Assembly time evaluating method based on artificial neural network and virtual assembly

Abstract

The invention discloses an assembly time evaluating method based on an artificial neural network and a virtual assembly. The method comprises the step of establishing a virtual working platform, planning a DELMIA assembly sequence and a DELMIA path and generating an assembly path, the step of generating the assembly sequence through a constraint matrix method and establishing the constraint relation among components, the step of preassembling the product components through a DELMIA assembly module, establishing a priority dismounting matrix, extracting the assembly sequence meeting the condition from the priority dismounting matrix and planning the assembly sequence through the strong data collecting capacity of the matrix, the step of establishing a virtual assembly work environment and the virtual assembly action process, the step of measuring the assembly path and calculating the assembly time, the step of establishing an assembly time evaluating model, the step of establishing the model and standardizing a sample, and the step of evaluating the sample. The assembly time evaluating method solves the problems that the product assembly period is long, cost is high, and the effect is poor.

Description

technical field [0001] The invention belongs to the field of computer application technology, in particular to an assembly time evaluation method based on artificial neural network and virtual assembly. Background technique [0002] With the development of computer-aided design and manufacturing technology, it has become a sharp tool that can change the low efficiency of the assembly industry in the process of product design and manufacturing. In the assembly manufacturing industry in the past, production and assembly could only be completed by assembly workers' accumulated assembly experience. Traditional optimization methods are only established at the stage of model imitation and stagnate. This kind of assembly process design optimization method is not only a problem of long experimental cycle, but also takes up too many production resources, and the uncertainty of the simulation process environment changes. Will reduce the convincing power of this model experiment metho...

AI Technical Summary

Problems solved by technology

[0011] The purpose of the embodiment of the present invention is to provide an assembly time evaluation method based on artificial neural network and virtual assembly, aiming at solving the problem that the traditional assembly process design needs to establish a large number of physical models to conduct mold assembly tests to determine the design, and the evaluation system cannot be online Optimization can only be analyzed from the results. The CAD system cannot yet achieve perfect integration with DFA, which makes the product assembly cycle long, high cost, and the effect is not good.

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