IET Collaborative Intelligent Manufacturing最新文献_第5页

Ensemble evolutionary algorithms equipped with Q-learning strategy for solving distributed heterogeneous permutation flowshop scheduling problems considering sequence-dependent setup time 配备 Q-learning 策略的集合进化算法，用于解决考虑序列设置时间的分布式异构包络流车间调度问题

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2024-03-15 DOI: 10.1049/cim2.12099

Fubin Liu, Kaizhou Gao, Dachao Li, Ali Sadollah

{"title":"Ensemble evolutionary algorithms equipped with Q-learning strategy for solving distributed heterogeneous permutation flowshop scheduling problems considering sequence-dependent setup time","authors":"Fubin Liu, Kaizhou Gao, Dachao Li, Ali Sadollah","doi":"10.1049/cim2.12099","DOIUrl":"https://doi.org/10.1049/cim2.12099","url":null,"abstract":"A distributed heterogeneous permutation flowshop scheduling problem with sequence-dependent setup times (DHPFSP-SDST) is addressed, which well reflects real-world scenarios in heterogeneous factories. The objective is to minimise the maximum completion time (makespan) by assigning jobs to factories, and sequencing them within each factory. First, a mathematical model to describe the DHPFSP-SDST is established. Second, four meta-heuristics, including genetic algorithms, differential evolution, artificial bee colony, and iterated greedy (IG) algorithms are improved to optimally solve the concerned problem compared with the other existing optimisers in the literature. The Nawaz-Enscore-Ham (NEH) heuristic is employed for generating an initial solution. Then, five local search operators are designed based on the problem characteristics to enhance algorithms' performance. To choose the local search operators appropriately during iterations, Q-learning-based strategy is adopted. Finally, extensive numerical experiments are conducted on 72 instances using 5 optimisers. The obtained optimisation results and comparisons prove that the improved IG algorithm along with Q-learning based local search selection strategy shows better performance with respect to its peers. The proposed algorithm exhibits higher efficiency for scheduling the concerned problems.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12099","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation-based optimisation for order release of printed circuit board workshop with process switching constraints 基于仿真的印制电路板车间订单释放优化（带工艺切换约束

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2024-03-11 DOI: 10.1049/cim2.12098

Lei Yue, Qing Xu, Hao Wang, Mudassar Rauf, Jabir Mumtaz

{"title":"Simulation-based optimisation for order release of printed circuit board workshop with process switching constraints","authors":"Lei Yue, Qing Xu, Hao Wang, Mudassar Rauf, Jabir Mumtaz","doi":"10.1049/cim2.12098","DOIUrl":"https://doi.org/10.1049/cim2.12098","url":null,"abstract":"Workload control (WLC) is usually employed to make order release to attain workload balance, satisfactory delivery rate and high production efficiency. However, in the real production environment of printed circuit board (PCB) industries, slight modifications in the product process shifts the bottleneck resources which leads to misjudge the effect of WLC and may ultimately increase the lateness of orders. Therefore, this research focuses on the order release problem of PCB production system considering main process flow and shifting of bottlenecks. At first, certain improvements are proposed on the classic WLC method and two order release control strategies based on process switching are designed to generate order release plan on the basis of Lancaster University Management School Corrected Order Release method. Furthermore, different scheduling rules are investigated along with the upper workload limits on the PCB system simultaneously. Finally, a simulation model is developed to analyse the impact of order release methods on the system performance through simulation experiments. Furthermore, extensive simulation experiments for different scheduling rules on bottleneck resource and different workload upper limit ratios are also carried out in the current research. Simulation results show that the process order release control strategy based on process switching has a strong adaptability in PCB manufacturing system.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140104337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent algorithms and methodologies for low-carbon smart manufacturing: Review on past research, recent developments and future research directions 低碳智能制造的智能算法和方法：回顾过去的研究、最近的发展和未来的研究方向

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2024-01-26 DOI: 10.1049/cim2.12094

