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Industry 4.0 Based Smart Manufacturing Systems
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Industry 4.0 Based Smart Manufacturing Systems

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 May 2021) | Viewed by 57779

Special Issue Editor

Prof. Dr. Tobias Meisen

E-Mail Website
Guest Editor
School of Electrical, Information and Media Engineering, University of Wuppertal, Rainer-Gruenter-Str. 21, D-42119 Wuppertal, Germany
Interests: deep and machine learning; knowledge graphs; semantic interoperability; transfer learning; explainable and transparent artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In a traditional way, manufacturing means the engineering process of creating industrial products from raw materials using a variety of subtractive and additive methods. However, in recent years, the concept of manufacturing has drastically shifted. After the first wave of digitization, new and modernized technologies such as integrated sensors, advanced robotics, and artificial intelligence led to the so-called Smart Manufacturing as part of the fourth industrial revolution—often referred to as Industry 4.0. In Smart Manufacturing, production tools are connected to constantly gather data, monitor production processes, and perform real-time optimization. Smart Manufacturing therefore includes not only data collection and processing, but also inferring from and reasoning about data by means of cognitive computing to improve the end product. In doing so, the vision of Smart Manufacturing leads to a self-monitoring and self-optimization of the entire end-to-end manufacturing process.

The key challenges of Smart Manufacturing are manifold, and several aspects need to be taken into consideration:

  • New ways of data acquisition that require implementing new sensors and the capability for connectivity in production machines and products, as well as new ways to store and propagate such data in a meaningful way;
  • Employing data science approaches to automate or optimize manufacturing to remove ‘trial-and-error’ approaches;
  • Developing new robotics and closed loop control feedback at the hardware level;
  • Sustainably transferring and deploying solutions into the world while addressing broader clean energy challenges and reducing material waste for the environment.

Industry 4.0 adds, among other things, aspects of business model development to this mostly technological perspective. The new value of data leads to new and changed business models and opportunities regarding the internal optimization of business processes. However, we have not yet fully understood how data can be managed as a central resource and how the full potential of data as a resource can be harnessed.

The aim of the edition “Industry 4.0-Based Smart Manufacturing Systems” is therefore to present new and innovative methods in which data can be better and more efficiently extracted, collected, processed, and finally used in Smart Manufacturing environments.

Prof. Dr. Tobias Meisen
Guest Editor

Manuscript Submission Information

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Keywords

  • Smart Manufacturing
  • Industry 4.0
  • Artificial intelligence
  • Data-driven production
  • Interoperability
  • Data as an asset

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Published Papers (14 papers)

