Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0

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

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 16505

Special Issue Editor


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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 has much potential and is expected to grow substantially in the near future. According to a modern market study, the global Industry 4.0 market size is projected to reach USD 377.30 billion by 2029 at a CAGR of 16.3 % during the forecast period 2022–2029.

Industry 4.0/5.0 is an integrated system consisting of automation tools, robotic control, communications and big data analytics. The increased adoption of industrial robots is one of the main driving factors of this market, while the main restraining factors include data risks associated with the integration of advanced technologies.

This Special Issue contains extended papers selected from the 3rd IFSA Winter Conference on Automation, Robotics & Communications for Industry 4.0/5.0 (ARCI 2023), 22–24 February 2023, Chamonix-Mont-Blanc, France.

Topics include (but are not limited to):

  • Process Automation;
  • Process control and monitoring;
  • Design principles in Industry 4.0/5.0;
  • Smart manufacturing and technologies;
  • Smart factories;
  • Machine learning and artificial intelligence in manufacturing;
  • Chemical process control;
  • Industrial big data and analytics;
  • Digital production and virtual engineering.

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.

Published Papers (12 papers)

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Research

16 pages, 4203 KiB  
Communication
The Industrial Digital Energy Twin as a Tool for the Comprehensive Optimization of Industrial Processes
by Alejandro Rubio-Rico, Fernando Mengod-Bautista, Andrés Lluna-Arriaga, Belén Arroyo-Torres and Vicente Fuster-Roig
Processes 2023, 11(8), 2353; https://doi.org/10.3390/pr11082353 - 4 Aug 2023
Viewed by 996
Abstract
Industrial manufacturing processes have evolved and improved since the disruption of the Industry 4.0 paradigm, while energy has progressively become a strategic resource required to maintain industrial competitiveness while maximizing quality and minimizing environmental impacts. In this context of global changes leading to [...] Read more.
Industrial manufacturing processes have evolved and improved since the disruption of the Industry 4.0 paradigm, while energy has progressively become a strategic resource required to maintain industrial competitiveness while maximizing quality and minimizing environmental impacts. In this context of global changes leading to social and economic impact in the short term and an unprecedented climate crisis, Digital Twins for Energy Efficiency in manufacturing processes provide companies with a tool to address this complex situation. Nevertheless, already existing Digital Twins applied for energy efficiency in a manufacturing process lack a flexible structure that easily replicates the real behavior of consuming machines while integrating it in complex upper-level environments. This paper presents a combined multi-paradigm approach to industrial process modeling developed and applied during the GENERTWIN project. The tool allows users to predict energy consumption and costs and, at the same time, evaluates the behavior of the process under certain productive changes to maximize consumption optimization, production efficiency and process flexibility. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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17 pages, 8353 KiB  
Article
IOTA Data Preservation Implementation for Industrial Automation and Control Systems
by Iuon-Chang Lin, Pai-Ching Tseng, Yu-Sung Chang and Tzu-Ching Weng
Processes 2023, 11(7), 2160; https://doi.org/10.3390/pr11072160 - 19 Jul 2023
Viewed by 1158
Abstract
Blockchain 3.0, an advanced iteration of blockchain technology, has emerged with diverse applications encompassing various sectors such as identity authentication, logistics, medical care, and Industry 4.0/5.0. Notably, the integration of blockchain with industrial automation and control systems (IACS) holds immense potential in this [...] Read more.
