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Machines
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Smart Manufacturing
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Smart Manufacturing

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 64925

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Zhuming Bi

E-Mail Website
Guest Editor
Department of Civil and Mechanical Engineering, Purdue University Fort Wayne, Fort Wayne, IN 46805, USA
Interests: mechanical engineering; robotics; manufacturing engineering; mechatronics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Li Da Xu

grade E-Mail Website
Guest Editor
Department of Information Technology, Old Dominion University, Norfolk, VA 23529, USA
Interests: industrial information integration engineering; industrial information systems; industrial informatics; enterprise systems
Special Issues, Collections and Topics in MDPI journals
Dr. Puren Ouyang

E-Mail Website
Guest Editor
Department of Aerospace Engineering, Ryerson University, 350 Victoria St, Toronto, ON M5B 2K3, Canada
Interests: mechatronics; robotics; control system; hybrid system; micro/nano engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Newly introduced enabling technologies, such as Industry 4.0, Internet of Things (IoT), Cyber-Physics System (CPS), Big Data Analytics (BDA), China Manufacturing 2025, and Cloud Computing (CC), have been changing the landscape of research and development (R&D) in Modern Manufacturing greatly; for examples, (1) the solutions of acquiring and transferring data are becoming affordable to instrument more and more ‘things’ and make them ‘smart’ in systems; (2) business related data is becoming bigger and bigger in terms of ‘volume’, ‘variety’, and ‘velocity’; where advanced data analytics is needed to capture, store, process, utilize data and assure the safety protection; (3) the boundary of a manufacturing system is becoming vaguer and vaguer; where enterprise architecture has to be adaptable to accommodate the needs of the collaborations with dynamic partners with respect to time. Manufacturing research is highly diversified due to the rapidly developed information technologies (ITs).

This special issue aims to explore the correlations of the aforementioned ITs with the emerging research topics in Smart Manufacturing. A paper on one or more of the following subjects is especially welcomed:

  • Literature review on the state of the art of manufacturing such as Smart Manufacturing, Sustainable Manufacturing, Cloud Manufacturing, and Digital Manufacturing
  • Cyber physical systems in manufacturing
  • Internet of Things in manufacturing
  • Big Data Analytics in manufacturing
  • Cloud-Computing in manufacturing
  • Enabling technologies for sustainable manufacturing
  • Adaptable enterprise architecture such as service-orientated architecture (SoA) and agent-based systems
  • Digital manufacturing
  • New sensors and controls for machine tools, fixtures, and other smart things
  • Data mining for planning, scheduling and controls
  • Development of intelligent systems such as robots, autonomous guided vehicles (AGVs), and other programmable manufacturing resources
  • Case studies in smart manufacturing

Prof. Dr. Zhuming Bi
Prof. Dr. Li Da Xu
Dr. Puren Ouyang
Guest Editors

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. Machines is an international peer-reviewed open access monthly 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.

Keywords

  • smart manufacturing
  • sustainable manufacturing
  • cloud manufacturing
  • digital manufacturing
  • sensors and actuators
  • advanced manufacturing
  • cyber-physics systems
  • internet of things
  • industry 4.0
  • big data analytics
  • literature survey
  • robotics and automation

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Published Papers (12 papers)

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Editorial

Jump to: Research, Review

4 pages, 198 KiB  
Editorial
Smart Manufacturing—Theories, Methods, and Applications
by Zhuming Bi, Lida Xu and Puren Ouyang
Machines 2022, 10(9), 742; https://doi.org/10.3390/machines10090742 - 29 Aug 2022
Cited by 4 | Viewed by 1892
Abstract
Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives [...] Full article
(This article belongs to the Special Issue Smart Manufacturing)

