Modular product design evaluation method based on data driving

Abstract

The invention relates to a modular product design evaluation method based on data driving, and the method comprises the steps: building a modular product multi-stage evaluation system according to characteristics of a product and personalized demands of a customer; aiming at the established evaluation system, designing an acquisition method of corresponding data; for a designed multi-stage evaluation system, establishing a two-stage neural network wherein the two-stage neural network comprises an input layer, a first-stage hidden layer, a first-stage output layer, a second-stage input layer,a second-stage hidden layer and an output layer; continuously inputting the acquired data into a neural network for training, and adjusting parameters of the neural network; and realizing design evaluation of the product by utilizing the neural network. Dynamic mapping of modular product design parameters and customer evaluation results is achieved in a machine learning mode, designers quickly estimate market evaluation of new products by continuously collecting data and dynamically adjusting the evaluation results, and the product design period is shortened.

Description

technical field [0001] The invention relates to a modular product design evaluation method, in particular to a data-driven product designer-oriented product design evaluation method. Background technique [0002] With the gradual in-depth research and application of the new generation of IT technologies (such as cloud computing, Internet of Things, big data, deep learning, etc.), the era of data-driven manufacturing has come. New product development is considered to be one of the important links for enterprises to maintain continuous competitiveness in the fierce market competitors, and enterprises are forced to continuously develop new products to adapt to the ever-changing individual needs of customers. How to efficiently use big data in the process of product design, manufacturing, sales, use, and evaluation, continuously analyze the coupling impact of different design parameters on customer experience, and help designers quickly estimate market evaluation results in the ...

AI Technical Summary

Problems solved by technology

[0004] However, with the increasing complexity of the product evaluation system and the constant changes in the product evaluation indicators of enterprises, the original rule-based method is difficult to adapt to new needs.

However, after searching, it is found that there is no report on the data-driven, multi-stage product design evaluation method for modular products

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