Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.5
Journals
Processes
Special Issues
Monitoring and Control of Processes in the Context of Industry...
share announcement

Monitoring and Control of Processes in the Context of Industry 4.0

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 9503

Special Issue Editors

Prof. Dr. Ján Piteľ

E-Mail Website
Guest Editor
Department of Industrial Engineering and Informatics, Faculty of Manufacturing Technologies with a Seat in Presov, Technical University of Kosice, 080 01 Presov, Slovakia
Interests: monitoring and control of machines; mechatronic systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ivan Pavlenko

E-Mail Website
Guest Editor
Department of Computational Mechanics named after V. Martsynkovskyy, Sumy State University, 40007 Sumy, Ukraine
Interests: dynamics and strength of machines; numerical simulation; parameter identification; artificial neural networks; design engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Sławomir Luściński

E-Mail Website
Guest Editor
Department of Production Engineering, Kielce University of Technology, Faculty of Management and Computer Modelling, Aleja Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland
Interests: computer modeling and simulation in production and logistics; Industry 4.0
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue, titled “Monitoring and Control of Processes in the Context of Industry 4.0”, aims to highlight the novel advances in process monitoring and control according to Industry 4.0 requirements. The real-time monitoring of processes and their advanced control using soft computing require a full digitalization of processes, resulting in their digital twins which are connections between the real and virtual world. Online digital twins require a reliable connection with the real processes and therefore technologies such as smart sensors and smart metering, IoT and signal processing play an important role. Vision systems, clouds and data mining are of great importance for data acquisition, storage and processing for quality control purposes. Topics will include, but are not limited to:

  • The real-time monitoring of processes;
  • Advanced control of processes using soft computing;
  • Digitalization of processes, interfaces and digital twins;
  • Smart sensors and smart metering in processes and signal processing;
  • Vision and measuring systems for quality control;
  • Data acquisition, storage and processing;
  • Virtual, augmented and mixed reality in processes;
  • Predictive maintenance and forecasting in processes.

Prof. Dr. Ján Piteľ
Prof. Dr. Ivan Pavlenko
Dr. Sławomir Luściński
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. Processes 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

  • monitoring
  • process control
  • digital twin
  • quality control
  • Industry 4.0

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

20 pages, 2436 KiB  
Article
Modeling and Analysis of Distributed Control Systems: Proposal of a Methodology
by Milan Tkáčik, Ján Jadlovský, Slávka Jadlovská, Anna Jadlovská and Tomáš Tkáčik
Processes 2024, 12(1), 5; https://doi.org/10.3390/pr12010005 - 19 Dec 2023
Viewed by 944
Abstract
A Distributed Control System is a concept of Network Control Systems whose applications range from industrial control systems to the control of large physical experiments such as the ALICE experiment at CERN. The design phase of the Distributed Control Systems implementation brings several [...] Read more.
A Distributed Control System is a concept of Network Control Systems whose applications range from industrial control systems to the control of large physical experiments such as the ALICE experiment at CERN. The design phase of the Distributed Control Systems implementation brings several challenges, such as predicting the throughput and response of the system in terms of data-flow. These parameters have a significant impact on the operation of the Distributed Control System, and it is necessary to consider them when determining the distribution of software/hardware resources within the system. This distribution is often determined experimentally, which may be a difficult, iterative process. This paper proposes a methodology for modeling Distributed Control Systems using a combination of Finite-State Automata and Petri nets, where the resulting model can be used to determine the system’s throughput and response before its final implementation. The proposed methodology is demonstrated and verified on two scenarios concerning the respective areas of ALICE detector control system and mobile robotics, using the MATLAB/Simulink implementation of created models. The methodology makes it possible to validate various distributions of resources without the need for changes to the physical system, and therefore to determine the appropriate structure of the Distributed Control System. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

18 pages, 1262 KiB  
Article
Integration of Bayesian Adaptive Exponentially Weighted Moving Average Control Chart and Paired Ranked-Based Sampling for Enhanced Semiconductor Manufacturing Process Monitoring
by Botao Liu, Muhammad Noor-ul-Amin, Imad Khan, Emad A. A. Ismail and Fuad A. Awwad
Processes 2023, 11(10), 2893; https://doi.org/10.3390/pr11102893 - 30 Sep 2023
Cited by 3 | Viewed by 820
Abstract
Exponentially weighted moving average (EWMA) and Shewhart control charts are commonly utilized to detect the small to moderate and large shifts in the process mean, respectively. This article introduces a novel Bayesian AEWMA control chart that employs various loss functions (LFs), including square [...] Read more.
Exponentially weighted moving average (EWMA) and Shewhart control charts are commonly utilized to detect the small to moderate and large shifts in the process mean, respectively. This article introduces a novel Bayesian AEWMA control chart that employs various loss functions (LFs), including square error loss function (SELF) and LINEX loss function (LLF). The control chart incorporates an informative prior for posterior and posterior predictive distributions. Additionally, the control chart utilizes various paired ranked set sampling (PRSS) schemes to improve its accuracy and effectiveness. The average run length (ARL) and standard deviation of run length (SDRL) are used to evaluate the performance of the suggested control chart. Monte Carlo simulations are conducted to compare the performance of the proposed approach to other control charts. The results show that the proposed method outperforms in identifying out-of-control signals, particularly under PRSS schemes compared to simple random sampling (SRS). The proposed CCs effectiveness was validated using a real-life semiconductor manufacturing application, utilizing different PRSS schemes. The performance of the Bayesian AEWMA CC was evaluated, demonstrating its superiority in detecting out-of-control signs compared to existing CCs. This study introduces an innovative method incorporating various LFs and PRSS schemes, providing an enhanced and efficient approach for identifying shifts in the process mean. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

