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Process Control and Smart Manufacturing for Industry 4.0

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A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: closed (1 December 2021) | Viewed by 35762
We are also glad to welcome the selected papers on related topics from Automation, Robotics & Communications for Industry 4.0: 1st IFSA Winter Conference (ARCI' 2021, https://www.arci-conference.com/).

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Special Issue Editor

Dr. Sergey Y. Yurish

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Guest Editor

International Frequency Sensor Association (IFSA), 08860 Castelldefels, Spain
Interests: smart sensors; optical sensors; frequency measurements
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industry 4.0 is an integrated system which consists of an automation tool, robotic control, communications, and big data analytics. Industry 4.0 holds a wealth of potential and is expected to register substantial growth in the near future. There have been several conferences on automation, robotics, and communications, but they do not meet the challenges of Industry 4.0. This series of annual ARCI Winter IFSA conferences have been launched to fill in this gap and provide a forum for open discussion of state-of-the-art technologies related to control, automation, robotics, and communication – the three main components of Industry 4.0.

Authors of selected high-qualified papers from the conference will be invited to submit extended versions of their original papers (with at least 50% extension of the contents of the conference paper) and contributions.

This Special Issue “Process Control and Smart Manufacturing for Industry 4.0” is focused on extended papers on the following topics:

Process Automation
Process Control and Monitoring
Design Principles in Industry 4.0
Smart Manufacturing and Technologies
Smart Factories
Machine Learning and Artificial Intelligence in Manufacturing
Chemical Process Control

Submissions on other topics are also welcome provided they fit within the theme of the Special Issue.

Prof. Dr. Sergey Y. Yurish
Guest Editor

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

process control
process monitoring
smart manufacturing
Industry 4.0

Published Papers (14 papers)

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14 pages, 4440 KiB

Open AccessArticle

Modeling of Erosion in a Cyclone and a Novel Separator with Arc-Shaped Elements

by Elmira I. Salakhova, Vadim E. Zinurov, Andrey V. Dmitriev and Ilshat I. Salakhov

Processes 2023, 11(1), 156; https://doi.org/10.3390/pr11010156 - 04 Jan 2023

Cited by 6 | Viewed by 1392

Abstract

Modeling of the separation of catalyst particles from gas using two devices, a cyclone and a novel separator with arc-shaped elements, was performed for fluidized-bed dehydrogenation of C₄–C₅ paraffins to isoolefins as an example. The proposed dust collector allows one to reduce erosive wear by several times (~6.5-fold) in identical regimes and at identical parameters of the process. The effect of particle size on erosive wear was analyzed under near-industrial conditions; the regions most susceptible to wear in the analyzed devices were identified, as well as the functions describing the dependence between the erosive wear rate and particle diameter for the cyclone and separator with arc-shaped elements, making it possible to predict wear in the devices were obtained. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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22 pages, 3796 KiB

Open AccessArticle

Energy-Saving and Low-Carbon Gear Blank Dimension Design Based on Business Compass

by Yongmao Xiao, Jincheng Zhou, Ruping Wang, Xiaoyong Zhu and Hao Zhang

Processes 2022, 10(9), 1859; https://doi.org/10.3390/pr10091859 - 15 Sep 2022

Cited by 2 | Viewed by 1080

Abstract

Sustainable blank dimension design is the key to the implementation of green industrial development. However, blank dimension design only considers the blank production factor of the blank dimension design stage, which cannot guarantee the blank production stage and the use stage’s overall goal. In this paper, based on the guiding thinking of a business compass, a low-carbon and low-energy consumption blank dimension optimization design model was proposed. Taking the process parameters of the production and the use of the blank as the variables, the grey wolf optimization algorithm was adopted to solve the problem. Taking the gear blanks dimension as an example, the optimized blank dimension is 98.6, compared with the standard blank dimension of 100, 105, the energy consumption is 95.7% and 93.1%, the carbon emission is 92.6% and 90.2%, and the material consumption is 96.5% and 87.5%, respectively. The sustainable blank dimension design has obvious advantages in terms of low energy consumption and low carbon, and it can save a lot of materials; it can also promote product sustainability. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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15 pages, 2110 KiB