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28 pages, 5152 KiB  
Article
Smart Factory Web—A Blueprint Architecture for Open Marketplaces for Industrial Production
by Thomas Usländer, Felix Schöppenthau, Boris Schnebel, Sascha Heymann, Ljiljana Stojanovic, Kym Watson, Seungwook Nam and Satoshi Morinaga
Appl. Sci. 2021, 11(14), 6585; https://doi.org/10.3390/app11146585 - 17 Jul 2021
Cited by 17 | Viewed by 6225
Abstract
The paper describes a reference architecture for open marketplaces to be used for networked stakeholders in industrial production ecosystems. The motivation for such an endeavor comes from the idea to apply the basic principle of the platform economy to offer functions of an [...] Read more.
The paper describes a reference architecture for open marketplaces to be used for networked stakeholders in industrial production ecosystems. The motivation for such an endeavor comes from the idea to apply the basic principle of the platform economy to offer functions of an asset “as a service” to industrial production, including the associated supply chain networks. Currently, commercial offers of “production as a service” usually lead to proprietary systems with the risk of platform vendor lock-ins. Hence, there is a need for an open approach that relies upon international (emerging) standards, especially those from IETF, IEC, the Plattform Industrie 4.0 and the International Data Spaces Association (IDSA). The presented approach enables federation of marketplaces according to well-defined interfaces. This article proposes a technology-independent open architecture derived from functional and non-functional system requirements and driven by the idea of the Smart Factory Web, a testbed of the Industrial Internet Consortium (IIC). Furthermore, the architecture of the Smart Factory Web (SFW) platform is presented and assessed against the current and future demands of open federated marketplaces for industrial production ecosystems. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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17 pages, 2121 KiB  
Article
A Framework for Assessing Manufacturing SMEs Industry 4.0 Maturity
by Afonso Amaral and Paulo Peças
Appl. Sci. 2021, 11(13), 6127; https://doi.org/10.3390/app11136127 - 30 Jun 2021
Cited by 54 | Viewed by 5436
Abstract
Under the scenario of the fourth industrial revolution, the adoption of Industry 4.0 in the day-to-day business of small and medium enterprises (SME) entails expected challenges. Focusing primarily on more advanced levels of maturity, the existing maturity models are inadequate for assessing companies [...] Read more.
Under the scenario of the fourth industrial revolution, the adoption of Industry 4.0 in the day-to-day business of small and medium enterprises (SME) entails expected challenges. Focusing primarily on more advanced levels of maturity, the existing maturity models are inadequate for assessing companies with low maturity levels, such as most of existing SMEs. A framework for a maturity model tailored to SMEs is proposed in this paper, allowing for a comprehensive and high granularity assessment of these companies’ maturity levels, which then eases their integration into this industrial revolution. The proposed holistic model considers all Industry 4.0 dimensions while being detailed enough in its initial levels to properly assess SMEs at the same time. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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18 pages, 9403 KiB  
Article
Wireless Sensor Network Aided Assembly Line Monitoring According to Expectations of Industry 4.0
by László Gogolák and Igor Fürstner
Appl. Sci. 2021, 11(1), 25; https://doi.org/10.3390/app11010025 - 22 Dec 2020
Cited by 9 | Viewed by 2600
Abstract
Striving for excellence during the assembling process through incorporating the expectations of Industry 4.0 requires complex information management on issues of overall system status, especially the physical characteristics and position of the parts being assembled, as well as the assembling units and tools. [...] Read more.
Striving for excellence during the assembling process through incorporating the expectations of Industry 4.0 requires complex information management on issues of overall system status, especially the physical characteristics and position of the parts being assembled, as well as the assembling units and tools. This research introduces both an overall customized assembling system supervision model, which is based on a modified four-layer control system hierarchy that suits the specific requirements of such systems and the developed wireless sensor network technology for assembling process management with a particular focus on localization. The developed model highlights the localization problems of the system as well as other aspects required for overall system status determination. The localization of assembled parts is based on the fingerprint localization method by using the received signal strength indicator. The proposed localization algorithms are based either on artificial neural networks or on the weighted k-nearest neighbor method. The developed model has been tested both in laboratory conditions and in a simulated industrial environment. The research results offer a general solution to the problem of assembling system supervision, regardless of size and shape, with emphasis on the localization problem solution. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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17 pages, 4095 KiB  
Article
Development of a New KPI for the Economic Quantification of Six Big Losses and Its Implementation in a Cyber Physical System
by Paula Morella, María Pilar Lambán, Jesús Royo, Juan Carlos Sánchez and Jaime Latapia
Appl. Sci. 2020, 10(24), 9154; https://doi.org/10.3390/app10249154 - 21 Dec 2020
Cited by 7 | Viewed by 4127
Abstract
The purpose of this work is to develop a new Key Performance Indicator (KPI) that can quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber Physical System (CPS), achieving a real-time monitorization of the KPI. This [...] Read more.
The purpose of this work is to develop a new Key Performance Indicator (KPI) that can quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber Physical System (CPS), achieving a real-time monitorization of the KPI. This paper follows the methodology explained below. A cost model has been used to accurately develop this indicator together with the Six Big Losses description. At the same time, the machine tool has been integrated into a CPS, enhancing the real-time data acquisition, using the Industry 4.0 technologies. Once the KPI has been defined, we have developed the software that can turn these real-time data into relevant information (using Python) through the calculation of our indicator. Finally, we have carried out a case of study showing our new KPI results and comparing them to other indicators related with the Six Big Losses but in different dimensions. As a result, our research quantifies economically the Six Big Losses, enhances the detection of the bigger ones to improve them, and enlightens the importance of paying attention to different dimensions, mainly, the productive, sustainable, and economic at the same time. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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20 pages, 9546 KiB  