15 pages, 908 KiB  
Article
Study on Multi-Objective Optimization of Logistics Distribution Paths in Smart Manufacturing Workshops Based on Time Tolerance and Low Carbon Emissions
by Chao Wu, Yongmao Xiao, Xiaoyong Zhu and Gongwei Xiao
Processes 2023, 11(6), 1730; https://doi.org/10.3390/pr11061730 - 06 Jun 2023
Viewed by 1438
Abstract
In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, [...] Read more.
In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A “time window span” was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of improving workstation service satisfaction. Lastly, in order to verify the effectiveness of the model and algorithm proposed in this study, a simulation experiment has been conducted on the workstation logistics distribution system in a smart manufacturing workshop to provide convincing evidence for optimizing workstation logistics distribution paths in workshops of discrete manufacturing enterprises. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

19 pages, 3089 KiB  
Article
A Framework for Multivariate Statistical Quality Monitoring of Additive Manufacturing: Fused Filament Fabrication Process
by Moath Alatefi, Abdulrahman M. Al-Ahmari, Abdullah Yahia AlFaify and Mustafa Saleh
Processes 2023, 11(4), 1216; https://doi.org/10.3390/pr11041216 - 14 Apr 2023
Cited by 2 | Viewed by 1317
Abstract
Advances in additive manufacturing (AM) processes have increased the number of relevant applications in various industries. To keep up with this development, the process stability of AM processes should be monitored, which is conducted through the assessment of the outputs or product characteristics. [...] Read more.
Advances in additive manufacturing (AM) processes have increased the number of relevant applications in various industries. To keep up with this development, the process stability of AM processes should be monitored, which is conducted through the assessment of the outputs or product characteristics. However, the use of univariate control charts to monitor an AM process might lead to misleading results, as most additively manufactured products have more than one correlated quality characteristic (QC). This paper proposes a framework for monitoring the multivariate quality characteristics of AM processes, and the proposed framework was applied to monitor a fused filament fabrication (FFF) process. In particular, specimens were designed and produced using the FFF process, and their QCs were identified. Then, critical quality characteristic data were collected using a precise measurement system. Furthermore, we propose a transformation algorithm to ensure the normality of the collected data. After examining the correlations between the investigated quality characteristics, a multivariate exponential weighted moving average (MEWMA) control chart was used to monitor the stability of the process. Furthermore, the MEWMA parameters were optimized using a novel heuristic technique. The results indicate that the majority of the collected data are not normally distributed. Consequently, the efficacy of the proposed transformation technique is demonstrated. In addition, our findings illustrate the correlations between the QCs. It is worth noting that the MEWMA optimization results confirm that the considered AM process (i.e., FFF) is relatively stable. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

18 pages, 4242 KiB  
Article
Turned Surface Monitoring Using a Confocal Sensor and the Tool Wear Process Optimization
by Jozef Jurko, Martin Miškiv-Pavlík, Jozef Husár and Peter Michalik
Processes 2022, 10(12), 2599; https://doi.org/10.3390/pr10122599 - 05 Dec 2022
Cited by 3 | Viewed by 1344
Abstract
Laser scanning technology has been used for several years. Nevertheless, no comprehensive study has been conducted to prove that the application of confocal chromatic sensor (CCHS) laser technology is effective and suitable to verify the integrity parameters of machined surfaces in terms of [...] Read more.
Laser scanning technology has been used for several years. Nevertheless, no comprehensive study has been conducted to prove that the application of confocal chromatic sensor (CCHS) laser technology is effective and suitable to verify the integrity parameters of machined surfaces in terms of cutting tool damage. In this paper, the optimization and effects of five factors (cutting speed, feed, depth of cut, attachment length of the workpiece, and tip radius) on the roundness deviation measured by CCHS and, at the same time, on the amount of wear on the back side of the cutting part of the tool were studied according to ISO 3685, which was measured with a microscope. The results obtained were evaluated using the gray relational analysis method (GRA), in conjunction with the Taguchi method, and the significance of the factors was demonstrated using the analysis of variance (ANOVA) method. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