Open AccessArticle

Energy-Saving and Efficient Equipment Selection for Machining Process Based on Business Compass Model

by Yongmao Xiao, Jincheng Zhou, Ruping Wang, Xiaoyong Zhu and Hao Zhang

Processes 2022, 10(9), 1846; https://doi.org/10.3390/pr10091846 - 13 Sep 2022

Cited by 3 | Viewed by 1456

Abstract

The optimal selection of machine equipment can reduce the energy consumption and processing time of the parts processing process in enterprises. The energy consumption and time of using different equipment to process the same product vary greatly. Traditional equipment selection is only through qualitative analysis comparing the process characteristics of using different equipment or optimizing parameters for a single piece of equipment. It does not take into account the dynamics of the production process and does not consider the impact of process factors on production decisions. To solve this problem, we established a production equipment selection model based on the business compass model and proposed a calculation method that considered energy consumption and time objectives in the production process. Quantitative analysis can be performed for different equipment. The energy consumption and processing time of different equipment are calculated by the beetle antennae search (BAS) algorithm. A case study of machining end cap holes was carried out. The results showed that this method can calculate the optimal energy consumption and the optimal time of different equipment for producing the same product, which has good theoretical and practical significance for enterprises and governments to choose energy-saving and efficient production equipment. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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18 pages, 2934 KiB

Open AccessEditor’s ChoiceArticle

An Agent-Based Approach for Make-To-Order Master Production Scheduling

by Faezeh Bagheri, Melissa Demartini, Alessandra Arezza, Flavio Tonelli, Massimo Pacella and Gabriele Papadia

Processes 2022, 10(5), 921; https://doi.org/10.3390/pr10050921 - 06 May 2022

Cited by 2 | Viewed by 2301

Abstract

In recent decades, manufacturers’ intense competitiveness to suit consumer expectations has compelled them to abandon the conventional workflow in favour of a more flexible one. This new trend increased the importance of master production schedule and make-to-order (MTO) strategy concepts. The former improves overall planning and controls complexity. The latter enables the production businesses to reinforce their flexibility and produce customized products. In a production setting, fluctuating resource capacity restricts production line performance, and ignoring this fact renders planning inapplicable. The current research work addresses the MPS problem in the context of the MTO production environment. The objective is to resolve Rough-Cut Capacity Planning by considering resource capacity fluctuation to schedule the customer’s order with the minimum cost imposed by the company and customer side. Consequently, this study is an initial attempt to propose a mathematical programming approach, which provides the optimum result for small and medium-size problems. Regarding the combinatorial intrinsic of this kind of problem, the mathematical programming approach can no longer reach the optimum solution for a large-scale problem. To overcome this, an innovative agent-based heuristic has been proposed. Computational experiments on variously sized problems confirm the efficiency of the agent-based approach. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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16 pages, 1899 KiB

Open AccessArticle

Two-Dimensional, Two-Layer Quality Regression Model Based Batch Process Monitoring

by Luping Zhao and Xin Huang

Processes 2022, 10(1), 43; https://doi.org/10.3390/pr10010043 - 27 Dec 2021

Viewed by 1705

Abstract

In this paper, a two-dimensional, two-layer quality regression model is established to monitor multi-phase, multi-mode batch processes. Firstly, aiming at the multi-phase problem and the multi-mode problem simultaneously, the relations among modes and phases are captured through the analysis between process variables and quality variables by establishing a two-dimensional, two-layer regression partial least squares (PLS) model. The two-dimensional regression traces the intra-batch and inter-batch characteristics, while the two-layer structure establishes the relationship between the target process and historical modes and phases. Consequently, online monitoring is carried out for multi-phase, multi-mode batch processes based on quality prediction. In addition, the online quality prediction and monitoring results based on the proposed method and those based on the traditional phase mean PLS method are compared to prove the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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21 pages, 4522 KiB

