scholarly journals Systematic Literature Review Predictive Maintenance Solutions for SMEs from the Last Decade

Machines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 191
Author(s):  
Sepideh Hassankhani Dolatabadi ◽  
Ivana Budinska
Keyword(s):  
Environmental Factors ◽  
Literature Review ◽  
Rapid Growth ◽  
Industry 4.0 ◽  
Predictive Maintenance ◽  
Smart Manufacturing ◽  
Equipment Failure ◽  
Specific Category ◽  
Low Costs ◽  
Manufacturing Technologies

Today, small- and medium-sized enterprises (SMEs) play an important role in the economy of societies. Although environmental factors, such as COVID-19, as well as non-environmental factors, such as equipment failure, make these industries more vulnerable, they can be minimized by better understanding the concerns and threats these industries face. Only a few SMEs have the capacity to implement the innovative manufacturing technologies of Industry 4.0. The system must be highly adaptable to any equipment, have low costs, avoid the need of doing complex integrations and setups, and have future reliability due to the rapid growth of technology. The goal of this study was to provide an overview of past articles (2010–2020), highlighting the major expectations, requirements, and challenges for SMEs regarding the implementation of predictive maintenance (PdM). The proposed solutions to meet these expectations, requirements, and challenges are discussed. In general, in this study, we attempted to overcome the challenges and limitations of using smart manufacturing—PdM, in particular—in small- and medium-sized enterprises by summarizing the solutions offered in different industries and with various conditions. Moreover, this literature review enables managers and stakeholders of organizations to find solutions from previous studies for a specific category, with consideration for their expectations and needs. This can be significantly helpful for small- and medium-sized organizations to save time due to time-consuming maintenance processes.

scholarly journals Exploring the Interrelationship between Additive Manufacturing and Industry 4.0

Designs ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 13 ◽  
Author(s):  
Javaid Butt
Keyword(s):  
Additive Manufacturing ◽  
Literature Review ◽  
Industry 4.0 ◽  
Data Exchange ◽  
Smart Manufacturing ◽  
Cognitive Computing ◽  
Digital Twins ◽  
Technological Developments ◽  
Manufacturing Techniques ◽  
Manufacturing Technologies

Innovative technologies allow organizations to remain competitive in the market and increase their profitability. These driving factors have led to the adoption of several emerging technologies and no other trend has created more of an impact than Industry 4.0 in recent years. This is an umbrella term that encompasses several digital technologies that are geared toward automation and data exchange in manufacturing technologies and processes. These include but are not limited to several latest technological developments such as cyber-physical systems, digital twins, Internet of Things, cloud computing, cognitive computing, and artificial intelligence. Within the context of Industry 4.0, additive manufacturing (AM) is a crucial element. AM is also an umbrella term for several manufacturing techniques capable of manufacturing products by adding layers on top of each other. These technologies have been widely researched and implemented to produce homogeneous and heterogeneous products with complex geometries. This paper focuses on the interrelationship between AM and other elements of Industry 4.0. A comprehensive AM-centric literature review discussing the interaction between AM and Industry 4.0 elements whether directly (used for AM) or indirectly (used with AM) has been presented. Furthermore, a conceptual digital thread integrating AM and Industry 4.0 technologies has been proposed. The need for such interconnectedness and its benefits have been explored through the content-centric literature review. Development of such a digital thread for AM will provide significant benefits, allow companies to respond to customer requirements more efficiently, and will accelerate the shift toward smart manufacturing.

scholarly journals Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System

2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Design Feature ◽  
Production Equipment ◽  
Smart Manufacturing ◽  
Process Data ◽  
Industrial Sectors ◽  
Advanced Manufacturing Technologies ◽  
Manufacturing Technologies ◽  
Equipment Application ◽  
The Impact

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.

