Li Hong Qiao

Operation Sequencing Using Genetic Algorithm

Operation sequencing is one of the most important tasks in process planning. The sequencing procedures associate manufacturing features from 3D CAD models and machining methods together to satisfy certain manufacturing process constraints. In order to simplify process constraint aggregations, two types of constraint matrixes, feature constraint matrix and the operation constraint matrix, are proposed in this paper, which take into account of the compulsive constraints, such as geometric topology constraints, manufacturing process knowledge criteria, custom compulsive constraints and so forth. Accordingly, an iterative genetic algorithm is proposed, which is naturally used in the manufacturing feature level and operation level. In the manufacturing feature level, feasible feature sequences are generated based on the analysis of feature constraint matrix. In the operation level, the information that is contained in the machining operation such as machine tools, set-ups and cutting tools is considered to optimize the operation sequences based on the results acquired in the feature level. Compared with the traditional simple genetic algorithm, the iterative genetic algorithm is proved to be superior in shortening the operation sequencing time.

Product Information Modeling and Organization with MBD

Model-based definition (MBD) promises reduced time-to-market and improved product quality. Adopting MBD concept in product development process seems to be the next reasonable step. However, some existent critical issues related to data content and presentation need to be overcome. To offer proper solutions from the standpoint of design and manufacturing integration, MBD concept was firstly introduced in order to describe its characteristics and capabilities. Then the answers to the following questions were given: what data are necessary for design and manufacturing integration, how data should be semantically organized and presented based on solid model and CATIA PPR (Product Process & Resource) tree.

Machining Sequencing Optimization Based on Simulated Annealing Algorithm

Distributed geometric features such as adjacent auxiliary holes with certain tolerance requirements are common geometry to be machined in many complex structural components. The machining sequencing decision of such features has high impact on the machining efficiency of the part. This paper conducted an algorithm to generate optimal machining sequence of the distributed holes in a machined part by using simulated annealing. The procedures of the algorithm were introduced. Distributed holes machining of an example part has been considered in the paper to exam the algorithm to find an optimal machining sequence of the holes in the row blank operation. The impacts of algorithm parameters on the results such as the starting annealing temperature, temperature coefficient and iterations are studied. Comparisons of the machining route before and after optimization were performed. According to the optimized sequencing, total distance and transfer time of cutting tools were greatly shortened. Therefore, the machining sequencing optimization of distributed holes can raise the machining efficiency in practice and has great significance.

A Hybrid Approach for Part Geometry Optimization through Engineering Simulation

The scope of design optimization differs from one industry to another. In various situations, new part design is an instance of previously designed part i.e. it differs only in some dimension from the previous part. This can be due to change in functional parameters of the product, building part family or continual improvement in existing design etc. A hybrid approach for part geometry optimization of such parts is presented in this paper. It includes finding relationship between part geometric and functional parameters at assembly level. The designed part is simulated using finite element analysis (FEA) for validation and a set of feasible part geometry parameters along with their effect on objective function (functional parameters) are obtained through knowledge enabled design of experiments (DOE). The optimum solution is sought among them and validated through structural analysis of part / product. The process has been applied successfully in design optimization of electrode_holder in spot welding equipment for automotive industry.

Assembly Unit Partition Based on Theory of Cut-Set

In the manufacture process of many large-scaled and complex products assembly, due to large number of parts or components, assemblies are often divided into several small assembly units in order to organize production and increase assembly efficiency. To obtain fine-grained rapid assembly unit partition, this paper presents a method of assembly unit partition based on cut-set theory with consideration of the assembly constraints and assembly complexity. The paper also discusses the method of establishing the assembly relationship graph of a product as the basis of unit partition. The relationship graph is extracted from the CAD model of the product and is used to describe the relationship of its component assembly. Using the proposed unit partition method, assembly constraints such as precedence relationship can be considered so that invalid assembly unit partition will be avoided. Furthermore, by defining assembly complexity, optimal selection of assembly unit partition can be achieved. The procedures of assembly unit partition including establishing of assembly relationship from CAD model, approach to cut-set, optimal selection and validation are addressed with an assembly example and a flow chart.