Blockchain 3.0, an advanced iteration of blockchain technology, has emerged with diverse applications encompassing various sectors such as identity authentication, logistics, medical care, and Industry 4.0/5.0. Notably, the integration of blockchain with industrial automation and control systems (IACS) holds immense potential in this evolving landscape. As industrial automation and control systems gain popularity alongside the widespread adoption of 5G networks, Internet of Things (IoT) devices are transforming into integral nodes within the blockchain network. This facilitates decentralized communication and verification, paving the way for a fully decentralized network. This paper focuses on showcasing the implementation and execution results of data preservation from industrial automation and control systems to IOTA, a prominent distributed ledger technology. The findings demonstrate the practical application of IOTA in securely preserving data within the context of industrial automation and control systems. The presented numerical results validate the effectiveness and feasibility of leveraging IOTA for seamless data preservation, ensuring data integrity, confidentiality, and transparency. By adopting IOTA’s innovative approach based on Directed Acyclic Graph (DAG), the paper contributes to the advancement of blockchain technology in the domain of Industry 4.0/5.0. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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15 pages, 2837 KiB  
Article
Low-Carbon and Energy-Saving Path Optimization Scheduling of Material Distribution in Machining Shop Based on Business Compass Model
by Yongmao Xiao, Hao Zhang and Ruping Wang
Processes 2023, 11(7), 1960; https://doi.org/10.3390/pr11071960 - 28 Jun 2023
Cited by 3 | Viewed by 867
Abstract
In order to reduce carbon emission and energy consumption in the process of raw material distribution, the workshop material distribution management model was established based on the business compass model; it can help guide enterprises to manage workshop production. Based on the raw [...] Read more.
In order to reduce carbon emission and energy consumption in the process of raw material distribution, the workshop material distribution management model was established based on the business compass model; it can help guide enterprises to manage workshop production. Based on the raw material distribution equipment, a path calculation model considering the carbon emission and energy consumption in the process of raw material distribution was established. The dung beetle optimizer was selected for the optimization calculation. The dung beetle optimizer has the characteristics of fast convergence and high solution accuracy. The material distribution of an engine assembly workshop was taken as an example; the results showed that the optimized scheduling model could effectively optimize the material distribution route and reduce energy consumption and carbon emission in the distribution process on the basis of meeting the distribution demand. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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31 pages, 11200 KiB  
Article
Numerical Experiments on Performance Comparisons of Conical Type Direct-Acting Relief Valve—With or without Conical Angle in Valve Element and Valve Seat
by Huiyong Liu and Qing Zhao
Processes 2023, 11(6), 1792; https://doi.org/10.3390/pr11061792 - 12 Jun 2023
Viewed by 979
Abstract
This paper conducts numerical experiments on performance comparisons of CTDARV—with or without conical angle in the valve element and valve seat. The working principles of three kinds of CTDARV are introduced. The simulation models of three kinds of CTDARV are established by utilizing [...] Read more.
This paper conducts numerical experiments on performance comparisons of CTDARV—with or without conical angle in the valve element and valve seat. The working principles of three kinds of CTDARV are introduced. The simulation models of three kinds of CTDARV are established by utilizing AMESIM. Numerical experiments on CTDARV, with or without a conical angle in the valve element and the valve seat, are conducted and the performance comparisons of three kinds of CTDARV are obtained. The results show that: (1) When all parameters of VED, VSD, VEM, SS, CAVE&CAVS, and OD have the same value, respectively, CA-VE has the highest stable pressure, CA-VE&VS has the highest stable displacement, CA-VS has the lowest stable pressure, and CA-VE has the lowest stable displacement. The stable pressure of CA-VE is significantly higher than that of CA-VS and CA-VE&VS. The stable displacement of CA-VE&VS is significantly higher than that of CA-VE and CA-VS, and the stable displacement of CA-VE and CA-VS has little difference. (2) With the increase of VED from 13 mm to 16 mm, the stable pressure of CA-VE remains constant, while that of CA-VS and CA-VE&VS both decreases. As the VSD increases from 3 mm to 6 mm, the stable pressure of CA-VE and CA-VE&VS decreases, and that of CA-VE decreases significantly. With the increase of VEM from 0.01 kg to 0.04 kg, the stable pressure of CA-VE, CA-VS, and CA-VE&VS remains unchanged. With the increase of SS from 5 N/mm to 20 N/mm, the stable pressure of CA-VE, CA-VS and CA-VE&VS increases. With the increase of CAVE&CAVS from 15 degrees to 60 degrees, the stable pressure of CA-VE, CA-VS, and CA-VE&VS decreases. With the OD increase from 0.8 mm to 1.4 mm, the stable pressure of CA-VE, CA-VS and CA-VE&VS remains unchanged. (3) With the increase of VED from 13 mm to 16 