Sudhanshu Joshi, Manu Sharma

{"title":"Intelligent algorithms and methodologies for low-carbon smart manufacturing: Review on past research, recent developments and future research directions","authors":"Sudhanshu Joshi, Manu Sharma","doi":"10.1049/cim2.12094","DOIUrl":"10.1049/cim2.12094","url":null,"abstract":"Significant attention has been given to low-carbon smart manufacturing (SM) as a strategy for promoting sustainability and carbon-free emissions in the manufacturing industry. The implementation of intelligent algorithms and procedures enables the attainment and enhancement of low-carbon clever manufacturing processes. These algorithms facilitate real-time monitoring and predictive maintenance, ensuring efficient and sustainable operations and data-driven decision-making, increasing resource utilisation, waste reduction, and energy efficiency. The research examines the utilisation of algorithms in the context of low-carbon smart manufacturing, encompassing machine learning, optimisation algorithms, and predictive analytics. A comprehensive literature evaluation spanning from 2011 to 2023 is conducted to assess the significance of low-carbon approaches in the context of smart manufacturing. An integrated approach is used using content analysis, network data analysis, bibliometric analysis, and cluster analysis. Based on the published literature the leading contributors to low-carbon manufacturing research are India, China, United States, United Kingdom, Singapore, and Italy. The results have shown five main themes—Low-carbon smart manufacturing and applications of Algorithms; Industry 4.0 technologies for low-carbon manufacturing; low carbon and green manufacturing; Low-carbon Manufacturing, and Product design and control; Lean Systems and Smart Manufacturing. The purpose of this study is to provide policymakers and researchers with a guide for the academic development of low-carbon manufacturing by evaluating research efforts in light of identified research deficits.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139593719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Factors influencing the adoption of industrial internet of things for the manufacturing and production small and medium enterprises in developing countries 影响发展中国家中小型制造和生产企业采用工业物联网的因素

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2024-01-16 DOI: 10.1049/cim2.12093

Sajid Shah, Syed Hamid Hussain Madni, Siti Zaitoon Bt. Mohd Hashim, Javed Ali, Muhammad Faheem

{"title":"Factors influencing the adoption of industrial internet of things for the manufacturing and production small and medium enterprises in developing countries","authors":"Sajid Shah, Syed Hamid Hussain Madni, Siti Zaitoon Bt. Mohd Hashim, Javed Ali, Muhammad Faheem","doi":"10.1049/cim2.12093","DOIUrl":"https://doi.org/10.1049/cim2.12093","url":null,"abstract":"Small and Medium Enterprises (SMEs) are steadily moving in the direction of implementing digital and smart technologies, including the Industrial Internet of Things (IIoT) for improving their products and services. The adoption of IIoT allows manufactures and producers to make quick decisions for improving productivity and quality in real-time. For this purpose, the era of digital industrial revolution from IR 1.0 to IR 5.0 is briefly explained. In this research study, the authors have reviewed and analysed the existing reviews, surveys and technical research studies on IIoT technologies for the manufacturing and production SMEs to highlight the concern raised. Forty-seven (47) influencing factors are identified and classified into four groups based on the TOEI framework. Based on the identified influencing factors, IIoT adoption model is proposed for the manufacturing and production SMEs to adopt the new IIoT technologies in their business environments. Furthermore, a comparative analysis of the influencing factors has been done for the adoption of IIoT to increase efficiency, productivity and competitiveness for the manufacturing and production SMEs in developing countries. The proposed IIoT adoption model will help future policymakers and stakeholders to develop policies and strategies for the successful adoption and implementation of IIoT in manufacturing and production SMEs in developing countries. Also, recommendations are suggested to encourage IIoT adoption in production and manufacturing environments so that manufacturers and producers can respond easily and quickly to highly changing demands, product trends, skills gaps and other unexpected challenges in the future.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139480447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A two-stage solution method for the design problem of medium-thick plates in steel plants 钢铁厂中厚板设计问题的两阶段求解法

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2024-01-13 DOI: 10.1049/cim2.12091