Predictive maintenance in the Industry 4.0: A systematic literature review

2020 ◽  
Vol 150 ◽  
pp. 106889
Author(s):  
Tiago Zonta ◽  
Cristiano André da Costa ◽  
Rodrigo da Rosa Righi ◽  
Miromar José de Lima ◽  
Eduardo Silveira da Trindade ◽  
...  
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Industry 4.0 ◽  
Predictive Maintenance

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.

scholarly journals Cutting Tool Wearing Identification Through Predictive Maintenance and Its Impact on Surface Quality

2021 ◽  
Author(s):  
Jose Maria Gonzalez Castro ◽  
Giselle Ramirez Sandoval ◽  
Eduard Vidales Coca ◽  
Nuri Cuadrado Lafoz ◽  
Francesc Bonada
Keyword(s):  
Surface Quality ◽  
Industry 4.0 ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Predictive Maintenance ◽  
Smart Manufacturing ◽  
Long Time ◽  
The Media ◽  
Tool Vibrations

Smart manufacturing has been in the media for a long time, but the reality shows that traditional mechanical manufacturing industries have not been able to implement data solutions aligned with Industry 4.0 standards. This work inquiries into the possibility of measuring cutting tool vibrations for CNC turning machines and presents the data analysis and a predictive model to identify tool wearing that can affects integrity surface quality of the manufactured component. These preliminary results are orientated towards implementing a predictive maintenance methodology in cutting tools.

scholarly journals A Systematic Literature Review of Industry 4.0 Technologies within Medical Device Manufacturing

2021 ◽  
Vol 13 (10) ◽  
pp. 264
Author(s):  
Tuuli Katarina Lepasepp ◽  
William Hurst
Keyword(s):  
Literature Review ◽  
Medical Device ◽  
Systematic Literature Review ◽  
Digital Libraries ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
New Technologies ◽  
Quality Analysis ◽  
Smart Manufacturing ◽  
Synonymous Term

Ever since the emergence of Industry 4.0 as the synonymous term for the fourth industrial revolution, its applications have been widely discussed and used in many business scenarios. This concept is derived from the advantages of internet and technology, and it describes the efficient synchronicity of humans and computers in smart factories. By leveraging big data analysis, machine learning and robotics, the end-to-end supply chain is optimized in many ways. However, these implementations are more challenging in heavily regulated fields, such as medical device manufacturing, as incorporating new technologies into factories is restricted by the regulations in place. Moreover, the production of medical devices requires an elaborate quality analysis process to assure the best possible outcome to the patient. Therefore, this article reflects on the benefits (features) and limitations (obstacles), in addition to the various smart manufacturing trends that could be implemented within the medical device manufacturing field by conducting a systematic literature review of 104 articles sourced from four digital libraries. Out of the 7 main themes and 270 unique applied technologies, 317 features and 117 unique obstacles were identified. Furthermore, the main findings include an overview of ways in which manufacturing could be improved and optimized within a regulated setting, such as medical device manufacturing.

scholarly journals Decision Making in Predictive Maintenance: Literature Review and Research Agenda for Industry 4.0

2019 ◽  
Vol 52 (13) ◽  
pp. 607-612 ◽  
Author(s):  
Alexandros Bousdekis ◽  
Katerina Lepenioti ◽  
Dimitris Apostolou ◽  
Gregoris Mentzas
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Research Agenda ◽  
Industry 4.0 ◽  
Predictive Maintenance

scholarly journals Reference Architectures for Industry 4.0: Literature Review

2020 ◽  
Author(s):  
Alexandre Helmann ◽  
Fernando Deschamps ◽  
Eduardo de Freitas Rocha Loures
Keyword(s):  
Literature Review ◽  
System Architecture ◽  
Industry 4.0 ◽  
New Technologies ◽  
Production Systems ◽  
Smart Manufacturing ◽  
Automation System ◽  
Manufacturing Processes ◽  
Direct Integration

