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Mathematics
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Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering
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Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 6220

Special Issue Editors

Prof. Dr. Zhongwei Liang

E-Mail Website
Guest Editor
Guangdong Research Centre for Strengthen Grinding and High-Performance Micro\Nano Machining, Guangzhou Industry & Information Technology Institute for Intelligent Robotic Equipment, Guangzhou University, Guangzhou 510006, China
Interests: advanced high-performance manufacturing; intelligent robotic equipment; manufacturing mechanics of AWJ grinding; jet strengthen-modified machining; turbulence mechanics; intelligent agricultural equipment
Prof. Dr. Yong Li

E-Mail Website
Guest Editor
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China
Interests: design of vapor-liquid channels for micro heat pipes; wick manufacturing technology; analytical modeling & numerical modeling of micro heat pipes

Special Issue Information

Dear Colleagues,

Intelligent manufacture is a key national development field, it lies at the core of many contemporary tools used in mechanical engineering. Based on its service performance demands in meeting the requirements of “High precision retention, High energy efficiency and consumption reduction, High fatigue-resistance life, High loading-strength, and High operational reliability”, many novel approaches have been proposed to realize the precise shape/property controlling manufacture of robotic equipment. They represent the manufacturing mechanism in mechanical engineering, control engineering, etc.

The theoretical analysis of intelligent manufacturing is important not only because it confirms the appropriateness of mechanical machining. It also provides insight into the manufacturer’s limitations and hints for future research. This research field deserves high innovative evaluation in the subjects of jet strengthen-modified machining, and precise control of automation production line, which provides important tools to improve the machining accuracy, material strength, and actual working performance of robotic equipment. It highlights the superiorities of theoretical analysis and facilitates remarkable performance improvement in the intelligent manufacturing field. So that it could be highly academic-valued due to its thorough clarification of high-performance manufacturing, and intelligent manufacture, etc. This research field has great significance to solve the theoretical and technological difficulties of high-end equipment.

You are cordially invited to submit papers related to all aspects of mathematical approaches in intelligent manufacture and mechanical engineering, both theoretical and applicational. This involves (but is not limited to) advanced high-performance manufacturing; intelligent robotic equipment; manufacturing mechanics of abrasive machining; jet strengthen-modified grinding; magnetic drive and its control technology; motorized spindle; electrical discharge machining; additive manufacturing; laser cutting; laser cleaning; laser shock processing; green manufacturing; etching; electrodeposition; surface treatment; mathematical models of micro machining performance; magnetic drive and its control technology; motorized spindle; electrical discharge machining; turbulence mechanics; combinatorial optimization; robust optimization, etc.

Prof. Dr. Zhongwei Liang
Prof. Dr. Yong Li
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • additive manufacturing
  • laser cleaning
  • laser shock processing
  • laser cutting
  • green manufacturing robust optimization
  • wick manufacturing technology mathematical models of heat transmission

Published Papers (5 papers)