mm, the stable displacement of CA-VE will not change, while that of CA-VS and CA-VE&VS will increase. As the VSD increases from 3 mm to 6 mm, the stable displacement of CA-VE increases, while that of CA-VE&VS decreases. When VSD is 4 mm–6 mm, the stable displacement of CA-VS remains unchanged. With the increase of VEM from 0.01 kg to 0.04 kg, the stable displacement of CA-VE, CA-VS and CA-VE&VS remains unchanged. As SS increases from 5 N/mm to 20 N/mm, the stable displacement of CA-VE, CA-VS, and CA-VE&VS decreases. As CAVE&CAVS increases from 15 degrees to 60 degrees, the stable displacement of CA-VE, CA-VS, and CA-VE&VS decreases. With the OD increasing from 0.8 mm to 1.4 mm, the stable displacement of CA-VE, CA-VS, and CA-VE&VS remains unchanged. (4) With the increase of VED from 13 mm to 16 mm, the velocity of CA-VE remains unchanged, while that of CA-VS and CA-VE&VS increases. As the VSD increases from 4 mm to 6 mm, the velocity of CA-VS remains unchanged, while that of CA-VE and CA-VE&VS decreases. With the increase of VEM from 0.01 kg to 0.04 kg, the velocity oscillation of CA-VE gradually increases, and the velocity of CA-VS and CA-VE&VS has little change. As SS increases from 5 N/mm to 20 N/mm, the velocity of CA-VE increases, while that of CA-VS and CA-VE&VS decreases. When CAVE&CAVS is 15 degrees and 30 degrees, the velocity of CA-VE is lower than that of CA-VS and CA-VE&VS. With the OD increasing from 0.8 mm to 1.4 mm, the velocity oscillation of CA-VE increases gradually, and the velocity of CA-VS and CA-VE&VS changes little. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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16 pages, 4500 KiB  
Article
A Novel Model Prediction and Migration Method for Multi-Mode Nonlinear Time-Delay Processes
by Ping Yuan, Tianhong Zhou and Luping Zhao
Processes 2023, 11(6), 1699; https://doi.org/10.3390/pr11061699 - 2 Jun 2023
Viewed by 856
Abstract
Most industrial processes have nonlinear and time-delay characteristics leading to difficulty in prediction modeling. In addition, the working conditions of most industrial processes are complex, which results in multiple modes. Testing and modeling for each mode is a waste of time and resources. [...] Read more.
Most industrial processes have nonlinear and time-delay characteristics leading to difficulty in prediction modeling. In addition, the working conditions of most industrial processes are complex, which results in multiple modes. Testing and modeling for each mode is a waste of time and resources. Therefore, it is urgent to complete model migration between different modes. In this work, a new prediction model, a nonlinear autoregressive model with exogenous inputs and back propagation neural network (NARX-BP), is proposed for the nonlinear and time-delay processes, where the input data order of the model is determined by the feedforward neural network (FNN) method, and the nonlinear relation is realized by the BP neural network. For the multi-mode characteristic, a new migration optimization algorithm, input–output slope/bias correction and differential evolution (IOSBC-DE), is provided for using a small amount of data under a new mode to correct the slope and bias of the relationship between the input and output variables through DE. The modeling and migration methods are applied to a wind tunnel system, and the simulation result shows the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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18 pages, 1117 KiB  
Article
Study on the Optimization of the Material Distribution Path in an Electronic Assembly Manufacturing Company Workshop Based on a Genetic Algorithm Considering Carbon Emissions
by Xiaoyong Zhu, Lili Jiang and Yongmao Xiao
Processes 2023, 11(5), 1500; https://doi.org/10.3390/pr11051500 - 15 May 2023
Cited by 1 | Viewed by 1418
Abstract
In order to solve the problems of high carbon emissions, low distribution efficiency and high costs related to the process of material distribution in manufacturing workshops, a multi-objective workshop material distribution path optimization problem model is established, and the model is solved using [...] Read more.
In order to solve the problems of high carbon emissions, low distribution efficiency and high costs related to the process of material distribution in manufacturing workshops, a multi-objective workshop material distribution path optimization problem model is established, and the model is solved using an improved genetic algorithm. The problem is processed using Gray code and crossover and variation operations with a genetic algorithm. To improve the search accuracy and convergence speed of the algorithm, an adaptive mutation method is proposed to enhance the diversity of the population and to achieve global optimal path objective finding. The improved algorithm is applied to workshop path multi-station logistics path planning, which