Open AccessFeature PaperArticle

Evaluation of Pull Production Control Mechanisms by Simulation

by Nataša Tošanović and Nedeljko Štefanić

Processes 2022, 10(1), 5; https://doi.org/10.3390/pr10010005 - 21 Dec 2021

Cited by 1 | Viewed by 2644

Abstract

Today, companies need to continuously improve their production processes, which is a complex task. Lean manufacturing is one of the methodologies for production improvement, and one of the basic goals of any lean implementation is to reduce work-in-process (WIP) and shorten the production lead time. One of the basic lean principles for achieving these goals is pull principle. The adoption of this principle is quite challenging, as it requires a long-term commitment in the application and adoption of various lean techniques and tools that are prerequisites for the successful introduction of the pull principle. Kanban is the most well-known pull production control mechanism, and the first one developed within Toyota production system, but later, other pull control mechanisms were developed. Some of them include Conwip, Hybrid Kanban/Conwip, and Drum Buffer Rope (DBR), and those three, together with Kanban, were the research topic of this study. These four mechanisms were not explored and compared all together not for these specific production configurations considered in this research but also with regard to optimal parameters of control mechanisms. The goal was to analyze and compare how these pull control mechanisms affect lead time in different production conditions. For this purpose, simulation experiments were performed. The results showed that for different production conditions, different pull control mechanisms are optimal in terms of shortening lead time. This finding could help companies as a guideline for making a decision in terms of which pull control mechanism to choose. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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25 pages, 1820 KiB

Open AccessArticle

The Analysis of the Spatial Production Mechanism and the Coupling Coordination Degree of the Danwei Compound Based on the Spatial Ternary Dialectics

by Zihan Yang, Jianqiang Yang and Kai Ren

Processes 2021, 9(12), 2281; https://doi.org/10.3390/pr9122281 - 20 Dec 2021

Cited by 2 | Viewed by 2431

Abstract

With the gradual deepening of the development of high-quality urban transformation, the “Danwei Compound” urban space production method constitutes the basis of Chinese current urban spatial transformation. The transformation plan of the original danwei compound “stock” to promote the healthy development of urban society has become the focus of research. First, with the help of Lefebvre’s space production theory, combined with the spatial transformation characteristics of its own structural form experienced by the Chinese urban danwei compound, the space production is divided into three stages, namely, the diversity-orderly type average space of the danwei compound system period, dispersed type abstract space of the commercial enclosed community period, and the integrated differential space of a livable community undergoing regeneration and transformation. At each stage, the government, market, and residents have different influences on time-space production. Secondly, using Hefei’s typical danwei compound as the research carrier, according to the space ternary dialectics, a multi-level analysis of “representations of space-representational space-spatial practice” is carried out on the production mechanism, and the logic of different types of spaces in different periods are described. Among them, the representations of space of the change of the danwei compound are the interrelationship of multiple governance subjects in different periods, such as changes in the implementation degree of governance strategies, the degree of residents’ community governance participation, residents’ satisfaction with community governance, etc. The representational space is the residents’ community perception and interpersonal relationship at different transition stages, Interpersonal trust, and other social relations’ changes. Spatial practice is manifested in changes in the support of public service facilities, public space, per capita living area, building quality, architectural style, and illegal building area. Finally, the three-dimensional space dialectical coupling coordination degree model is used to analyze and compare the representations of space of typical settlements in the three stages and the coupling characteristics of the representational space and the practice of space. On this basis, we provide innovative ideas and put forward relevant measures and suggestions for the regeneration, transformation, and development of livable areas. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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17 pages, 6535 KiB

Open AccessArticle

Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning

by Gang Liu, Rongxu Zhang, Yanyan Wang and Rongjun Man

Processes 2021, 9(11), 1955; https://doi.org/10.3390/pr9111955 - 31 Oct 2021

Cited by 10 | Viewed by 2025

Abstract

The application of scene recognition in intelligent robots to forklift AGV equipment is of great significance in order to improve the automation and intelligence level of distribution centers. At present, using the camera to collect image information to obtain environmental information can break through the limitation of traditional guideway and positioning equipment, and is beneficial to the path planning and system expansion in the later stage of warehouse construction. Taking the forklift AGV equipment in the distribution center as the research object, this paper explores the scene recognition and path planning of forklift AGV equipment based on a deep convolution neural network. On the basis of the characteristics of the warehouse environment, a semantic segmentation network applied to the scene recognition of the warehouse environment is established, and a scene recognition method suitable for the warehouse environment is proposed, so that the equipment can use the deep learning method to learn the environment features and achieve accurate recognition in the large-scale environment, without adding environmental landmarks, which provides an effective convolution neural network model for the scene recognition of forklift AGV equipment in the warehouse environment. The activation function layer of the model is studied by using the activation function with better gradient performance. The results show that the performance of the H-Swish activation function is better than that of the ReLU function in recognition accuracy and computational complexity, and it can save costs as a calculation form of the mobile terminal. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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22 pages, 4156 KiB

