INTEGRATED APPROACH TO GENERATION OF PRECEDENCE RELATIONS AND PRECEDENCE GRAPHS FOR ASSEMBLY SEQUENCE PLANNING

An integrated approach to generation of precedence relations and precedencegraphs for assembly sequence planning is presented, which contains more assembly flexibility. Theapproach involves two stages. Based on the assembly model, the components in the assembly can bedivided into partially constrained components and completely con-strained components in the firststage, and then geometric precedence relation for every component is generated automatically.According to the result of the first stage, the second stage determines and constructs allprecedence graphs. The algorithms of these two stages proposed are verified by two assemblyexamples.

AutoSeqMan:batch assembly of contigs for Sanger sequences

With the wide application of DNA sequencing technology, DNA sequences are still increasingly generated through the Sanger sequencing platform. SeqMan （in the LaserGene package） is an excellent program with an easy-to-use graphical user interface （GUI） employed to assemble Sanger sequences into contigs. However, with increasing data size, larger sample sets and more sequenced loci make contig assemble complicated due to the considerable number of manual operations required to run SeqMan. Here, we present the ＇autoSeqMan＇ software program, which can automatedly assemble contigs using SeqMan scripting language. There are two main modules available, namely, ＇Classification＇ and ＇Assembly＇. Classification first undertakes preprocessing work, whereas Assembly generates a SeqMan script to consecutively assemble contigs for the classified files. Through comparison with manual operation, we showed that autoSeqMan saved substantial time in the preprocessing and assembly of Sanger sequences. We hope this tool will be useful for those with large sample sets to analyze, but with little programming experience. It is freely available at https：//github.com/ Sun-Yanbo/autoSeqMan.

Optimization of Wind Turbine Hub Assembly Sequence Based on Intelligent Algorithm

A method for hub assembly sequence planning oriented to the fixed position layout is proposed.An assembly relationship model was constructed to describe the relationship between hub assembly components and workstations,considering the layout of the hub assembly line and process constraints,including the assembly precedence matrix,workstation assembly capability table and criticality table of components.The evaluation mechanism for the assembly sequence was established.Values from the evaluation functions with engineering significance were used to select the optimal assembly sequence from the perspective of assembly time,assembly index and assembly path distance.In function,the criticality of components was introduced into the traditional assemblability index,comparing the multi-objective dragonfly algorithm(MODA)with non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)to complete the assembly sequence planning and assignment for workstations.The optimized results show that the presented method is feasible and efficient for solving the hub assembly sequence planning problem.

Immune and Genetic Algorithm Based Assembly Sequence Planning

In this paper an assembly sequence planning model inspired by natural immune and genetic algorithm (ASPIG) based on the part degrees of freedom matrix (PDFM) is proposed, and a proto system — DSFAS based on the ASPIG is introduced to solve assembly sequence problem. The concept and generation of PDFM and DSFAS are also discussed. DSFAS can prevent premature convergence, and promote population diversity, and can accelerate the learning and convergence speed in behavior evolution problem.

INTEGRATED APPROACH TO ASSEMBLY SEQUENCE PLANNING OF C0MPLEX PRODUCTS

Assembly sequence planning will be more difficult due to the increasingcomplexity of products. An integrated approach to assembly sequence planning of complex productsapplying de-composition-planning-combination strategy is presented. First, an assembly is decomposedinto a hierarchical structure using an assembly structure representation based on connectors. Then,an assembly planning system is used to generate the sequences that are locally optimal for eachleaf partition hi the structure hierarchy. By combining the local sequences systematically in abottom-up manner and choosing suitable ones from the merged sequences, the assembly sequence of eachparent structure including the whole assembly is generated. An integrated system has beencompleted. A complex product is given to illustrate the feasibility and the practicality of theapproach.

Strategy of Concurrent Optimization for an Assembly Sequence

An effective constraint release based approach to realize concurrent optimization for an assembly sequence is proposed. To quantify the measurement of assembly efficiency, a mathematical model of concurrency evaluation index was put forward at first, and then a technology to quantify assembly constraints was developed by application of some fuzzy logic algorithms. In the process of concurrent optimization of the assembly sequence, two kinds of constraints were involved. One was self-constraints of components, which was used to evaluate the assemble capability of components under the condition of full-freedom. Another was an assembly constraint between components represented by geometric constraints between points, lines and planes under physical restriction conditions. The concept of connection strength degree （CSD） was introduced as one efficient indicator and the value of it was evaluated by the intersection of the two constraints mentioned above. The equivalent constraints describing the connection weights between components were realized by a well designed constraints reduction, and then the connection weights based complete assembly liaison graph was applied to release virtual connections between components. Under a given threshold value, a decomposition and reconstituting strategy for the graph with the focus on high assembly concurrency was used to realize an optimized assembly concurrency evaluation index. Finally, the availability of the approach was illustrated in an example to optimize the assembly of a shift pump.