effectively solves the transport path optimization and station solving problems in workshop logistics distribution, and the convergence speed and convergence accuracy of the algorithm are significantly improved. Finally, a simulation analysis is carried out on the optimization of the production material distribution of a smart gas meter workshop owned by K Company, which is an electronic assembly manufacturing company. We used MATLAB software for the case company logistics distribution route model for data analysis and solving. Due to the consideration of carbon emissions, we did not consider two kinds of experiments, which were two different cases of the optimal path. The experimental results verify that the distribution optimization scheduling model can meet the demands for immediate material distribution in the production workshop, which is conducive to improving material distribution efficiency, reducing logistics costs and achieving the goal of lowering carbon emissions. This optimization model has a certain utility in that in the current context of aiming for carbon neutral and carbon peaking, early low carbon distribution layout can reduce the environmental cost of the enterprise, making material distribution a more environmental economic path. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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17 pages, 1786 KiB  
Article
Optimization of Low-Carbon and Highly Efficient Turning Production Equipment Selection Based on Beetle Antennae Search Algorithm (BAS)
by Yongmao Xiao, Guohua Chen, Hao Zhang and Xiaoyong Zhu
Processes 2023, 11(3), 911; https://doi.org/10.3390/pr11030911 - 16 Mar 2023
Cited by 1 | Viewed by 1124
Abstract
Reducing carbon emission and raising efficient production are the important goals of modern enterprise production process. The same product can be produced by a variety of equipment, and the carbon emissions and processing time of different equipment vary greatly. Choosing suitable production equipment [...] Read more.
Reducing carbon emission and raising efficient production are the important goals of modern enterprise production process. The same product can be produced by a variety of equipment, and the carbon emissions and processing time of different equipment vary greatly. Choosing suitable production equipment is an important method for manufacturing enterprises to achieve the efficient emission reduction of production process. However, the traditional production equipment selection mode only gives qualitative results, and it is difficult to provide effective advice for enterprises to choose suitable equipment under the needs of carbon neutrality. To solve this problem, this paper systematically analyzes carbon emission and the time of the turning production process, and a unified calculation model for carbon emission and efficient production of multi-type processing equipment is established. The important point of the article is to research the diversity among between carbon emissions and efficiency levels of the same product produced by different devices. The carbon emissions and efficiency levels of different kinds of equipment can be calculated by the BAS algorithm. By turning a shaft part as an example, the results show that this method can calculate the optimal value of carbon emissions and efficiency of the same product produced by different equipment and can provide suggestions for enterprises to select appropriate equipment for low-carbon and efficient production. This paper provides a reference for further research on the quantitative calculation model for the selection of high-efficiency and low-carbon production equipment. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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16 pages, 2992 KiB  
Article
Research on Multiple Constraints Intelligent Production Line Scheduling Problem Based on Beetle Antennae Search (BAS) Algorithm
by Yani Zhang, Haoshu Xu, Jun Huang and Yongmao Xiao
Processes 2023, 11(3), 904; https://doi.org/10.3390/pr11030904 - 16 Mar 2023
Cited by 1 | Viewed by 1334
Abstract
Aiming at the intelligent production line scheduling problem, a production line scheduling method considering multiple constraints was proposed. Considering the constraints of production task priority, time limit, and urgent task insertion, a production process optimization scheduling calculation model was established with the minimum [...] Read more.
