Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Disassembly sequence planning using component-joint graph and ant colony optimization

Disassembly sequence planning is an important step of mechanical maintenance. This article presents an integrated study about the generation and optimizing algorithm of the disassembly sequence. Mechanical products are divided into two categories of components and connectors. The article uses component-joint graph to represent assembly constraints, including the incidence constraints are represented by incidence matrix and the interference constraints are represented by interference constraints. The inspiring factor and pheromone matrix are calculated according to assembly constraints. Then the ant generates its own disassembly sequences one by one and updates the inspiring factor and pheromone matrix. After all iterations, the best disassembly sequence planning of components and connectors are given. Finally, an application instance of the disassembly sequence of the jack is presented to illustrate the validity of this method.

Convolutional Graph Neural Network with Novel Loss Strategies for Daily Temperature and Precipitation Statistical Downscaling over South China

Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.

Using genetic/simulated annealing algorithm to solve disassembly sequence planning

Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binaxy-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.

Disassemblability Modeling Technology of Configurable Product Based on Disassembly Constraint Relation Weighted Design Structure Matrix(DSM)

The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disassemblability. The disassemblability modeling technology for configurable product based on disassembly constraint relation weighted design structure matrix （DSM） is proposed. Major factors affecting the disassemblability of configurable product are analyzed, and the disassembling degrees between components in configurable product are obtained by calculating disassembly entropies such as joint type, joint quantity, disassembly path, disassembly accessibility and material compatibility. The disassembly constraint relation weighted DSM of configurable product is constructed and configuration modules are formed by matrix decomposition and tearing operations. The disassembly constraint relation in configuration modules is strong coupling, and the disassembly constraint relation between modules is weak coupling, and the disassemblability configuration model is constructed based on configuration module. Finally, taking a hydraulic forging press as an example, the decomposed weak coupling components are used as configuration modules alone, components with a strong coupling are aggregated into configuration modules, and the disassembly sequence of components inside configuration modules is optimized by tearing operation. A disassemblability configuration model of the hydraulic forging press is constructed. By researching the disassemblability modeling technology of product configuration design based on disassembly constraint relation weighted DSM, the disassembly property in maintenance, recycling and reuse of configurable product are optimized.

Graph Transformers研究进展综述

随着图结构数据在各种实际场景中的广泛应用,对其进行有效建模和处理的需求日益增加。Graph Transformers(GTs)作为一类使用Transformers处理图数据的模型,能够有效缓解传统图神经网络(GNN)中存在的过平滑和过挤压等问题,因此可以学习到更好的特征表示。根据对近年来GTs相关文献的研究,将现有的模型架构分为两类:第一类通过绝对编码和相对编码向Transformers中加入图的位置和结构信息,以增强Transformers对图结构数据的理解和处理能力;第二类根据不同的方式(串行、交替、并行)将GNN与Transformers进行结合,以充分利用两者的优势。介绍了GTs在信息安全、药物发现和知识图谱等领域的应用,对比总结了不同用途的模型及其优缺点。最后,从可扩展性、复杂图、更好的结合方式等方面分析了GTs未来研究面临的挑战。

Neighborhood Modularization‑based Artificial Bee Colony Algorithm for Disassembly Planning with Operation Attributes

The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource conservation.Disassembly is an essential process of remanufacturing end-of-life products.Effective disassembly plans help improve disassembly efficiency and reduce disassembly costs.This paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are made.Besides,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation attributes.Then,a neighborhood modularization-based artificial bee colony algorithm is developed,which contains a modular optimized design.Finally,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.

Disassembly Sequence Planning:A Survey

It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired economic benefits.Therefore,performing their efficient disassembly is highly important in green manufacturing and sustainable economic development.Their typical examples are electronic appliances and electromechanical/mechanical products.This paper presents a survey on the state of the art of disassembly sequence planning.It can help new researchers or decision makers to search for the right solution for optimal disassembly planning.It reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded products.This paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty handling.This survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.