Research

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19 pages, 1719 KiB  
Article
Transformation towards a Smart Maintenance Factory: The Case of a Vessel Maintenance Depot
by Gwang Seok Kim and Young Hoon Lee
Machines 2021, 9(11), 267; https://doi.org/10.3390/machines9110267 - 2 Nov 2021
Cited by 3 | Viewed by 3349
Abstract
The conceptualization and framework of smart factories have been intensively studied in previous studies, and the extension to various business areas has been suggested as a future research direction. This paper proposes a method for extending the smart factory concept in the ship [...] Read more.
The conceptualization and framework of smart factories have been intensively studied in previous studies, and the extension to various business areas has been suggested as a future research direction. This paper proposes a method for extending the smart factory concept in the ship building phase to the ship servicing phase through actual examples. In order to expand the study, we identified the differences between manufacturing and maintenance. We proposed a smart transformation procedure, framework, and architecture of a smart maintenance factory. The transformation was a large-scale operation for the entire factory beyond simply applying a single process or specific technology. The transformations were presented through a vessel maintenance depot case and the effects of improvements were discussed. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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25 pages, 37041 KiB  
Article
Optimization of Material Supply in Smart Manufacturing Environment: A Metaheuristic Approach for Matrix Production
by Tamás Bányai
Machines 2021, 9(10), 220; https://doi.org/10.3390/machines9100220 - 29 Sep 2021
Cited by 15 | Viewed by 3359
Abstract
In the context of Industry 4.0, the matrix production developed by KUKA robotics represents a revolutionary solution for flexible manufacturing systems. Because of the adaptable and flexible manufacturing and material handling solutions, the design and control of these processes require new models and [...] Read more.
In the context of Industry 4.0, the matrix production developed by KUKA robotics represents a revolutionary solution for flexible manufacturing systems. Because of the adaptable and flexible manufacturing and material handling solutions, the design and control of these processes require new models and methods, especially from a real-time control point of view. Within the frame of this article, a new real-time optimization algorithm for in-plant material supply of smart manufacturing is proposed. After a systematic literature review, this paper describes a possible structure of the in-plant supply in matrix production environment. The mathematical model of the mentioned matrix production system is defined. The optimization problem of the described model is an integrated routing and scheduling problem, which is an NP-hard problem. The integrated routing and scheduling problem are solved with a hybrid multi-phase black hole and flower pollination-based metaheuristic algorithm. The computational results focusing on clustering and routing problems validate the model and evaluate its performance. The case studies show that matrix production is a suitable solution for smart manufacturing. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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19 pages, 2387 KiB  
Article
Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems
by Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo and Lida Xu
Machines 2021, 9(10), 208; https://doi.org/10.3390/machines9100208 - 23 Sep 2021
Cited by 14 | Viewed by 5186
Abstract
In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing [...] Read more.
In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing system aims to reconfigure different systems in achieving high-level smartness in its system lifecycle; moreover, each smart system is customized in terms of the constraints of manufacturing resources and the prioritized performance metrics to achieve system smartness. Few works were found on the development of systematic methodologies for the design of smart manufacturing systems. The novel contributions of the presented work are at two aspects: (1) unified definitions of digital functional elements and manufacturing systems have been proposed; they are generalized to have all digitized characteristics and they are customizable to any manufacturing system with specified manufacturing resources and goals of smartness and (2) a systematic design methodology has been proposed; it can serve as the guide for designs of smart manufacturing systems in specified applications. The presented work consists of two separated parts. In the first part of paper, a simplified definition of smart manufacturing (SM) is proposed to unify the diversified expectations and a newly developed concept digital triad (DT-II) is adopted to define a generic reference model to represent essential features of smart manufacturing systems. In the second part of the paper, the axiomatic design theory (ADT) is adopted and expanded as the generic design methodology for design, analysis, and assessment of smart manufacturing systems. Three case studies are reviewed to illustrate the applications of the proposed methodology, and the future research directions towards smart manufacturing are discussed as a summary in the second part. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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19 pages, 2095 KiB  
Article
Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model
by Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo and Lida Xu
Machines 2021, 9(10), 207; https://doi.org/10.3390/machines9100207 - 23 Sep 2021
Cited by 12 | Viewed by 4983
Abstract
Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers [...] Read more.
Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited in two aspects: (1) the highly diversified understandings of SM may lead to overlapped, missed, and non-systematic research efforts in advancing the theory and methodologies in the field of SM; (2) few works have been found that focus on the development of generic design methodologies for smart manufacturing systems from the practice perspective. The novelty of this paper consists of two main aspects which are reported in two parts respectively. In the first part, a simplified definition of SM is proposed to unify the existing diversified expectations, and a newly developed concept named digital triad (DT-II) is adopted to define a reference model for SM. The common features of smart manufacturing systems in various applications are identified as functional requirements (FRs) in systems design. To model a system that is capable of reconfiguring itself to adapt to changes, the concept of IoDTT is proposed as a reference model for smart manufacturing systems. In the second part, these two concepts are used to formulate a system design problem, and a generic methodology, based on axiomatic design theory (ADT), is proposed for the design of smart manufacturing systems. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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34 pages, 1563 KiB  
Article
Blockchain-Empowered Digital Twins Collaboration: Smart Transportation Use Case
by Radhya Sahal, Saeed H. Alsamhi, Kenneth N. Brown, Donna O’Shea, Conor McCarthy and Mohsen Guizani
Machines 2021, 9(9), 193; https://doi.org/10.3390/machines9090193 - 9 Sep 2021
Cited by 88 | Viewed by 8276
Abstract
Digital twins (DTs) is a promising technology in the revolution of the industry and essential for Industry 4.0. DTs play a vital role in improving distributed manufacturing, providing up-to-date operational data representation of physical assets, supporting decision-making, and avoiding the potential risks in [...] Read more.
Digital twins (DTs) is a promising technology in the revolution of the industry and essential for Industry 4.0. DTs play a vital role in improving distributed manufacturing, providing up-to-date operational data representation of physical assets, supporting decision-making, and avoiding the potential risks in distributed manufacturing systems. Furthermore, DTs need to collaborate within distributed manufacturing systems to predict the risks and reach consensus-based decision-making. However, DTs collaboration suffers from single failure due to attack and connection in a centralized manner, data interoperability, authentication, and scalability. To overcome the above challenges, we have discussed the major high-level requirements for the DTs collaboration. Then, we have proposed a conceptual framework to fulfill the DTs collaboration requirements by using the combination of blockchain, predictive analysis techniques, and DTs technologies. The proposed framework aims to empower more intelligence DTs based on blockchain technology. In particular, we propose a concrete ledger-based collaborative DTs framework that focuses on real-time operational data analytics and distributed consensus algorithms. Furthermore, we describe how the conceptual framework can be applied using smart transportation system use cases, i.e., smart logistics and railway predictive maintenance. Finally, we highlighted the future direction to guide interested researchers in this interesting area. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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17 pages, 4298 KiB  
Article
A Product Conceptual Design Method Based on Evolutionary Game
by Yun-Liang Huo, Xiao-Bing Hu, Bo-Yang Chen and Ru-Gu Fan
Machines 2019, 7(1), 18; https://doi.org/10.3390/machines7010018 - 5 Mar 2019
Cited by 11 | Viewed by 5171
Abstract
In this paper, an intelligent-design method to deal with conceptual optimization is proposed for the decisive impact of the concept on the product-development cycle cost and performance. On the basis of matter-element analysis, an effective functional-structure combination model satisfying multiple constraints is first [...] Read more.
In this paper, an intelligent-design method to deal with conceptual optimization is proposed for the decisive impact of the concept on the product-development cycle cost and performance. On the basis of matter-element analysis, an effective functional-structure combination model satisfying multiple constraints is first established, which maps the product characteristics obtained by expert research and customer-requirements analysis of the function and structure domain. Then, the Evolutionary Game Algorithm (EGA) was utilized to solve the model, in which a strategy-combination space is mapped to the solution-search space of the conceptual-solution problem, and the game-utility function is mapped to the objective functions of concept evaluation. Constant disturbance and Best-Response Correspondence were applied cross-repeatedly until the optimal equilibrium Pareto state corresponding to the global optimal solution was obtained. Finally, the method was simulated on MATLAB 8.3 and applied to the design for fixed winch hoist, which greatly shortens its design cycle. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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13 pages, 4208 KiB  
Article
Application of IoT-Aided Simulation to Manufacturing Systems in Cyber-Physical System
by Yifei Tan, Wenhe Yang, Kohtaroh Yoshida and Soemon Takakuwa
Machines 2019, 7(1), 2; https://doi.org/10.3390/machines7010002 - 3 Jan 2019
Cited by 58 | Viewed by 8160
Abstract
With the rapid development of mobile and wireless networking technologies, data has become more ubiquitous and the IoT (Internet of Things) is attracting much attention due to high expectations for enabling innovative service, efficiency, and productivity improvement. In next-generation manufacturing, the digital twin [...] Read more.
With the rapid development of mobile and wireless networking technologies, data has become more ubiquitous and the IoT (Internet of Things) is attracting much attention due to high expectations for enabling innovative service, efficiency, and productivity improvement. In next-generation manufacturing, the digital twin (DT) has been proposed as a new concept and simulation tool for collecting and synchronizing real-world information in real time in cyber space to cope with the challenges of smart factories. Although the DT is considered a challenging technology, it is still at the conceptual stage and only a few studies have specifically discussed methods for its construction and implementation. In this study, we first explain the concept of DT and important issues involved in developing it within an IoT-aided manufacturing environment. Then, we propose a DT construction framework and scheme for inputting data derived from the IoT into a simulation model. Finally, we describe how we verify the effectiveness of the proposed framework and scheme, by constructing a DT-oriented simulation model for an IoT-aided manufacturing system. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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13 pages, 6627 KiB  
