A mechanical assembly is a composition of interrelated parts. Assembly data base stores the geometric models of indi-vidual parts, the spatial positions and orientations of the parts in the assembly, and the relationships between parts. An assembly of parts can be represented by its liaison which has a description of its relationships between the various parts in the assembly. The problem is to not only make the information available but also use the relevant information for making decisions, especially determination of the assembly sequence plan. The method described in this paper ex-tracts the feature based assembly information from CAD models of products and build up liaisons to facilitate assembly planning applications. The system works on the assumption that the designer explicitly defines joints and mating condi-tions. Further, a computer representation of mechanical assemblies in the form of liaisons is necessary in order to automate the generation of assembly plans. A novel method of extracting the assembly information and representing them in the form of liaisons is presented in this paper.

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A Novel Method of Using API to Generate Liaison Relationships from an Assembly

This paper proposes a modified discrete firefly algorithm (MDFA) to solve the problem of assembly sequence planning. Firstly, to improve the performance of the firefly algorithm (FA), we proposed a MDFA by endowing the fireflies with the capability of changeable visual range. The computing case shows the proposed algorithm is more effective and robust than standard FA, genetic algorithm and particle swarm optimization algorithm. Secondly, a method of how to set parameters for FA and MDFA is proposed. This method is practical in the application of FA to solve discrete problem. Thirdly, to make the sequences more closer to real industrial requirements, a so called process precedence relations (PPR) evaluation function is presented, which not only considering the interference between parts, assembly tools and clamps, but also regarding the assembly order between parts and their reference parts. Finally, the evolution performance of the MDFA is investigated, and the performance of the proposed approach to solve ASP is verified through two cases study.

The modified firefly algorithm considering fireflies’visual range and its application in assembly sequences planning

Microfluidic-based mixing methods have aroused increasing attention due to their tremendous potential in bio-related and materials science fields. Achieving mixing based on microscale devices, microfluidic-based mixing methods offer several advantages over their macroscale device-based counterparts, such as compact size, ease of operation, and the straightforward control of the mixing process. Generally, the ability to achieve high mixing performance in an efficient and simple manner is a key criterion for the reliability of a microfluidic-based method, which is essential to the reactor design. In the review paper, we summarize a number of microfluidic-based mixing methods capable of synthesizing nanoparticles. For comparative purposes, we divide these methods into active and passive methods, looking at their working principles as well as their respective advantages. On this basis, we present five commonly used active methods and three representative passive methods, with a detailed discussion on the practical applications of each method in improving the performance of fluid mixing. At the end of the review, we elaborate on some of current limitations and future prospects of these methods, which will help guide readers who are interested in making some innovations in this area of research. 

A review of microfluidic-based mixing methods

Lower fluidic resistance of double-layer droplet continuous flow PCR microfluidic chip for rapid detection of bacteria.

This work is mainly to combine fractal principle with multi-objective genetic algorithm, and the multi-objective optimization of the Cantor fractal baffle micromixer is carried out. At different Reynolds numbers (Res), the three-dimensional Navier-Stokes equation is employed to numerically analyze the fluid flow and mixing in the microchannel. We choose the ratio of the three parameters associated with the geometry of the micromixer as design variables, and take the mixing index and pressure drop at the outlet of the micromixer as two objective functions for optimization. For the parameter study of the design space, the Latin hypercube sampling (LHS) method is used as an experimental design technique, and it is used to select design points in the design space. We use the proxy modeling of the response surface analysis (RSA) to approximate the objective function. The genetic algorithm is used to get the Pareto optimal frontier of the micromixer. K-means clustering is used to classify the optimal solution set, and we select representative design variables from it. Through multi-objective optimization, when Re = 1 and 10, the optimized mixing efficiency of the micromixer increased by 20.59% and 14.07% compared with the reference design, respectively. And we also prove that this multi-objective optimization method is applicable to any Res. 

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New insights into the micromixer with Cantor fractal obstacles through genetic algorithm

Finding the optimal design of a Cantor fractal-based AC electric micromixer with film heating sheet by a three-objective optimization approach

Assembly sequence planning plays a major role in the manufacturing industry. There are still many challenges in the area of assembly planning. One of the significant reasons is the weakness in effective description of assembly knowledge and information. With the purpose of reducing computational complexity, this paper presents a method based on engineering knowledge approach to the assembly sequence planning. The DACG (Directed Assembly Connection Graph) proposed provides an appropriate way to express both geometric information and non-geometric knowledge. In order to increase the assembly planning efficiency, the DACG includes engineering knowledge and semantic in design, manufacturing and assembly fields. Product semantic information model could offer much useful information for designer to finish the assembly (process) design and make right decision in that process. A product assembly planning example is presented to illustrate the effectiveness of the proposed approach. Preliminary experience with the...

https://journals.sagepub.com/doi/pdf/10.1260/1748-3018.5.1.57

Xiaoyu Li

Papers

Finding the optimal design of a Cantor fractal-based AC electric micromixer with film heating sheet by a three-objective optimization approach

Knowledge-Based Approach to Assembly Sequence Planning

Optimized design of droplet micro-mixer with sinusoidal structure based on Pareto genetic algorithm

Numerical Simulation Study of Double-Emulsion Droplet Formation in a Co-flow Microchannel Capillary Device