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Research

18 pages, 4605 KiB  
Article
Predicting and Enhancing the Multiple Output Qualities in Curved Laser Cutting of Thin Electrical Steel Sheets Using an Artificial Intelligence Approach
by Muhamad Nur Rohman, Jeng-Rong Ho, Chin-Te Lin, Pi-Cheng Tung and Chih-Kuang Lin
Mathematics 2024, 12(7), 937; https://doi.org/10.3390/math12070937 - 22 Mar 2024
Viewed by 526
Abstract
This study focused on the efficacy of employing a pulsed fiber laser in the curved cutting of thin, non-oriented electrical steel sheets. Experiments were conducted in paraffinic oil by adjusting the input process parameters, including laser power, pulse frequency, cutting speed, and curvature [...] Read more.
This study focused on the efficacy of employing a pulsed fiber laser in the curved cutting of thin, non-oriented electrical steel sheets. Experiments were conducted in paraffinic oil by adjusting the input process parameters, including laser power, pulse frequency, cutting speed, and curvature radius. The multiple output quality metrics included kerf width, inner and outer heat-affected zones, and re-welded portions. Analyses of the Random Forest Method and Response Surface Method indicated that laser pulse frequency was the most important variable affecting the cut quality, followed by laser power, curvature radius, and cutting speed. To improve cut quality, an innovative artificial intelligence (AI) approach incorporating a deep neural network (DNN) model and a modified equilibrium optimizer (M-EO) was proposed. Initially, the DNN model established correlations between input parameters and cut quality aspects, followed by M-EO pinpointing optimal cut qualities. Such an approach successfully identified an optimal set of laser process parameters, even beyond the specified process window from the initial experiments on curved cuts, resulting in significant enhancements confirmed by validation experiments. A comparative analysis showcased the developed models’ superior performance over prior studies. Notably, while the models were initially developed based on the results from curved cuts, they proved adaptable and capable of yielding comparable outcomes for straight cuts as well. Full article
(This article belongs to the Special Issue Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering)
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24 pages, 3818 KiB  
Article
Separation and Calibration Method of Structural Parameters of 6R Tandem Robotic Arm Based on Binocular Vision
by Rui Wang, Xiangyu Guo, Songmo Li and Lin Wang
Mathematics 2023, 11(11), 2491; https://doi.org/10.3390/math11112491 - 29 May 2023
Cited by 1 | Viewed by 1098
Abstract
In this paper, a kinematic separation calibration method of 6R series manipulator is proposed, and its absolute accuracy is improved by a binocular camera and standard sphere. First, a geometric error mapping model for the robotic arm was established, and the error parameters [...] Read more.
In this paper, a kinematic separation calibration method of 6R series manipulator is proposed, and its absolute accuracy is improved by a binocular camera and standard sphere. First, a geometric error mapping model for the robotic arm was established, and the error parameters were divided into position parameters and attitude parameters for calibration purposes. Second, in the process of solving error parameters using numerical algorithms, it is easy to encounter matrix ill-conditioned problems. The spectral correction iteration method is introduced to improve the calculation accuracy. Third, three standard balls are installed at the end of the robotic arm as markers, and the center coordinates are measured using a binocular camera to obtain the actual end pose parameters. To verify the effectiveness of the proposed method, a simulation model verification was designed, and the results showed that the separation calibration method was the best. Finally, the IRB-1200 robot was successfully calibrated using the proposed method; the average robot position and angle error after calibration was significantly decreased. The position accuracy was improved by 66.9%, and the attitude accuracy was improved by 86.2%. Full article
(This article belongs to the Special Issue Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering)
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17 pages, 4034 KiB  
Article
Three-Parameter Estimation Method of Multiple Hybrid Weibull Distribution Based on the EM Optimization Algorithm
by Xiaowei Dong, Feng Sun, Fangchao Xu, Qi Zhang, Ran Zhou, Liang Zhang and Zhongwei Liang
Mathematics 2022, 10(22), 4337; https://doi.org/10.3390/math10224337 - 18 Nov 2022
Cited by 3 | Viewed by 1400
Abstract
The hybrid Weibull distribution model can describe the failure rules of electromechanical products more accurately than the single Weibull distribution model, and it can improve the accuracy of reliability analysis. However, the hybrid Weibull distribution model is also more complex, and the multi-parameter [...] Read more.
The hybrid Weibull distribution model can describe the failure rules of electromechanical products more accurately than the single Weibull distribution model, and it can improve the accuracy of reliability analysis. However, the hybrid Weibull distribution model is also more complex, and the multi-parameter estimation is more difficult. In this paper, a reliability mathematical model based on the two-fold three-parameter hybrid Weibull distribution model was established, an EM optimization algorithm was derived for its solution, and a practical initial parameter selection scheme was designed. The validity of the model and the algorithm were verified, and goodness-of-fit tests were conducted through an arithmetic example. The results showed that the initial value selection scheme proposed in this paper and the corresponding solution algorithm could solve all the parameters and weight coefficients to be estimated for each sub distribution, and the obtained failure probability fitting curve had a high fit with the actual sample data, which effectively solved the multi-parameter estimation problem of the multiple mixed Weibull distribution model. Full article
(This article belongs to the Special Issue Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering)
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30 pages, 4313 KiB  
Article
Multi-Objective Material Logistics Planning with Discrete Split Deliveries Using a Hybrid NSGA-II Algorithm
by Weikang Fang, Zailin Guan, Peiyue Su, Dan Luo, Linshan Ding and Lei Yue
Mathematics 2022, 10(16), 2871; https://doi.org/10.3390/math10162871 - 11 Aug 2022
Cited by 4 | Viewed by 1309
Abstract
To schedule material supply intelligently and meet the production demand, studies concerning the material logistics planning problem are essential. In this paper, we consider the problem based on the scenario that more than one vehicle may visit each station in batches. The primary [...] Read more.
To schedule material supply intelligently and meet the production demand, studies concerning the material logistics planning problem are essential. In this paper, we consider the problem based on the scenario that more than one vehicle may visit each station in batches. The primary objective is to satisfy the demands in the time windows, followed by logistics planning with the minimum vehicles and travel time as the optimization objective. We construct a multi-objective mixed-integer programming model for the scenario of discrete material supply in workshops. First, we propose a hybrid heuristic algorithm combining NSGA-II and variable neighborhood search. This proposed algorithm combines the global search capability of NSGA-II and the strong local search capability, which can balance intensification and diversification well. Second, to maintain the diversity of population, we design the population diversity strategy and various neighborhood operators. We verify the effectiveness of the hybrid algorithm by comparing with other algorithms. To test the validity of the proposed problem, we have carried out research and application in a construction machinery enterprise. Full article
(This article belongs to the Special Issue Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering)
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24 pages, 9258 KiB  
Article
Optimal Control of PC-PLC Virus-Mutation and Multi-Delay Propagation Model in Distribution Network CPS
by Yingying Su, Zijing Qiu, Guiyun Liu and Zhongwei Liang
Mathematics 2022, 10(16), 2840; https://doi.org/10.3390/math10162840 - 09 Aug 2022
Viewed by 1102
Abstract
The intelligent manufacturing of power systems has led to many challenges. The cyber-physical system (CPS) was introduced to solve the problem of insufficient integration of equipment and systems. It brings advantages, but also risks. In the distribution network CPS, malicious attacks on the [...] Read more.
The intelligent manufacturing of power systems has led to many challenges. The cyber-physical system (CPS) was introduced to solve the problem of insufficient integration of equipment and systems. It brings advantages, but also risks. In the distribution network CPS, malicious attacks on the PC-PLC communication network can cause significant incidents and affect system safety. The paper discusses two challenges, of possible mutated virus attacks and multi-delay in the PC-PLC coupled network. We present for the first time a virus-mutation and multi-delay propagation model. Then, to effectively control the virus propagation in the network and minimize the cost, the paper proposes five control measures, introduces their possible control combinations, and solves the optimal control problem with the Pontryagin maximum theorem. Finally, simulations verify the optimal control strategies for all combinations. By comparing the effects of maximum control, minimum control, average control, and optimal control, the optimal control strategy has been proven to be effective. Full article
(This article belongs to the Special Issue Mathematical Approaches in Intelligent Manufacture and Mechanical Engineering)
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