Article
Automatic Test and Sorting System for the Slide Valve Body of Oil Control Valve Based on Cartesian Coordinate Robot
by Pingping Liu, Gangjun Li, Rui Su and Guang Wen
Machines 2018, 6(4), 64; https://doi.org/10.3390/machines6040064 - 13 Dec 2018
Cited by 2 | Viewed by 4753
Abstract
Current industrial robotics technology is often not well integrated with the enterprise’s on-site environment and actual working conditions and small and medium-sized enterprises are unable to achieve product automation due to production cost constraints. In order to meet the medium and small scale [...] Read more.
Current industrial robotics technology is often not well integrated with the enterprise’s on-site environment and actual working conditions and small and medium-sized enterprises are unable to achieve product automation due to production cost constraints. In order to meet the medium and small scale production of the slide valve body of OCV (Oil Control Valve) of a certain enterprise and its special process requirements, the automatic test system and sorting system based on the production environment of the enterprise are studied and designed. Firstly, according to the production conditions and process requirements of the enterprise, the overall design scheme of the automatic production line is put forward based on the existing automatic assembly system. Secondly, the test description is further improved by analysing and interpreting the test requirements of the products in detail and the automatic test system and test process are designed. Finally, according to the sorting process requirements, a Cartesian coordinate robot sorting system with two-terminal manipulators parallel operation is designed and its sorting motion scheme is optimized. The automatic test system and sorting system are seamlessly connected with the automatic assembly system, which can efficiently complete the automatic test and sorting of products and meet the production cycle time. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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25 pages, 5051 KiB  
Article
Smart Hybrid Manufacturing Control Using Cloud Computing and the Internet-of-Things
by Jonnro Erasmus, Paul Grefen, Irene Vanderfeesten and Konstantinos Traganos
Machines 2018, 6(4), 62; https://doi.org/10.3390/machines6040062 - 3 Dec 2018
Cited by 26 | Viewed by 6337
Abstract
Industry 4.0 is expected to deliver significant gains in productivity by assimilating several technological advancements including cloud computing, the Internet-of-Things, and smart devices. However, it is unclear how these technologies should be leveraged together to deliver the promised benefits. We present the architecture [...] Read more.
Industry 4.0 is expected to deliver significant gains in productivity by assimilating several technological advancements including cloud computing, the Internet-of-Things, and smart devices. However, it is unclear how these technologies should be leveraged together to deliver the promised benefits. We present the architecture design of an information system that integrates these technologies to support hybrid manufacturing processes, i.e., processes in which human and robotic workers collaborate. We show how well-structured architecture design is the basis for a modular, complex cyber-physical system that provides horizontal, cross-functional manufacturing process management and vertical control of heterogenous work cells. The modular nature allows the extensible cloud support enhancing its accessibility to small and medium enterprises. The information system is designed as part of the HORSE Project: a five-year research and innovation project aimed at making recent technological advancements more accessible to small and medium manufacturing enterprises. The project consortium includes 10 factories to represent the typical problems encountered on the factory floor and provide real-world environments to test and evaluate the developed information system. The resulting information system architecture model is proposed as a reference architecture for a manufacturing operations management system for Industry 4.0. As a reference architecture, it serves two purposes: (1) it frames the scientific inquiry and advancement of information systems for Industry 4.0 and (2) it can be used as a template to develop commercial-grade manufacturing applications for Industry 4.0. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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19 pages, 6130 KiB  
Article
Analysis of Vibration Plate Cracking Based on Working Stress
by Zeyu Kang, Gangjun Li, Fujun Wang, Huan Zhang and Rui Su
Machines 2018, 6(4), 51; https://doi.org/10.3390/machines6040051 - 26 Oct 2018
Cited by 1 | Viewed by 4619
Abstract
At present, vibroseis has become the major technique to achieve environmental protection and high efficiency in fossil fuel exploration. During such exploration, a vibrator transmits seismic waves to the surface. The waves are excited by continuously changing the load stress from the burden [...] Read more.
At present, vibroseis has become the major technique to achieve environmental protection and high efficiency in fossil fuel exploration. During such exploration, a vibrator transmits seismic waves to the surface. The waves are excited by continuously changing the load stress from the burden of weight of the vehicle and the vibrator’s variable frequency load. This paper will apply a numerical simulation method to develop research on the analysis of vibration plate cracking based on working stress. Based on the structure and mechanism of vibroseis vibrator plate, a vibrator simulation model is built under system dynamics to develop research on the vibroseis plate load stress feature and gain distribution, and change pattern of the plate load stress. The results show that stress response around the upright welding of is high, and there is evident distortion in plate area, which matches the actual fracture position on the plate, and can be confirmed as a key area of plate fatigue. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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Review