An Approach to Assembly Sequence Plannning Based on Hierarchical Strategy and Genetic Algorithm

Using group and subassembly cluster methods, the hierarchical structure of a product is ?generated automatically, which largely reduces the complexity of planning. Based on genetic algorithm, the optimal of assembly sequence of each structure level can be obtained by sequence-by-sequence search. As a result, a better assembly sequence of the product can be generated by combining the assembly sequences of all hierarchical structures, which provides more parallelism and flexibility for assembly operations. An industrial example is solved by this new approach.

Chromosomal level assembly and population sequencing of the Chinese tree shrew genome

Chinese tree shrews (Tupaia belangeri chinensis) have become an increasingly important experimental animal in biomedical research due to their close relationship to primates. An accurately sequenced and assembled genome is essential for understanding the genetic features and biology of this animal. In this study, we used long-read single-molecule sequencing and high-throughput chromosome conformation capture (Hi-C) technology to obtain a high-qualitychromosome-scale scaffolding of the Chinese tree shrew genome. The new reference genome (KIZ version 2: TS_2.0) resolved problems in presently available tree shrew genomes and enabled accurate identification of large and complex repeat regions, gene structures, and species-specific genomic structural variants. In addition, by sequencing the genomes of six Chinese tree shrew individuals, we produced a comprehensive map of 12.8 M single nucleotide polymorphisms and confirmed that the major histocompatibility complex (MHC) loci and immunoglobulin gene family exhibited high nucleotide diversity in the tree shrew genome. We updated the tree shrew genome database (TreeshrewDB v2.0: http://www.treeshrewdb.org) to include the genome annotation information and genetic variations. The new high-quality reference genome of the Chinese tree shrew and the updated TreeshrewDB will facilitate the use of this animal in many different fields of research.

Sequencing of Mixed Model Assembly Lines Based on Improved Shuffled Frog Leaping Algorithm

Shuffled frog leaping algorithm( SFLA) was used to solve multi-objective sequencing problem of mixed model assembly line( MMAL). Local convergence can be avoided and optimal solution can be obtained to a certain extent. However,the multi-objective sequencing problem of MMAL is an non-deterministic polynomial hard( NP-hard) problem and the shortcomings are slow convergence rate and low precision. To solve the shortcomings for optimization objectives of minimizing total utility time and keeping average consumption rate of parts, a chaos differential evolution SFLA( CDESFLA) is proposed in this study. Because SFLA is easy to fall into local optimum,the evolution operator of differential evolution algorithms is introduced in SFLA as a local search strategy,and differential mutation operator is introduced in chaotic sequence to prevent premature convergence. The examples show that the proposed CDESFLA is better for convergence accuracy than SFLA,genetic algorithm( GA) and particle swarm optimization( PSO)

Heuristics for Mixed Model Assembly Line Balancing Problem with Sequencing

The growing global competition compels organizations to use many productivity improvement techniques. In this direction, assembly line balancing helps an organization to design its assembly line such that its balancing efficiency is maximized. If the organization assembles more than one model in the same line, then the objective is to maximize the average balancing efficiency of the models of the mixed model assembly line balancing problem. Maximization of average balancing efficiency of the models along with minimization of makespan of sequencing models forms a multi-objective function. This is a realistic objective function which combines the balancing efficiency and makespan. This assembly line balancing problem with multi-objective comes under combinatorial category. Hence, development of meta-heuristic is inevitable. In this paper, an attempt has been made to develop three genetic algorithms for the mixed model assembly line balancing problem such that the average balancing efficiency of the model is maximized and the makespan of sequencing the models is minimized. Finally, these three algorithms and another algorithm in literature modified to solve the mixed-model assembly line balancing problem are compared in terms of the stated multi-objective function using a randomly generated set of problems through a complete factorial experiment.