Open AccessArticle

A Data Management Approach Based on Product Morphology in Product Lifecycle Management

by Gang Liu, Rongjun Man and Yanyan Wang

Processes 2021, 9(7), 1235; https://doi.org/10.3390/pr9071235 - 16 Jul 2021

Cited by 5 | Viewed by 2932

Abstract

In the product life cycle from conception to retirement, there are three forms: conceptual products, digital products and physical products. The carriers of conceptual products are requirements, functions and abstract structures, and data management focuses on the mapping of requirements, functions, and structures. The carrier of digital products is digital files such as drawings and models, and the focus of data management is the design evolution of product. Physical products are physical entities, and their attributes and states will change over time. Existing data model research often focuses on one or two forms, and it is even impossible to integrate three forms of data into one system. So, a new data management method based on product form is presented. According to the characteristics of the three product form data, a conceptual product data model, a digital product data model, and a physical product data model are established to manage the three forms of data, respectively, and use global object mapping to integrate them into a unified data model. The conceptual product data model has a single data model for a single business stage. The digital product data model uses the core data model as the single data source, and uses one stage rule filter to add constraints to the core data model for each business stage. The physical product data model uses the core data model to manage the public data of the physical phase, and the phase private data model focuses on the private data of each business phase. Finally, a case of Multi-Purpose Container Vessel is studied to verify the feasibility of the method. This paper proposes three product forms of product data management and a unified data management model covering the three product forms, which provides a new method for product life cycle data. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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13 pages, 4636 KiB

Open AccessFeature PaperArticle

Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration Sensors

by Oliver Mey, André Schneider, Olaf Enge-Rosenblatt, Dirk Mayer, Christian Schmidt, Samuel Klein and Hans-Georg Herrmann

Processes 2021, 9(7), 1108; https://doi.org/10.3390/pr9071108 - 25 Jun 2021

Cited by 7 | Viewed by 3908

Abstract

Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. Data analysis can be improved by applying machine learning algorithms and fusion of data from heterogenous sensors. This paper presents an approach for a step-wise integration of classifications gained from vibration and acoustic emission sensors in order to combine the information from signals acquired in the low and high frequency ranges. A test rig comprising a drive train and bearings with small artificial damages is used for acquisition of experimental data. The results indicate that an improvement of damage classification can be obtained using the proposed algorithm of combining classifiers for vibrations and acoustic emissions. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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18 pages, 2981 KiB

Open AccessFeature PaperArticle

Magnetic Particle Inspection Optimization Solution within the Frame of NDT 4.0

by Andreea Ioana Sacarea, Gheorghe Oancea and Luminita Parv

Processes 2021, 9(6), 1067; https://doi.org/10.3390/pr9061067 - 18 Jun 2021

Cited by 9 | Viewed by 2889

Abstract

The quality of product and process is one of the most important factors in achieving constructively and then functionally safe products in any industry. Over the years, the concept of Industry 4.0 has emerged in all the quality processes, such as nondestructive testing (NDT). The most widely used quality control methods in the industries of mechanical engineering, aerospace, and civil engineering are nondestructive methods, which are based on inspection by detecting indications, without affecting the surface quality of the examined parts. Over time, the focus has been on research with the fourth generation in nondestructive testing, i.e., NDT 4.0 or Smart NDT, as a main topic to ensure the efficiency and effectiveness of the methods for a safe detection of all types of discontinuities. This area of research aims at the efficiency of methods, the elimination of human errors, digitalization, and optimization from a constructive point of view. In this paper, we presented a magnetic particles inspection method and the possible future directions for the development of standard equipment used in the context of this method in accordance with the applicable physical principles and constraints of the method for cylindrical parts. A possible development direction was presented in order to streamline the mass production of parts made of ferromagnetic materials. We described the methods of analysis and the tools used for the development of a magnetic particle inspection method used for cylindrical parts in all types of industry and NDT 4.0; the aim is to provide new NDT 4.0 directions in optimizing the series production for cylindrical parts from industry, as given in the conclusion of this article. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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25 pages, 44125 KiB