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18 pages, 579 KiB  
Review
A Systematic Review of Product Design for Space Instrument Innovation, Reliability, and Manufacturing
by Kai-Leung Yung, Yuk-Ming Tang, Wai-Hung Ip and Wei-Ting Kuo
Machines 2021, 9(10), 244; https://doi.org/10.3390/machines9100244 - 19 Oct 2021
Cited by 13 | Viewed by 3462
Abstract
The design and development of space instruments are considered to be distinct from that of other products. It is because the key considerations are vastly different from those that govern the use of products on planet earth. The service life of a space [...] Read more.
The design and development of space instruments are considered to be distinct from that of other products. It is because the key considerations are vastly different from those that govern the use of products on planet earth. The service life of a space instrument, its use in extreme space environments, size, weight, cost, and the complexity of maintenance must all be considered. As a result, more innovative ideas and resource support are required to assist mankind in space exploration. This article reviews the impact of product design and innovation on the development of space instruments. Using a systematic literature search review and classification, we have identified over 129 papers and finally selected 48 major articles dealing with space instrument product innovation design. According to the studies, it is revealed that product design and functional performance is the main research focuses on the studied articles. The studies also highlighted various factors that affect space instrument manufacturing or fabrication, and that innovativeness is also the key in the design of space instruments. Lastly, the product design is important to affect the reliability of the space instrument. This review study provides important information and key considerations for the development of smart manufacturing technologies for space instruments in the future. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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