optimization. With the ongoing automation of manufacturing and industrial practices as a part of Industry 4.0, there has been greater need for advancing GP regression techniques to handle challenges such as high input dimensionality, data paucity or big data problems, these consist primarily of proposing efficient design of experiments, optimal data acquisition strategies, and other mathematical tricks. In this work, our attention is focused on the challenges of efficiently training a GP model, which, to the authors opinion, has attracted very little attention and is to-date, poorly addressed. The performance of widely used training approaches such as maximum likelihood estimation and Markov Chain Monte Carlo (MCMC) sampling can deteriorate significantly in high dimensional and big data problems and can lead to cost deficient implementations of critical importance to many industrial applications. Here, we compare an Adaptive Sequential Monte Carlo (ASMC) sampling algorithm to classic MCMC sampling strategies and we demonstrate the effectiveness of our implementation on several mathematical problems and challenging industry applications of varying complexity. The computational time savings of our ASMC approach manifest in large-scale problems helping us to push the boundary of GP regression applicability and scalability in various domain of Industry 4.0, including but not limited to design automation, design engineering, predictive maintenance, and supply chain manufacturing.

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