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.

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.

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.

Ant colony optimization for assembly sequence planning based on parameters optimization

As an important part of product design and manufacturing, assembly sequence planning (ASP) has a considerable impact on product quality and manufacturing costs. ASP is a typical NP-complete problem that requires effective methods to find the optimal or near-optimal assembly sequence. First, multiple assembly constraints and rules are incorporated into an assembly model. The assembly constraints and rules guarantee to obtain a reasonable assembly sequence. Second, an algorithm called SOS-ACO that combines symbiotic organisms search (SOS) and ant colony optimization (ACO) is proposed to calculate the optimal or near-optimal assembly sequence. Several of the ACO parameter values are given, and the remaining ones are adaptively optimized by SOS. Thus, the complexity of ACO parameter assignment is greatly reduced. Compared with the ACO algorithm, the hybrid SOS-ACO algorithm finds optimal or near-optimal assembly sequences in fewer iterations. SOS-ACO is also robust in identifying the best assembly sequence in nearly every experiment. Lastly, the performance of SOS-ACO when the given ACO parameters are changed is analyzed through experiments. Experimental results reveal that SOS-ACO has good adaptive capability to various values of given parameters and can achieve competitive solutions.

Assembly Sequence Planning for Mechanical Products

A method for assembly sequence planning is proposed in this paper. First, two methods for assembly sequence planning are compared, which are indirect method and direct method. Then, the limits of the previous assembly planning system are pointed out. On the basis of indirect method, an improved method for assembly sequence planning is put forward. This method is composed of four parts, which are assembly modeling for products, assembly sequence representing, assembly sequence planning, and evaluation and optimization. The assembly model is established by human machine interaction, and the assembly model contains components' information and the assembly relation among the components. The assembly sequence planning is based on the breaking up of the assembly model. And/or graph is used to represent assembly sequence set. Every component which satisfies the disassembly condition is recorded as a node of an and/or graph. After the disassembly sequence and/or graph is generated, heuristic algorithm AO * algorithm is used to search the disassembly sequence and/or graph, and the optimum assembly sequence planning is realized. This method is proved to be effective in a prototype system which is a sub project of a state 863/CIMS research project of China ‘Concurrent Engineering’.

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.

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.

Using Genome-Referenced Expressed Sequence Tag Assembly to Analyze the Origin and Expression Patterns of Gossypium hirsutum Transcripts

We assembled a total of 297,239 Gossypium hirsutum （Gh, a tetraploid cotton, AADD） expressed sequence tag （EST） sequences that were available in the National Center for Biotechnology Information database, with reference to the recently published G. raimondii （Gr, a diploid cotton, DD） genome, and obtained 49,125 UniGenes. The average lengths of the U niGenes were increased from 804 and 791 bp in two previous EST assemblies to 1,019 bp in the current analysis. The number of putative cotton UniGenes with lengths of 3 kb or more increased from 25 or 34 to 1,223. As a result, thousands of originally independent G. hirsutum ESTs were aligned to produce large contigs encoding transcripts with very long open reading frames, indicating that the G. raimondii genome sequence provided remarkable advantages to assemble the tetraploid cotton transcriptome. Significant different distribution patterns within several GO terms, including transcription factor activity, were observed between D- and A-derived assemblies. Tran- scriptome analysis showed that, in a tetraploid cotton cell, 29,547 UniGenes were possibly derived from the D subgenome while another 19,578 may come from the A subgenome. Finally, some of the in silico data were confirmed by reverse transcription polymerase chain reaction experiments to show the changes in transcript levels for several gene families known to play key role in cotton fiber development. We believe that our work provides a useful platform for functional and evolutionary genomic studies in cotton.

De Novo Assembly Methods for Next Generation Sequencing Data

The recent breakthroughs in next-generation sequencing technologies, such as those of Roche 454,Illumina/Solexa, and ABI SOLID, have dramatically reduced the cost of producing short reads of the genome of new species. The huge volume of reads, along with short read length, high coverage, and sequencing errors, poses a great challenge to de novo genome assembly. However, the paired-end information provides a new solution to these problems. In this paper, we review and compare some current assembly tools, including Newbler, CAP3, Velvet,SOAPdenovo, AllPaths, Abyss, IDBA, PE-Assembly, and Telescoper. In general, we compare the seed extension and graph-based methods that use the overlap/lapout/consensus approach and the de Bruijn graph approach for assembly. At the end of the paper, we summarize these methods and discuss the future directions of genome assembly.

Sequencing and comparative analyses of Aegilops tauschii chromosome arm 3DS reveal rapid evolution of Triticeae genomes

Bread wheat （Triticum aestivum, AABBDD） is an allohexaploid species derived from two rounds of interspecific hybridizations. A high-quality genome sequence assembly of diploid Aegilops tauschii, the donor of the wheat D genome, will provide a useful platform to study polyploid wheat evolution. A combined approach of BAC pooling and next-generation sequencing technology was employed to sequence the minimum tiling path （MTP） of 3176 BAC clones from the short arm ofAe. tauschii chromosome 3 （At3DS）. The final assembly of 135 super-scaffolds with an N50 of 4.2 Mb was used to build a 247-Mb pseudomolecule with a total of 2222 predicted protein-coding genes. Compared with the orthologous regions of rice, Brachypodium, and sorghum, At3DS contains 38.67% more genes. In comparison to At3DS, the short arm sequence of wheat chromosome 3B （Ta3BS） is 95-Mb large in size, which is primarily due to the expansion of the non-centromeric region, suggesting that transposable element （TE） bursts in Ta3B likely occurred there. Also, the size increase is accompanied by a proportional increase in gene number in Ta3BS. We found that in the sequence of short arm of wheat chromosome 3D （Ta3DS）, there was only less than 0.27% gene loss compared to At3DS. Our study reveals divergent evolution of grass genomes and provides new insights into sequence changes in the polyploid wheat genome.

New Generations: Sequencing Machines and Their Computational Challenges

New generation sequencing systems are changing how molecular biology is practiced. The widely promoted $1000 genome will be a reality with attendant changes for healthcare, including personalized medicine. More broadly the genomes of many new organisms with large samplings from populations will be commonplace. What is less appreciated is the explosive demands on computation, both for CPU cycles and storage as well as the need for new computational methods. In this article we will survey some of these developments and demands.