Establishing Geometry and Functional Parameters Relationships through Regression Analysis and their Assistance to Product Customization

In a product structure composed of different parts, sub-assemblies and/or assemblies, different constituents have their particular role in overall product function. Modular product design enables designing instances of a product suitable for different applications with minor design changes in certain parts or systems and plays an important role in product customization. On the other hand, product geometry and functional parameters are related with each other and appropriate selection of the former can ensure fulfillment of the latter. In this research, a micro-level methodology for product customization by designing part instances in a modular design is presented. The approach emphasizes on achieving product functional parameters while controlling respective critical geometric parameters. In this regard, product geometric and functional parameters relationships are established using regression analysis of results from finite element analysis (FEA) simulations of product process model. The research is applied on a machine structure from industry and the results show success and effectiveness of the proposed methodology.

Parts Tolerance Allocation Based on Assembly Clearance Analysis and Product Functional Parameters

Geometric tolerances are assigned to avoid parts rejection in a manufacturing process while ensuring fulfillment of intended function. Selection of tolerance value is an important task which affects the overall product cost and performance both. The significance of tolerance value is more evident in case of mating parts where the dimension of more than one parts share responsibility of successful assembly and design. The objective of this research is to determine appropriate tolerance value based on assembly clearance analysis which takes into account relationship between assembly clearance and product performance parameters. The study is conducted through CAD-CAE integrated finite element analysis (FEA) simulations of the product process model. The results output help in distinguishing different tolerance levels which can be further probed for optimal, using available manufacturing resource capability data. The research output is a more practical tolerance value achieved based on product performance analysis as well as available resources and appropriate cost. The results obtained validate the utility of the approach presented in this paper.

Manufacturing Process Specification and Collaborative Decision-Making

A majority of information in manufacturing is the process information which presents mobility. Such information reflects transforming process form materials to products. This research establishes a manufacturing process information model that presents uniqueness, validness, completeness and generality based in PSL. The model can provide necessary process information and related product, material and resource information required by systems for integrating and collaborative decision making. It then enables to build a collaborative manufacturing decision making process model which is capable of utilizing the process information model. By defining logic procedure, data wrapping and service invoking in the decision making process model, multi-manufacturing systems collaborative decision making will be implemented. Such method of manufacturing process information modeling and decision making process modeling is illustrated by examples of the collaborative creation of a part process plan and an assembly process plan considering actual manufacturing environment.

An Approach to Region-Based Feature Recognition for Structural Parts

Feature-based numerical control programming can enhance the process planning efficiency for complex structural parts in aeronautic industry. Feature recognition is often being a useful tool to the domain. In order to handle the variety and uncertainty of the feature interpretation of feature recognition of structural parts, a region-based feature recognition approach is proposed. On the basis of the characteristics of the structural parts, the approach employs the fact that topology surfaces of structural parts have directions, and utilizes region as the foundation of feature recognition. By recognition and combination of regions, the approach acquires the features of a structural part. The approach is efficient in recognizing the features of structural parts which have apparent directional characteristic.

Multi-Objective Optimization Design of Complex Mechanical and Electrical Products Based on Improved Evolutionary Algorithm

The design of complex mechanical and electrical products has to achieve various objectives and satisfy various constraints. In many cases, there are trade-off relationships between these objectives, and thus it is difficult to optimize these objectives simultaneously. This invokes the need of the multiobjective optimization to achieve these objectives collectively. In this paper, multiple objectives for complex mechanical and electrical products are optimized, simultaneously using an improved multiobjective evolutionary algorithm: ISPEA2. The results showed that ISPEA2 could generate uniformly a pareto optimal set in the design space and has better robustness and convergence than SPEA2 and NSGA-II.