STUDY ON HUMAN-COMPUTER SYSTEM FOR STABLE VIRTUAL DISASSEMBLY

The cooperative work between human being and computer based on virtual reality (VR) is investigated to plan the disassembly sequences more efficiently. A three-layer model of human-computer cooperative virtual disassembly is built, and the corresponding human-computer system for stable virtual disassembly is developed. In this system, an immersive and interactive virtual disassembly environment has been created to provide planners with a more visual working scene. For cooperative disassembly, an intelligent module of stability analysis of disassembly operations is embedded into the human-computer system to assist planners to implement disassembly tasks better. The supporting matrix for stability analysis of disassembly operations is defined and the method of stability analysis is detailed. Based on the approach, the stability of any disassembly operation can be analyzed to instruct the manual virtual disassembly. At last, a disassembly case in the virtual environment is given to prove the validity of above ideas.

End-of-life vehicle recycling based on disassembly

The end-of-life vehicle recycling was studied based on the disassembly. The end-of-life recycling and the disassembly were reviewed and discussed. A disassembly experiment of an end-of-life engine was carried out, which strictly recorded the process of dismantling. Based on the results, a model of the end-of-life recycling was presented. In this model, the end-of-life parts were classified by three ways which included to recycle directly, to recycle after remanufacturing and to discard. By using this model, the dismantling efficiency and the recycling rate can be improved. Also, it obtains a good result after used in a dismantling factory.

基于Graph Transformer的半监督异配图表示学习模型

现有的图卷积网络(GCN)模型基于同配性假设,无法直接应用于异配图的表示学习,且许多异配图表示学习的研究工作受消息传递机制的限制,导致节点特征混淆和特征过度挤压而出现过平滑问题。针对这些问题,提出一种基于Graph Transformer的半监督异配图表示学习模型HPGT(HeteroPhilic Graph Transformer)。首先,使用度连接概率矩阵采样节点的路径邻域,再通过自注意力机制自适应地聚合路径上的节点异配连接模式,编码得到节点的结构信息,用节点的原始属性信息和结构信息构建Transformer层的自注意力模块;其次,将每个节点自身的隐层表示与它的邻域节点的隐层表示分离更新以避免节点通过自注意力模块聚合过量的自身信息,再把每个节点表示与它的邻域表示连接,得到单个Transformer层的输出,另外,将所有的Transformer层的输出跳连到最终的节点隐层表示以防止中间层信息丢失;最后,使用线性层和Softmax层将节点的隐层表示映射到节点的预测标签。实验结果表明,与无结构编码(SE)的模型相比,基于度连接概率的SE能为Transformer层的自注意力模块提供有效的偏差信息,HPGT平均准确率提升0.99%~11.98%;与对比模型相比,在异配数据集(Texas、Cornell、Wisconsin和Actor)上,模型节点分类准确率提升0.21%~1.69%,在同配数据集(Cora、CiteSeer和PubMed)上,节点分类准确率分别达到了0.8379、0.7467和0.8862。以上结果验证了HPGT具有较强的异配图表示学习能力,尤其适用于强异配图节点分类任务。

Crystal Structure of Sar1[H79G]-GDP Which Provides Insight into the Coat-controlled GTP Hydrolysis in the Disassembly of COP Ⅱ

Sarl is a small GTPase involved in COPⅡ vesicle transport. Previous studies showed that H79G mutation of Sarl can lock Sarl in its GTP-bound active conformation, stabilize coat assembly, and prevent the disassembly of COP Ⅱ vesicle coats by reducing Sec23/24 GAP- stimulated hydrolysis. We show here that the replacement of His79 by glycine induces a large conformation change in switch Ⅱ and results in the lost of hydrogen bond between His79 and its associated nucleophilic water molecule that was hypothesized to reduce the GAP-stimulated hydrolysis during the COP Ⅱ assembly and disassembly. These results confirm that the switch Ⅱ conformation is important for COP Ⅱ disassembly through coat-controlled GTP hydrolysis.

Analysis of Mobile Phone Reliability Based on Active Disassembly Using Smart Materials

When using shape memory materials into active disassembly of actual electronic products, because the elastic modulus of shape memory materials is affected by the temperature is relatively large, therefore, the main difference of environmental reliability between active disassembly products and common products is the impact of collision and vibration under different temperature. Establishing three-dimensional analysis model, comparing the impact of collision and vibration of mobile phone shells which are made up of PVC materials after casting & radiation and PC/ABS materials under different temperature. Analyzing the reliability of mobile phone under different temperature and optimizing its structure according to data of testing.

Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storing,and retrieving essential information from the manufacturing stage.Data collected at sites are shared with others where execution automatedly occurs.The obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing process.However,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major concern.The current research validates the information optimally to offer a minimum set of activities to complete the disassembly process.An optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in manufacturing.However,finding an optimal DSP is complex because of its combinatorial nature.The genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP problem.The converging nature at local optima is a limitation in the traditional GA.This study improvised the GA workability by integrating with the proposed priori crossover operator.An optimality function is defined to reduce disassembly effort by considering directional changes as parameters.The enhanced GA method is tested on a real-time product to evaluate the performance.The obtained results reveal that diversity control depends on the operators employed in the disassembly attributes.The proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the product.The effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

Experimental Study on the Reduction Effect of Pit Texture on Disassembly Damage for Interference Fit

After remanufacturing disassembly,several kinds of friction damages can be found on the mating surface of interference fit.These damages should be repaired and the cost is closely related to the severity of damages.Inspired by the excellent performance of surface texture in wear reduction,5 shapes of pit array textures are added to the specimens’surface to study their reduction effect of disassembly damage for interference fit.The results of disassembly experiments show that the order of influence of texture parameters on disassembly damage is as follows:equivalent circle diameter of single texture,texture shape and texture surface density.The influence of equivalent circle diameter of single texture and texture shape are obviously more significant than that of texture surface density.The circular texture with a surface density of 30%and a diameter of 100μm shows an excellent disassembly damage reduction effect because of its perfect ability of abrasive particle collection.And the probability of disassembly damage formation and evolution is also relatively small on this kind of textured surface.Besides,the load-carrying capacity of interference fit with the excellent texture is confirmed by load-carrying capacity experiments.The results show that the load-carrying capacity of the excellent texture surface is increased about 40%compared with that of without texture.This research provides a potential approach to reduce disassembly damage for interference fit.

Disassembly Evaluation in Design of a System Using a Multi-Parameters Index

In order to help designers, consider disassembly in their design activities, a method for evaluation of product disassembly is proposed. Criteria characterizing the disassembility of a product are identified. Each criterion is assigned a coefficient, thus proposing an index of easy fixations (Iff) as a design indicator to evaluate the level of disassembly of a solution generated by the designer. This index is calculated as a weighted average of the indicators for evaluating the disassembility of the product. The proposed method uses information such as the list of subsets or parts, the component tree, the part geometry, the functional links between components and parts, the properties of the components. It has been tested on one product: the soy roaster.

Assembly and disassembly of mammalian chromosome pellicle

By means of indirect double immunofluorescent staining, the coordination of PI antigen and perichromonucleolin (PCN), the constituent of nuclear periphery and nucleolus respectively, in the assembly and disassembly of chromosome pellicle during mitosis was studied. It was found that in 3T3 cells, during mitosis PI antigen began to coat the condensing chromosome .surface earlier.than PCN did. However, both of them completed their coating on chromosome at approximately the same stage of mitosis, prometaphase metaphase. The dissociation of PI antigen from chromosome pellicle to participate the formation of nuclear periphery took, place also ahead of that of PCN. At early telophase PI antigen had been extensively involved in the formation of nuclear periphery, while PCN remained in association with the surface of decondensing chromosomes. At late telophase, when PI antigen was localized in an fairly well formed nuclear periphery, PCN was in a stage of forming prenucleolar bodies.

p38 MAP kinase is necessary for melanoma-mediated regulation of VE-cadherin disassembly

Introduction Vascular endothelial (VE)-cadherin is localized to the endothelial borders and the adherens junctions,which are regulated by changes in mitogen activated protein kinases (MAPK),GTPases,and intracellular calcium. We previously

Research on Anti-collision Algorithm of Short Distance Data communication based on Binary-Tree Disassembly

This paper puts forward adaptive anti collision algorithm based on two fork tree decomposition. New search algorithm built on the basis of binary-tree algorithm, using the uniqueness of the label EPC, to estimate the distribution of label by slot allocation, the huge and complicated two fork tree is decomposed into several simple binary-tree by search the collision slots for binary-tree, so, it can simplifies the search process. The algorithm fully considers4 important performance parameters of the reader paging times, transmission delay, energy consumption and throughput label, the simulation results show that, the improved anti-collision algorithm is obviously improved performance than other two fork tree algorithm, it is more suitable for RFID anti-collision protocols.