Mass Personalization for Complex Equipment Based on Operating Data-driven Inverse Design

doi:10.3901/JME.2021.08.065

Abstract

Abstract: Unlike consumer products with explicit personalization such as appearances, equipment products must finish scheduled tasks with energy efficiency in various complex usage scenarios and working conditions. Therefore, besides explicit personalized demands, equipment products contain implicit personalized demands hidden in diverse usage scenarios or working conditions, which challenges the personalization of equipment products. By analyzing the R&;D, operating characteristics, and big-data opportunities of equipment products, a mass personalization method based on data-driven inverse design (DID-MP) is proposed for complex equipment. Firstly, the data-driven inverse design is compared with the traditional forward design process, in order to introduce and highlight data-driven inverse design (DID) characteristics. Secondly, based on DID and traditional mass customization, two concepts, i.e., first-time customization and second-time customization, are proposed. The DID-MP framework for complex equipment is given together with the key techniques for objective selection, operating data acquisition, identification and modeling of system parameters based on usage scenarios, and optimal system parameter identification and feedforward application. Finally, a case study of optimizing and updating the loader transmission and control module is used to verify the proposed mass personalization method using DID. The comparison with the traditional methods shows that the proposed method is powerful to realize mass personalization of complex equipment.

Key words: operating data, complex equipment, inverse design, mass personalization, loaders

CLC Number:

TH166
U463

HOU Liang, LIN Haojing, WANG Shaojie, LIAN Xiaozhen, ZHANG Wei. Mass Personalization for Complex Equipment Based on Operating Data-driven Inverse Design[J]. Journal of Mechanical Engineering, 2021, 57(8): 65-80.

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