Aiming at the intelligent production line scheduling problem, a production line scheduling method considering multiple constraints was proposed. Considering the constraints of production task priority, time limit, and urgent task insertion, a production process optimization scheduling calculation model was established with the minimum waiting time and minimum completion time as objectives. The BAS was used to solve the problem, and a fast response mechanism for emergency processing under multiple constraints was established. Compared with adaptive particle swarm optimization (APSO) and non-dominated sorting genetic algorithm-II (NSGA-II) operation, this algorithm showed its superiority. The practical application in garment processing enterprises showed that the method was effective and can reduce the completion time and waiting time. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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26 pages, 5937 KiB  
Article
Structural Optimization of High-Pressure Polyethylene Cyclone Separator Based on Energy Efficiency Parameters
by Baisong Hu, Shuo Liu, Chuanzhi Wang and Bingjun Gao
Processes 2023, 11(3), 691; https://doi.org/10.3390/pr11030691 - 24 Feb 2023
Viewed by 1617
Abstract
The high-pressure polyethylene process uses cyclone separators to separate ethylene gas, polyethylene, and its oligomers. The oligomers larger than 10 microns that cannot be separated must be filtered through a filter to prevent them from entering the compressor and affecting its normal operation. [...] Read more.
The high-pressure polyethylene process uses cyclone separators to separate ethylene gas, polyethylene, and its oligomers. The oligomers larger than 10 microns that cannot be separated must be filtered through a filter to prevent them from entering the compressor and affecting its normal operation. When the separation efficiency of the cyclone separator is low, the filter must be cleaned more frequently, which will reduce production efficiency. Research shows that improving the separation efficiency of the separator is beneficial for the separation of small-particle oligomers and reduces the frequency of filter cleaning. For this reason, Computational Fluid Dynamics simulations were performed for 27 sets of cyclone separators to determine the effects of eight structural factors (cylinder diameter, cylinder height, cone diameter, cone height, guide vane height, guide vane angle, exhaust pipe extension length, and umbrella structure height) on separation efficiency and pressure drop. The equations for separation efficiency and pressure drop using these eight factors and the equations based on energy-efficiency parameters were determined. The optimization analysis showed that separation efficiency can be improved by 98.7% under the premise that the pressure drop is only increased by 8.2%. By applying the improved structure to the high-pressure polyethylene process, separation efficiency is increased by 17.7%, which could effectively reduce the frequency of filter cleaning for this process, and thereby greatly improve production efficiency. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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16 pages, 4542 KiB  
Article
Application of PLC-Based Spectrophotometric System Nitrogen Protection Device to Automated Direct Measurement of Target Substances in Zinc Hydrometallurgy
by Xuefei Zhang, Ning Duan, Linhua Jiang, Fuyuan Xu, Zhaosheng Yu, Wen Cheng, Wenbao Lv and Yibing Qiu
Processes 2023, 11(3), 672; https://doi.org/10.3390/pr11030672 - 22 Feb 2023
Cited by 4 | Viewed by 1505
Abstract
Due to the fast material reaction in zinc hydrometallurgy, the traditional national standard photometric method cannot capture the characteristic information of target substances in real time. Herein, a nitrogen protection device is built based on ultraviolet spectrophotometry, supplemented by a programmable logic controller [...] Read more.
Due to the fast material reaction in zinc hydrometallurgy, the traditional national standard photometric method cannot capture the characteristic information of target substances in real time. Herein, a nitrogen protection device is built based on ultraviolet spectrophotometry, supplemented by a programmable logic controller (PLC), to form an automatic control system for the direct detection of target substances (SO42−, Pb2+ and S2−) in zinc hydrometallurgy. The baseline straightness comparison results show that the nitrogen atmosphere can effectively improve the stability of the instrument. Furthermore, the detection sensitivity of SO42−, Pb2+ and S2− under the nitrogen atmosphere is higher than that of the air atmosphere, manifesting in sensitivity increases of 16.23%, 18.05% and 17.91%, respectively. Additionally, devices based on PLC systems show advantages over manual control both in states feedback and information backtrack. Moreover, the regulation time and nitrogen consumption during the regulation process are reduced by 80% and 75%, respectively, which effectively reduces the test cost and improves the equipment utilization rate (from four cycles per day to six cycles per day). The device can meet the requirements of different target substances and different process conditions by changing the electronic control parts and air source, so it has great application potential in the automatic direct measurement of target substances in zinc hydrometallurgy. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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23 pages, 3532 KiB  