Article
Analysis of a Novel Automatic Control Approach for the Free Forging Hammer
by Xiaopeng Yan and Baijin Chen
Appl. Sci. 2020, 10(24), 9127; https://doi.org/10.3390/app10249127 - 21 Dec 2020
Cited by 3 | Viewed by 3193
Abstract
This paper proposes an electro-hydraulic servo control method and realizes the automatic control and remote control of free forging hammers for the first time. A configuration and control strategy for the program-control free forging hammer are constructed. Based on the configuration, a single-acting [...] Read more.
This paper proposes an electro-hydraulic servo control method and realizes the automatic control and remote control of free forging hammers for the first time. A configuration and control strategy for the program-control free forging hammer are constructed. Based on the configuration, a single-acting differential servo cylinder system is proposed to drive the follow-up spool valve and then control the motion state of the hammerhead. Furthermore, a non-contact measurement method is adopted to detect the real-time position of the hammerhead, and the installation position of the measuring sensor is isolated from the hammer body and foundation, thereby reducing the influence of vibration and impact on the accuracy of the feedback signal and ensuring the successive forming process of the forging hammer. In addition, a blow energy model of the forging hammer processing system is established, and a fuzzy-PID control scheme for the forging hammer is then adopted. Based on the control strategy, the striking accuracy of the proposed automatic forging hammer is significantly improved compared with the traditional forging hammer. Finally, the method is applied to an 8 MN forging hammer, and the results show its better processing performance than traditional hammers in terms of all indices. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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17 pages, 573 KiB  
Article
On Ad Hoc Communication in Industrial Environments
by Christian Sauer, Marco Schmidt and Eike Lyczkowski
Appl. Sci. 2020, 10(24), 9126; https://doi.org/10.3390/app10249126 - 21 Dec 2020
Cited by 6 | Viewed by 2284
Abstract
Wireless communication is becoming vital in the industrial environment. New communication technologies, including ad hoc communication, are researched for this application. A thorough understanding regarding the connection characteristics of industrial networks could benefit this trend. In this work it was possible to record [...] Read more.
Wireless communication is becoming vital in the industrial environment. New communication technologies, including ad hoc communication, are researched for this application. A thorough understanding regarding the connection characteristics of industrial networks could benefit this trend. In this work it was possible to record the time-variant network topology of such a network utilizing a novel method. Using this method and the generated recordings, novel insights into the behavior of industrial ad hoc networks are presented. The recorded time-variant topology, the tools and method of acquisition, and tools for processing and examination are published. This enables researchers and engineers to check their communication technologies in terms of applicability to the industrial use case and record more network topologies in a wide variety of wireless networking scenarios. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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13 pages, 469 KiB  
Article
Anode Effect Prediction in Hall-Héroult Cells Using Time Series Characteristics
by Ron Kremser, Niclas Grabowski, Roman Düssel, Albert Mulder and Dietmar Tutsch
Appl. Sci. 2020, 10(24), 9050; https://doi.org/10.3390/app10249050 - 18 Dec 2020
Cited by 4 | Viewed by 4889
Abstract
In aluminium production, anode effects occur when the alumina content in the bath is so low that normal fused salt electrolysis cannot be maintained. This is followed by a rapid increase of pot voltage from about 4.3 V to values in the range [...] Read more.
In aluminium production, anode effects occur when the alumina content in the bath is so low that normal fused salt electrolysis cannot be maintained. This is followed by a rapid increase of pot voltage from about 4.3 V to values in the range from 10 to 80 V. As a result of a local depletion of oxide ions, the cryolite decomposes and forms climate-relevant perfluorocarbon (PFC) gases. The high pot voltage also causes a high energy input, which dissipates as heat. In order to ensure energy-efficient and climate-friendly operation, it is important to predict anode effects in advance so that they can be prevented by prophylactic actions like alumina feeding or beam downward movements. In this paper a classification model is trained with aggregated time series data from TRIMET Aluminium SE Essen (TAE) that is able to predict anode effects at least 1 min in advance. Due to a high imbalance in the class distribution of normal state and labeled anode effect state as well as possible model’s weaknesses the final F1 score of 32.4% is comparatively low. Nevertheless, the prediction provides an indication of possible anode effects and the process control system may react on it. Consequent practical implications will be discussed. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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22 pages, 6236 KiB  
Article
Safe Three-Dimensional Assembly Line Design for Robots Based on Combined Multiobjective Approach
by Shuai Wang, Ruifeng Guo, Hongliang Wang and Birgit Vogel-Heuser
Appl. Sci. 2020, 10(24), 8844; https://doi.org/10.3390/app10248844 - 10 Dec 2020
Cited by 2 | Viewed by 2388
Abstract
In advanced industrial automation, industrial robots have been widely utilized on assembly lines in order to reduce labor dependence. However, many related layout design approaches proposed are prone to generating unsafe layouts: there generally lacks a consideration regarding robots’ heights and assembly range, [...] Read more.
In advanced industrial automation, industrial robots have been widely utilized on assembly lines in order to reduce labor dependence. However, many related layout design approaches proposed are prone to generating unsafe layouts: there generally lacks a consideration regarding robots’ heights and assembly range, which will lead to costly collisions in the operation stage. In order to address the problem, we propose a three-dimensional (3D) optimization approach to a safe layout design for an assembly line with robots. We define modeling rules for robots to judge assembly ranges. A quantitative safety indicator is employed as a trigger for 3D collision detection in order to determine the positional relationship and status of the safe assembly collaboration. The optimization goals are established for minimizing the logistical cost and layout area in the model. A combined algorithm of differential evolution and nondominated sequencing genetic II is applied, which effectively enhances the poor diversity and convergence of the mainstream optimization method when solving this model. The benchmark tests and validation proved that our approach yields excellent convergence and distribution performance. The case study verifies that the safe layout model is valid and our approach can generate a safe layout in order to optimize economics and safety. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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19 pages, 1615 KiB  