Gongzhuang Peng, Boyu Zhang, Shenglong Jiang

{"title":"A two-stage solution method for the design problem of medium-thick plates in steel plants","authors":"Gongzhuang Peng, Boyu Zhang, Shenglong Jiang","doi":"10.1049/cim2.12091","DOIUrl":"https://doi.org/10.1049/cim2.12091","url":null,"abstract":"The medium-thick plate is an important type of steel product widely used in construction and engineering machinery. The orders are usually characterised by multiple specifications and small quantities. The plate design is an important part in the production process of medium-thick plate, which includes the combination of sub-plates and the size design of the motherboard. A multi-objective model for medium-thick plate design is proposed based on the 2D bin packing model, comprehensively considering spatial and size constraints of the plate production. A two-stage genetic algorithm (TSGA) is developed to solve the proposed model. In the first stage, an improved GA is used to optimise the corresponding relationship between the sub-plates and the slab, as well as the size of the motherboard. In the second stage, an exact algorithm based on the integer programming model is applied to calculate the order layout to minimise the surplus materials. To validate the proposed method, computational experiments are conducted based on actual production data from a steel plant. The experimental results show the effectiveness of the TSGA algorithm in solving the plate design problem.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139435109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimising digital signal processor-based defect detection in smart manufacturing with lightweight convolutional neural networks 利用轻量级卷积神经网络优化智能制造中基于数字信号处理器的缺陷检测

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2024-01-12 DOI: 10.1049/cim2.12092

Han Yue, Rucen Wang, Yi Gao, Ailing Xia, Kaikai Su, Jianhua Zhang

{"title":"Optimising digital signal processor-based defect detection in smart manufacturing with lightweight convolutional neural networks","authors":"Han Yue, Rucen Wang, Yi Gao, Ailing Xia, Kaikai Su, Jianhua Zhang","doi":"10.1049/cim2.12092","DOIUrl":"https://doi.org/10.1049/cim2.12092","url":null,"abstract":"Industrial defect detection is an important part of intelligent manufacturing, and Internet of things (IoT)-based defect detection is receiving more and more attention. Although deep learning (DL) can help defect detection reduce the cost and improve the accuracy of traditional manual quality inspection, DL requires huge computational resources and is difficult to be simply deployed on IoT devices with limited computational power and memory resources. Digital signal processor (DSP) is an important IoT device with small size, high performance and low energy consumption, which has been widely used in intelligent manufacturing. In order to perform accurate defect detection on DSP, the authors proposed various optimisation strategies and then used a parallel scheme to scale the model to execute on multiple cores. The authors’ method evaluated it on Northeastern University Surface Defect Dataset, Magnetic Tile Defect Dataset, Rail Surface Defect Dataset and Silk Cylinder Defect Dataset, and the experimental results showed that the authors’ method obtains faster speeds without accuracy loss compared to running the same Convolutional Neural Networks model on a mainstream desktop CPU. This means that the authors’ method can realise efficient and accurate defect detection on IoT devices with limited computational power and memory resources, which opens up new possibilities for future development in the field of smart manufacturing.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139434960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Delaunay meshes simplification with multi-objective optimisation and fine tuning 通过多目标优化和微调简化 Delaunay 网格

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-12-22 DOI: 10.1049/cim2.12088

Linkun Fan, Caiyun Wu, Fazhi He, Bo Fan, Yaqian Liang

{"title":"Delaunay meshes simplification with multi-objective optimisation and fine tuning","authors":"Linkun Fan, Caiyun Wu, Fazhi He, Bo Fan, Yaqian Liang","doi":"10.1049/cim2.12088","DOIUrl":"https://doi.org/10.1049/cim2.12088","url":null,"abstract":"3D meshes simplification plays an important role in many industrial domains. The two goals of Delaunay mesh simplification are maintaining high geometric fidelity and reducing mesh complexity. However, they are conflicting and cannot solved by gradient. Such limitation prevents existing Delaunay mesh simplification to obtain a small enough number of vertices and promising fidelity at the same time. To address these issues, this paper proposes an evolutionary multi-objective approach for Delaunay mesh simplification. Firstly, the authors replace the previous fixed error-bound threshold by the designed adaptive segment-specific thresholds. Secondly, a constrained simplification is performed through a series of edge collapses that satisfy both Delaunay and error constraints. Next, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to solve the multi-objective problem to search for the optimal trade-off threshold sequences. Finally, a fine-tuning method is designed to further enhance the geometric fidelity of the simplified mesh. Experimental results demonstrate that the authors’ method consistently achieves a satisfactory balance between the approximation error and number of vertices, outperforming existing state-of-the-art methods.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 4","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139042041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The methods of task pre-allocation and reallocation for multi-UAV cooperative reconnaissance mission 多无人机协同侦察任务的任务预分配和再分配方法