Currently, production systems are receiving the application of more advanced, integrated and connected technologies to optimize the performance of their manufacturing processes. The new technological solutions demand architectures that support intelligent solutions for a new digitalized industry. However, production systems already in operation have difficulty in implementing these technologies. The existing barriers limit the availability of the direct integration of different systems contemplated in an automation system architecture. This article systematically reviews the existing literature to portray the characteristics of each architecture and that can guide the adoption of new technologies. Through this review, emerging reference architectures were identified, such as RAMI4.0, IIRA, IBM Industry 4.0 and NIST Smart Manufacturing. In conclusion, the article presents a framework for considering which model best fits with the new technological solutions.

scholarly journals Research and Finding Technical Enablers using Ism for Industry 4.0 in Indian Agricultural Industries

2019 ◽  
Vol 8 (11S) ◽  
pp. 137-141 ◽  
Keyword(s):  
Literature Review ◽  
Industry 4.0 ◽  
Learning Technologies ◽  
Smart Manufacturing ◽  
Automation System ◽  
Agricultural Field ◽  
International Benchmarking ◽  
Individual Industry ◽  
Agricultural Industries ◽  
Indian Industries

At the present scenario, agriculture industries are working hard to produce farmer satisfied products at affordable cost. The globalization and heavy worldwide competition stress them to precise and sustain in the market. The existing system are to be modified for smart manufacturing to cop up international benchmarking. The modifications consist of modern machine tools, automation system, machine learning technologies and systematic approach. The existing system and path for every individual industry are unique. Here the skill needed is to fit suitable enablers to the factors. The enactment of Industry 4.0 appropriately to industry is a task, because different industries lie at different sectors. In this context a study is carried to identify the important technological enablers for the enactment of Industry 4.0 in Indian agricultural industries. Various enablers essential for implementing Industry 4.0 has been identified from literature review. The Interpretive structural modelling(ISM) is employed for finding the mutual relationship among the enablers. Data collected to rank the enablers in the agricultural field. The technological enablers are further being classified as dependent and driving factors. Thus a hypothetical model is created based on literature review. A proper acknowledgement of interactions among enablers will help organization to rank the factors and manage these factors with more efficiency to produce advantages of implementing Industry 4.0. This paper is aiming to identify the various enablers to implement Industry4.0 in Indian industries.

Sociotechnical factors and Industry 4.0: an integrative perspective for the adoption of smart manufacturing technologies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Érico Marcon ◽  
Marlon Soliman ◽  
Wolfgang Gerstlberger ◽  
Alejandro G. Frank
Keyword(s):  
Technology Adoption ◽  
Industry 4.0 ◽  
Empirical Studies ◽  
Work Organization ◽  
Organizational Factors ◽  
Smart Manufacturing ◽  
Manufacturing Companies ◽  
Content Type ◽  
Manufacturing Technologies ◽  
Systemic View

PurposeAs the level of implementation of Industry 4.0 increases, misalignments between adopted technologies and organizational factors may result in benefits below expected. This paper aims to analyze how organizational factors can contribute to a higher level of adoption of Industry 4.0 technologies. The paper uses a sociotechnical perspective lens to achieve this aim.Design/methodology/approachUsing a sample of 231 manufacturing companies in Denmark, a leading country in Industry 4.0 readiness, the paper analyzes through cluster analysis and logistic regression whether the development of four sociotechnical dimensions – that is, Social, Technical, Work Organization and Environmental factors – in these companies can benefit the achievement of higher levels of Industry 4.0 technology adoption.FindingsThe results show that companies focused on the development of sociotechnical aspects generally present higher Industry 4.0 adoption levels. However, some sociotechnical factors are less supportive than others.Originality/valueBased on these results, practitioners can plan the adoption of advanced technologies, using a systemic organizational view. This study provides evidence on a growing field with few empirical studies available. The paper contributes by providing an analysis of a leading country in Industry 4.0 implementation, presenting a systemic view on technology adoption in the Industry 4.0 context.

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