Article
PetriNet Editor + PetriNet Engine: New Software Tool For Modelling and Control of Discrete Event Systems Using Petri Nets and Code Generation
by Erik Kučera, Oto Haffner, Peter Drahoš, Roman Leskovský and Ján Cigánek
Appl. Sci. 2020, 10(21), 7662; https://doi.org/10.3390/app10217662 - 29 Oct 2020
Cited by 7 | Viewed by 4797
Abstract
Petri nets are an important tool for creation of new platforms for digitised production systems due to their versatility in modelling discrete event systems. For the development of modern complex production processes for Industry 4.0, using advanced mathematical models based on Petri nets [...] Read more.
Petri nets are an important tool for creation of new platforms for digitised production systems due to their versatility in modelling discrete event systems. For the development of modern complex production processes for Industry 4.0, using advanced mathematical models based on Petri nets is an appropriate and effective option. The main aim of the proposed article is to design a new software tool for modelling and control of discrete event systems using Arduino-type microcontrollers and code generation techniques. To accomplish this task, a new tool called “PetriNet editor + PetriNet engine” based on Petri nets is proposed able to generate the code for the microcontroller according to the modelled Petri net. The developed software tool was successfully verified in control of a laboratory plant. Offering a graphical environment for the design of discrete event system control algorithms, it can be used for education, research and practice in cyber-physical systems (Industry 4.0). Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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8 pages, 2790 KiB  
Article
Measurement of Wafer Focus by Grating Shearing Interferometry
by Jian Wang, Song Hu and Xianchang Zhu
Appl. Sci. 2020, 10(21), 7467; https://doi.org/10.3390/app10217467 - 23 Oct 2020
Cited by 1 | Viewed by 2071
Abstract
A method applied for improving the measurement precision and efficiency of wafer focusing in an optical lithography instrument (OLI) is introduced. Based on grating shearing interferometry, the defocus and tilt of the wafer are measured by testing the phase difference in the interference [...] Read more.
A method applied for improving the measurement precision and efficiency of wafer focusing in an optical lithography instrument (OLI) is introduced. Based on grating shearing interferometry, the defocus and tilt of the wafer are measured by testing the phase difference in the interference pattern. To validate the feasibility, an experiment is implemented, of which the measurement precision is indicated as 30 nm due to the high precision of phase-resolving arithmetic after analyzing the measurement uncertainty and indicating the precision by interferometer. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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25 pages, 5189 KiB  
Article
Integration of an MES and AIV Using a LabVIEW Middleware Scheduler Suitable for Use in Industry 4.0 Applications
by Muzaffar Rao, Liam Lynch, James Coady, Daniel Toal and Thomas Newe
Appl. Sci. 2020, 10(20), 7054; https://doi.org/10.3390/app10207054 - 11 Oct 2020
Cited by 4 | Viewed by 4146
Abstract
Industry 4.0 uses the analysis of real-time data, artificial intelligence, automation, and the interconnection of components of the production lines to improve manufacturing efficiency and quality. Manufacturing Execution Systems (MESs) and Autonomous Intelligent Vehicles (AIVs) are key elements of Industry 4.0 implementations. An [...] Read more.
Industry 4.0 uses the analysis of real-time data, artificial intelligence, automation, and the interconnection of components of the production lines to improve manufacturing efficiency and quality. Manufacturing Execution Systems (MESs) and Autonomous Intelligent Vehicles (AIVs) are key elements of Industry 4.0 implementations. An MES connects, monitors, and controls data flows on the factory floor, while automation is achieved by using AIVs. The Robot Operating System (ROS) built AIVs are targeted here. To facilitate MES and AIV interactions, there is a need to integrate the MES and the AIVs to help in building an automated and interconnected manufacturing environment. This integration needs middleware, which understands both MES and AIVs. To address this issue, a LabVIEW-based scheduler is proposed here as the middleware. LabVIEW communicates with the MES through webservices and has support for ROS. The main task of the scheduler is to control the AIV based on MES requests. The scheduler developed was tested in a real factory environment using the SAP MES and a Robotnik ‘RB-1′ robot. The scheduler interface provides real-time information about the current status of the MES, AIV, and the current stage of scheduler processing. The proposed scheduler provides an efficient automated product delivery system that transports the product from process cell to process cell using the AIV, based on the production sequences defined by the MES. In addition, using the proposed scheduler, integration of an MES is possible with any low-cost ROS-built AIV. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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18 pages, 1796 KiB  
Article
New Software Tool for Modeling and Control of Discrete-Event and Hybrid Systems Using Timed Interpreted Petri Nets
by Erik Kučera, Oto Haffner, Peter Drahoš, Ján Cigánek, Roman Leskovský  and Juraj Štefanovič
Appl. Sci. 2020, 10(15), 5027; https://doi.org/10.3390/app10155027 - 22 Jul 2020
Cited by 7 | Viewed by 3302
Abstract
For the development of modern complex production processes in Industry 4.0, it is appropriate to effectively use advanced mathematical models based on Petri nets. Due to their versatility in modeling discrete-event systems, Petri nets are an important support in creating new platforms for [...] Read more.
For the development of modern complex production processes in Industry 4.0, it is appropriate to effectively use advanced mathematical models based on Petri nets. Due to their versatility in modeling discrete-event systems, Petri nets are an important support in creating new platforms for digitized production systems. The main aim of the proposed article is to design a new software tool for modeling and control of discrete-event and hybrid systems using Arduino and similar microcontrollers. To accomplish these tasks, a new tool called PN2ARDUINO based on Petri nets is proposed able to communicate with the microcontroller. Communication with the microcontroller is based on the modified Firmata protocol hence, the control algorithm can be implemented on all microcontrollers that support this type of protocol. The developed software tool was successfully verified in control of laboratory systems. In addition, it can be used for education and research purposes as it offers a graphical environment for designing control algorithms for hybrid and mainly discrete-event systems. The proposed software tool can improve education and practice in cyber-physical systems (Industry 4.0). Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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Review