Article
Identification of Key Brittleness Factors for the Lean–Green Manufacturing System in a Manufacturing Company in the Context of Industry 4.0, Based on the DEMATEL-ISM-MICMAC Method
by Xiaoyong Zhu, Yu Liang, Yongmao Xiao, Gongwei Xiao and Xiaojuan Deng
Processes 2023, 11(2), 499; https://doi.org/10.3390/pr11020499 - 7 Feb 2023
Cited by 4 | Viewed by 2318
Abstract
In the context of Industry 4.0, the lean–green manufacturing system has brought many advantages and challenges to industrial participants. Security is one of the main challenges encountered in the new industrial environment, because smart factory applications can easily expose the vulnerability of manufacturing [...] Read more.
In the context of Industry 4.0, the lean–green manufacturing system has brought many advantages and challenges to industrial participants. Security is one of the main challenges encountered in the new industrial environment, because smart factory applications can easily expose the vulnerability of manufacturing and threaten the operational security of the whole system. It is difficult to address the problem of the brittleness factor in manufacturing systems. Therefore, building on vulnerability theory, this study proposes a vulnerability index system for lean–green manufacturing systems in a manufacturing company in the context of Industry 4.0. The index has four dimensions: human factors, equipment factors, environmental factors, and other factors. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was used to calculate the degree of influence, the degree of being influenced, and the centrality and causes of the factors. The causal relationships and key influences between the factors were identified. Then, the dependence and hierarchy of each of the key influencing factors were analyzed using the Matrix-Based Cross-Impact Multiplication Applied to Classification (MICMAC) and Interpretative Structural Model (ISM) methods, and a hierarchical structural model of the factors was constructed. Finally, an intelligent manufacturing system that produces a micro-acoustic material and device was used as an example to verify the accuracy of the proposed method. The results show that the method not only identifies the key brittleness factors in a lean–green manufacturing system but can also provide a guarantee for the safe operation of a manufacturing system. This study provides theoretical guidance for the effective management of intelligent manufacturing systems; moreover, it lays a foundation and provides a new methodology for assessing the vulnerability of manufacturing systems. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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12 pages, 1493 KiB  
Article
Research on Assembly Sequence Optimization Classification Method of Remanufacturing Parts Based on Different Precision Levels
by Yongmao Xiao, Jincheng Zhou, Shixiong Xing and Xiaoyong Zhu
Processes 2023, 11(2), 383; https://doi.org/10.3390/pr11020383 - 26 Jan 2023
Cited by 2 | Viewed by 955
Abstract
Aiming at resolving the problem of low assembly accuracy and the difficulty of guaranteeing assembly quality of remanufactured parts, an optimization classification method for the assembly sequence of remanufactured parts based on different accuracy levels is proposed. By studying the characteristics of recycled [...] Read more.
Aiming at resolving the problem of low assembly accuracy and the difficulty of guaranteeing assembly quality of remanufactured parts, an optimization classification method for the assembly sequence of remanufactured parts based on different accuracy levels is proposed. By studying the characteristics of recycled parts, based on the requirement that the quality of remanufactured products not be lower than that of the assembly quality of new products, the classification selection matching constraints of remanufactured parts are determined, and the classification selection matching optimization models of remanufactured parts with different precision levels is established. An algorithm combining particle swarm optimization and a genetic algorithm is proposed to solve the model and obtain the optimal assembly sequence. Taking the remanufacturing assembling of a 1.4 TGDI engine crank and a connecting rod mechanism as an example, the comparison of quality data shows that this method can effectively improve the qualified rate of assembly, reduce the cost of after-sale claims, provide new theories and methods for remanufacturing enterprises that need hierarchical assembly, and provide effective guidance for the development of the remanufacturing industry. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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