Research of the Assembly Model Based on Petri Net

Assembly model plans an important role in assembly sequence planning.Flexible assembly system (FAS) is a dis- crete event system (DES),so Petri net,as an important analytical tool for the DES,is used for modeling of an FAS.All of the feasible assembly sequences can be obtained by firing the Petri net model.In order to enhancing the efficiency of the assembly sequence planning,knowledge-based Petri net,combining an usual Petri net with expert’s knowledge and experiences,is proposed to con- struct the assembly model.So the feasible assembly sequences can be reduced greatly,and the optimum assembly sequence could be generated without the combinatorial explosion of solutions.

Genome assembly of the maize inbred line A188 provides a new reference genome for functional genomics

The current assembled maize genomes cannot represent the broad genetic diversity of maize germplasms.Acquiring more genome sequences is critical for constructing a pan-genome and elucidating the linkage between genotype and phenotype in maize.Here we describe the genome sequence and annotation of A188,a maize inbred line with high phenotypic variation relative to other lines,acquired by single-molecule sequencing and optical genome mapping.We assembled a 2210-Mb genome with a scaffold N50 size of 11.61 million bases(Mb),compared to 9.73 Mb for B73 and 10.2 Mb for Mo17.Based on the B73_Ref Gen_V4 genome,295 scaffolds(2084.35 Mb,94.30%of the final genome assembly)were anchored and oriented on ten chromosomes.Comparative analysis revealed that~30%of the predicted A188 genes showed large structural divergence from B73,Mo17,and W22 genomes,which causes high protein divergence and may lead to phenotypic variation among the four inbred lines.As a line with high embryonic callus(EC)induction capacity,A188 provides a convenient tool for elucidating the molecular mechanism underlying the formation of EC in maize.Combining our new A188 genome with previously reported QTL and RNA sequencing data revealed eight genes with large structural variation and two differentially expressed genes playing potential roles in maize EC induction.

De novo Assembly of Pen Shell(Atrina pectinata) Transcriptome and Screening of Its Genic Microsatellites

The pen shell(Atrina pectinata) is a large wedge-shaped bivalve, which belongs to family Pinnidae. Due to its large and nutritious adductor muscle, it is the popular seafood with high commercial value in Asia-Pacific countries. However, limiting genomic and transcriptomic data have hampered its genetic investigations. In this study, the transcriptome of A. pectinata was deeply sequenced using Illumina pair-end sequencing technology. After assembling, a total of 127263 unigenes were obtained. Functional annotation indicated that the highest percentage of unigenes(18.60%) was annotated on GO database, followed by 18.44% on PFAM database and 17.04% on NR database. There were 270 biological pathways matched with those in KEGG database. Furthermore, a total of 23452 potential simple sequence repeats(SSRs) were identified, of them the most abundant type was mono-nucleotide repeats(12902, 55.01%), which was followed by di-nucleotide(8132, 34.68%), tri-nucleotide(2010, 8.57%), tetra-nucleotide(401, 1.71%), and penta-nucleotide(7, 0.03%) repeats. Sixty SSRs were selected for validating and developing genic SSR markers, of them 23 showed polymorphism in a cultured population with the average observed and expected heterozygosities of 0.412 and 0.579, respectively. In this study, we established the first comprehensive transcript dataset of A. pectinata genes. Our results demonstrated that RNA-Seq is a fast and cost-effective method for genic SSR development in non-model species.

FAST GENERATION OF OPTIMAL ASSEMBLY PLANS

Existing approaches to automatic assembly planning often lead to combinatorial explo- sion. When the parts composing the assembly increase in number, computer-aided planning be- comes much slower than manual planning. Efforts to reduce the computing time by taking into ac- count various constraints and criteria to guide the search for the optimal plan requires too much input information, so as to offset the convenience of automatic assembly planning. In addition, as the planner becomes more complicated, such efforts often fail to reach the objective. This paper presents a new concep── unit , asserting that the intemal structure of an assembly is hierachical. Every disassembly operation only handles several units, no matter how many parts are involved. Furthermore, the scenario of disassembly is brought to light. It relates to only two key data──the liaison type and the assembly direction. The computational cast of this approach is roughly propor. tional to the number of parts. A planner, implementing these principlcs can generate the optimal as- sembly plans dramatically faster than the known approaches.

Application of Assembly Modeling and Simulation Technology to a Large Size Wind-drive Generator

Challenges still remain in carrying out assembly modeling efficiently in virtual assembly （VA） fields. One of the root causes is the apparent weakness in effective description of assembly knowledge and information. The assembly modeling, disassembly modeling, assembly interference inspection, assembly sequence planning and optimization, and assembly simulation display for key techniques is studied theoretically in this paper. An example of product assembly modeling is provided to illustrate the effectiveness of the proposed approach. On the basis of re- search, using assembly simulation techniques and multimedia techniques to finish structure design in linkage design of a large size wind-drive generator. The application of the modeling method has shortened the lead time dramatically.

Multi-User Collaborative Assembly Planning over the Internet

Due to the increasing complexity of products and for the distributed product development, more closely collaborative work among designers is required. A collaborative assembly planning approach is proposed to support assembly planning in a networked environment. The working procedure is depicted and the key techniques including collaborative-planning-oriented assembly decomposition modeling, assembly assignment modeling, and sub-plans merging are addressed. By incorporating visual models at client side with assembly application models at server side, a web-based supporting environment for collaborative assembly planning has been developed using VRML and Java-EAI techniques. A case study is given to illustrate the feasibility and validity of the idea.

Solving Level Scheduling in Mixed Model Assembly Line by Simulated Annealing Method

This paper presents an application of the simulated annealing algorithm to solve level schedules in mixed model assembly line. Solving production sequences with both number of setups and material usage rates to the minimum rate will optimize the level schedule. Miltenburg algorithm (1989) is first used to get seed sequence to optimize further. For this the utility time of the line and setup time requirement on each station is considered. This seed sequence is optimized by simulated annealing. This investigation helps to understand the importance of utility in the assembly line. Up to 15 product sequences are taken and constructed by using randomizing method and find the objective function value for this. For a sequence optimization, a meta-heuristic seems much more promising to guide the search into feasible regions of the solution space. Simulated annealing is a stochastic local search meta-heuristic, which bases the acceptance of a modified neighboring solution on a probabilistic scheme inspired by thermal processes for obtaining low-energy states in heat baths. Experimental results show that the simulated annealing approach is favorable and competitive compared to Miltenburg’s constructive algorithm for the problems set considered. It is proposed to found 16,985 solutions, the time taken for computation is 23.47 to 130.35, and the simulated annealing improves 49.33% than Miltenberg.

改进布谷鸟算法在装配序列规划中的应用研究

针对装配序列规划问题,建立考虑装配序列的几何可行性、稳定性、聚合性、重定向性的装配关系模型以及基于适应度函数的装配序列优化数学模型。提出一种改进布谷鸟算法对装配序列规划问题进行求解,采用随机键和最小位置规则的方法设计基于零件编号、装配方向、装配工具的3层编码方案;设计基于最小装配成本的初始化策略与随机初始化策略相结合的混合种群初始化策略,提高种群质量;改进种群进化和搜索方式,将种群分为3个子群,并分别采用自适应步长飞行、标准步长飞行和交叉、变异的方式进行种群更新,提高算法的收敛速度和求解精度。最后通过实例应用及与其他算法的比较,验证了所提出的改进布谷鸟算法在求解装配序列规划问题上的有效性和优越性。

飞机壁板装配偏差传递与演变及其优化方法

壁板的装配准确度直接影响飞机的气动力特性,在装配过程中受到夹紧力、铆接力、回弹力、装配顺序等影响,壁板将发生不同程度的变形,装配变形与零件偏差、夹具偏差等相互耦合,导致壁板最终的装配准确度难以预测和控制。针对以上问题,本文对壁板装配过程中偏差的传递与演变规律进行研究,构建了壁板装配偏差传递与演变的刚柔混合模型与壁板装配准确度的评价准则;采用确定性分析法计算壁板的刚性定位偏差,并通过建立多步夹紧和不同长桁装配顺序下的偏差状态空间模型,揭示了壁板装配过程中偏差的演变规律,实现了壁板装配偏差的准确预测;提出了基于代理模型和智能优化算法的长桁装配顺序稳健优化设计方法,通过装配顺序优化使壁板的装配质量得到了整体提升。

一种基于计算智能的飞机部件装配序列优化方法

针对目前装配资源受限条件下大型部件装配规划存在效率低、性能差的问题,提出一种基于离散烟花算法的装配序列规划模型。建立了装配部件、装配资源和混合干涉矩阵,以描述不同情况下的装配干涉问题。为了加快可行解的求解速度,设计了包括爆炸幅度、烟花爆炸产生的火花数量和火花位置更新的策略。实验阶段,以机翼的装配过程为例对所提模型进行验证。结果表明,与离散粒子群优化算法相比,使用所提出的离散烟花算法获得的解的适应度函数值更优,所提算法适应度值提升约24.5%。