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31 pages, 328 KiB  
Review
A Scoping Review on Virtual Reality-Based Industrial Training
by Jose E. Naranjo, Diego G. Sanchez, Angel Robalino-Lopez, Paola Robalino-Lopez, Andrea Alarcon-Ortiz and Marcelo V. Garcia
Appl. Sci. 2020, 10(22), 8224; https://doi.org/10.3390/app10228224 - 20 Nov 2020
Cited by 46 | Viewed by 8043
Abstract
The fourth industrial revolution has forced most companies to technologically evolve, applying new digital tools, so that their workers can have the necessary skills to face changing work environments. This article presents a scoping review of the literature on virtual reality-based training systems. [...] Read more.
The fourth industrial revolution has forced most companies to technologically evolve, applying new digital tools, so that their workers can have the necessary skills to face changing work environments. This article presents a scoping review of the literature on virtual reality-based training systems. The methodology consisted of four steps, which pose research questions, document search, paper selection, and data extraction. From a total of 350 peer-reviewed database articles, such as SpringerLink, IEEEXplore, MDPI, Scopus, and ACM, 44 were eventually chosen, mostly using the virtual reality haptic glasses and controls from Oculus Rift and HTC VIVE. It was concluded that, among the advantages of using this digital tool in the industry, is the commitment, speed, measurability, preservation of the integrity of the workers, customization, and cost reduction. Even though several research gaps were found, virtual reality is presented as a present and future alternative for the efficient training of human resources in the industrial field. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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Other