Open AccessArticle

Multifunctional Technology of Flexible Manufacturing on a Mechatronics Line with IRM and CAS, Ready for Industry 4.0

by Adriana Filipescu, Dan Ionescu, Adrian Filipescu, Eugenia Mincă and Georgian Simion

Processes 2021, 9(5), 864; https://doi.org/10.3390/pr9050864 - 14 May 2021

Cited by 11 | Viewed by 3088

Abstract

A communication and control architecture of a multifunctional technology for flexible manufacturing on an assembly, disassembly, and repair mechatronics line (A/D/RML), assisted by a complex autonomous system (CAS), is presented in the paper. A/D/RML consists of a six-work station (WS) mechatronics line (ML) connected to a flexible cell (FC) equipped with a six-degree of freedom (DOF) industrial robotic manipulator (IRM). The CAS has in its structure two driving wheels and one free wheel (2 DW/1 FW)-wheeled mobile robot (WMR) equipped with a 7-DOF robotic manipulator (RM). On the end effector of the RM, a mobile visual servoing system (eye-in-hand VSS) is mounted. The multifunctionality is provided by the three actions, assembly, disassembly, and repair, while the flexibility is due to the assembly of different products. After disassembly or repair, CAS picks up the disassembled components and transports them to the appropriate storage depots for reuse. Technology operates synchronously with signals from sensors and eye-in-hand VSS. Disassembling or repairing starts after assembling and the final assembled product fails the quality test. Due to the diversity of communication and control equipment such as PLCs, robots, sensors or actuators, the presented technology, although it works on a laboratory structure, has applications in the real world and meets the specific requirements of Industry 4.0. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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20 pages, 38957 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

General Approach for Inline Electrode Wear Monitoring at Resistance Spot Welding

by Christian Mathiszik, David Köberlin, Stefan Heilmann, Jörg Zschetzsche and Uwe Füssel

Processes 2021, 9(4), 685; https://doi.org/10.3390/pr9040685 - 13 Apr 2021

Cited by 7 | Viewed by 3727

Abstract

Electrodes for resistance spot welding inevitably wear out. In order to extend their service life, the tip-dressing process restores their original geometry. So far, however, the point in time for tip-dressing is mainly based on experience and not on process data. Therefore, this study aims to evaluate the in-situ or inline wear during the welding process without using additional sensors, and to base the timing for tip-dressing on continuous process monitoring, extending electrode life even further. Under laboratory conditions, electrode wear is analyzed by topographical measurements deepening the knowledge of the known main wear modes of resistance-spot-welding electrodes, mushrooming and plateau forming, and characterizing an electrode length delta over the number of spot welds. In general, electrode wear results in deformation of the electrode contact area, which influences process parameters and thereby weld quality. The conducted tests show correlation between this deformed contact area and the electrode length delta. The study shows that this electrode length delta is visible in actual process data, and can therefore be used as a criterion to characterize the wear of electrodes. Furthermore, this study gives reason to question commonly used spot-welding quality criteria and suggests different approaches, such as basing spot-welding quality on the possibility of nondestructive testing. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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Other

Jump to: Research

16 pages, 2157 KiB

Open AccessCase Report

Processing Technologies for Crisis Response on the Example of COVID-19 Pandemic—Injection Molding and FFF Case Study

by Bogna Sztorch, Dariusz Brząkalski, Marek Jałbrzykowski and Robert E. Przekop

Processes 2021, 9(5), 791; https://doi.org/10.3390/pr9050791 - 30 Apr 2021

Cited by 6 | Viewed by 2237

Abstract

The paper presents a comparison of two methods of manufacturing utility objects made of plastics, applied to the emerging immediate need in the field of quick provision of personal protective equipment for medical services. The traditional processing method, which is injection molding (IM), and a modern rapid prototyping method, which is fused filament fabrication (FFF) 3D printing, were compared in terms of unit costs and production possibilities at various timeframes. The paper presents the effects of launching two production processes of protective helmets (face shields) using the example of real cases implemented ad hoc during the epidemic development. The implementation of the protective helmet production project based on polyamide-6 processing showed the real possibilities of quickly launching the rapid production of protective equipment with the aid of mold injection technology. Full article

(This article belongs to the Special Issue Process Control and Smart Manufacturing for Industry 4.0)

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