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-12-19 DOI: 10.1049/cim2.12090

Gang Wang, Xiao Lv, Liangzhong Cui, Xiaohu Yan

{"title":"The methods of task pre-allocation and reallocation for multi-UAV cooperative reconnaissance mission","authors":"Gang Wang, Xiao Lv, Liangzhong Cui, Xiaohu Yan","doi":"10.1049/cim2.12090","DOIUrl":"https://doi.org/10.1049/cim2.12090","url":null,"abstract":"Nowadays, multi unmanned aerial vehicle (multi-UAV) systems have been widely used in battlefield. The rationality of mission plan can directly affect the effectiveness of multi-UAV system. The existing multi-UAV task allocation model lack a comprehensive modelling of task pre-allocation and task reallocation issues. However, in actual task execution, task pre-allocation and task reallocation are a holistic problem. Therefore, based on the background of multi-UAV cooperative reconnaissance, the authors establish a multi-UAV cooperative reconnaissance task pre-allocation and reallocation model (MCRTPR). There are two kinds of task allocation in MCRTPR model. One is task pre-allocation, which is a static task allocation before the mission begin. Another is task reallocation, that is a dynamic task allocation during the mission. For task pre-allocation, a particle swarm optimisation algorithm based on experience pool (EPPSO) is proposed. And for task reallocation, the authors design a partial task reallocation algorithm based on contract network protocol (CNP-PTR). The experimental results show that, compared with some state-of-the-art algorithms, EPPSO can get the lowest fitness value under various experimental conditions, and CNP-PTR is able to handle task reallocation problem caused by multiple kinds of dynamic events.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 4","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138739872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Feasibility assessment of remanufacturing waste sheet steel into angle mesh steel 将废钢板再制造成角钢网的可行性评估

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-12-15 DOI: 10.1049/cim2.12089

Ziyad Tariq Abdullah

{"title":"Feasibility assessment of remanufacturing waste sheet steel into angle mesh steel","authors":"Ziyad Tariq Abdullah","doi":"10.1049/cim2.12089","DOIUrl":"https://doi.org/10.1049/cim2.12089","url":null,"abstract":"As a better alternative to the energy-intensive process of recycling waste sheet steel (WSS) from the exterior components of end-of-life vehicles to produce new steel, the feasibility of remanufacturing WSS into angle mesh steel (AMS) for construction applications is evaluated. A remanufacturing unit with a capacity of 1278 m2/day of WSS (30,000 vehicle/year) was evaluated using a triple-bottom-line sustainability analysis of the technological, economic, and environmental feasibilities by hybrid defuzzification–curve-fitting, solid-waste recoverability management, and weighting methods. Based on the remanufacturing productivity, an economic feasibility index was calculated considering the sales potential and profit, while the energy and CO2 emission savings were used to evaluate the environmental feasibility. The technical feasibility considered machine parameters and topological properties of the WSS. The Volkswagen Passat has the best remanufacturability of 200 analysed vehicle models. Remanufacturability indexes of 0.61 and 0.86 were calculated, giving remanufacturing efficiencies of 58%–82%. All feasibility indexes exceed literature thresholds, indicating that the proposed remanufacturing process is a sustainable business strategy and contributes to the United Nations Sustainability Goals of climate action; responsible consumption and production; no poverty; and industry, innovation, and infrastructure.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 4","pages":""},"PeriodicalIF":8.2,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138679016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new design approach of hardware implementation through natural language entry 一种基于自然语言输入的硬件实现设计新方法

IF 8.2

IET Collaborative Intelligent Manufacturing Pub Date : 2023-11-06 DOI: 10.1049/cim2.12087

Kaiyuan Yang, Haotian Liu, Yuqin Zhao, Tiantai Deng

引用次数: 0