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16 pages, 306 KiB  
Case Report
Case Study of Expected Loss Failure Mode and Effect Analysis Model Based on Maintenance Data
by Seungsik Min and Hyeonae Jang
Appl. Sci. 2021, 11(16), 7349; https://doi.org/10.3390/app11167349 - 10 Aug 2021
Cited by 2 | Viewed by 2638
Abstract
Failure mode and effect analysis (FMEA) is one of the most widely employed pre-evaluation techniques to avoid risks during the product design and manufacturing phases. Risk priority number (RPN), a risk assessment indicator used in FMEA, is widely used in the field due [...] Read more.
Failure mode and effect analysis (FMEA) is one of the most widely employed pre-evaluation techniques to avoid risks during the product design and manufacturing phases. Risk priority number (RPN), a risk assessment indicator used in FMEA, is widely used in the field due to its simple calculation process, but its limitations as an absolute risk assessment indicator have been pointed out. There has also been criticism of the unstructured nature and lack of systematicity in the FMEA procedures. This work proposes an expected loss-FMEA (EL-FMEA) model that organizes FMEA procedures and structures quantitative risk assessment metrics. In the EL-FMEA model, collectible maintenance record data is defined and based on this, the failure rate of components and systems and downtime and uptime of the system are calculated. Moreover, based on these calculated values, the expected economic loss is computed considering the failure detection time. It also provides an alternative coefficient to evaluate whether or not a detection system is installed to improve the expected loss of failure. Finally, a case study was conducted based on the maintenance record data, and the application procedure of the EL-FMEA model was presented in detail, and the practicality of this model was verified through the results. Full article
(This article belongs to the Special Issue Industry 4.0 Based Smart Manufacturing Systems)
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