16 pages, 3776 KiB  
Article
Vapor Overproduction Condition Monitoring in a Liquid–Vapor Ejector
by Serhii Sharapov, Jana Mižáková, Danylo Husiev, Vitalii Panchenko, Vitalii Ivanov, Ivan Pavlenko and Kamil Židek
Processes 2022, 10(11), 2383; https://doi.org/10.3390/pr10112383 - 13 Nov 2022
Viewed by 1043
Abstract
We consider the influence of vapor content in the mixed flow leaving a liquid-vapor ejector on the energy efficiency of a vacuum unit. As shown by numerical studies of liquid-vapor ejectors, this issue is important as vapor overproduction, which accompanies the process of [...] Read more.
We consider the influence of vapor content in the mixed flow leaving a liquid-vapor ejector on the energy efficiency of a vacuum unit. As shown by numerical studies of liquid-vapor ejectors, this issue is important as vapor overproduction, which accompanies the process of secondary flow ejection, directly impacts the efficiency of the working process of both the liquid-vapor ejector and the vacuum unit as a whole. The greater the degree of vapor overproduction, the greater the load on the vapor phase of the separator, which is part of the vacuum unit. In addition, the liquid phase must be returned to the cycle to ensure the constancy of the mass flow rate of the working fluid of the primary flow. Our numerical study results revealed the rational value of the degree of vapor overproduction at which the efficiency of the liquid–vapor ejector was maximized, and the amount of additional working fluid that needed to enter the cycle of the vacuum unit was minimal. Experimental condition monitoring studies on the liquid–vapor ejector were carried out on plane-parallel transparent models with different flow path geometries. Through experimental studies, we confirmed and adjusted the values of the achievable efficiency of the working process of a liquid–vapor ejector, depending on the degree of vapor overproduction. Using a comparative analysis of liquid–vapor ejectors with different flow path geometries, differences were revealed in their working processes, which consisted of the degree of completion of the mixing of the working media of primary and secondary flows. To determine the feasibility of using liquid–vapor ejectors with different flow path geometries, exergy analysis was performed, resulting in achievable efficiency indicators. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

21 pages, 6575 KiB  
Article
Experimental Studies and Condition Monitoring of Auxiliary Processes in the Production of Al2O3 by Sol–Gel Technology
by Vsevolod Sklabinskyi, Oleksandr Liaposhchenko, Ján Piteľ, Ivan Pavlenko, Maksym Skydanenko, Ruslan Ostroha, Mykola Yukhymenko, Kostiantyn Simeiko, Maryna Demianenko, Michal Volf, Oleksandr Starynskyi, Oleksandr Yurchenko and Oleksandr Mandryka
Processes 2022, 10(10), 2090; https://doi.org/10.3390/pr10102090 - 15 Oct 2022
Viewed by 1228
Abstract
Powders and granules of heavy metal oxides produced through condition monitoring are in high demand as intermediate products for obtaining fine-grained ceramics for a wide range of applications, i.e., nuclear fuel and fuel elements for nuclear power plants. Sol–gel technology to produce nuclear [...] Read more.
Powders and granules of heavy metal oxides produced through condition monitoring are in high demand as intermediate products for obtaining fine-grained ceramics for a wide range of applications, i.e., nuclear fuel and fuel elements for nuclear power plants. Sol–gel technology to produce nuclear fuel (UO2), as well as catalysts (ThO2) for organic synthesis in the form of granules from pressed microspheres, is a promising method to obtain powders and granules of heavy metal oxides (fine-graded ceramics). Al2O3 was selected as the model analog at the stages of obtaining a solution of heavy metal and sol, the formation and gelation of droplets, and the preparation of gel spheres and their further washing and drying, as well as recovery and firing of particles. In the study, the main parameters were substantiated, e.g., the diameter and angle of inclination of the axis for the holes in the perforated shell, the multiplicity of sol circulation before the holes, the coefficients of liquid (sol) flow rate, the oscillation frequency of the disperser, and the concentration of surfactant and acid in sol. All of these parameters affect the characteristics of the granules that are obtained by sol–gel technology. Moreover, recommendations to increase productivity and the energy efficiency of production were also given. In particular, it was found that oscillation frequency in a range of 70–80 Hz leads to a granulometric composition of the obtained granules of 2.0–2.2 mm. A hole of 0.85 mm and a frequency of 100 Hz slightly change this range to 1.2–2.0 mm, while maintaining monodispersity. Full article
(This article belongs to the Special Issue Monitoring and Control of Processes in the Context of Industry 4.0)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop