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.

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.

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.

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.

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.

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’.