New Pattern of Operation & Maintenance Data and Multi-modal Knowledge Driven Improvement Design for Complex Products

doi:10.3901/JME.2025.03.091

Abstract

Abstract: Based on analysis of the challenges facing by complex products (CPs) manufacturing enterprises during innovative development, the limitations of existing product improvement design methods and the evolution directions of current product design paradigms, a new pattern and architecture of operation & maintenance (O&M) data and multi-modal knowledge (MMK) driven improvement design for CPs is proposed and designed. The operation logic of "configuration → monitoring → evaluation → correlation → feedback → improvement" for the proposed pattern is discussed. The related key technologies of the new pattern are put forward and elaborated, which included the O&M data proactive perceiving and lifecycle data value-adding calculation of CPs, the key functional modules performance degradation assessment and key design parameters identification of CPs, and the knowledge modeling and design scheme intelligent configuration for CPs improvement design, etc. By applying these technologies, the cross-stage and multi-business collaborative optimization of design and O&M stages can be facilitated effectively. As a result, the effectiveness of product improvement design schemes and the intelligence of scheme configuration processes are enhanced. The proposed new pattern and key technologies could provide important referential value to the research and application of exploring a new manufacturing service mode that leading the development of high-end equipment manufacturing industry.

Key words: operation and maintenance data, multi-modal knowledge, improving design, product lifecycle

CLC Number:

TH186
TH166

ZHAO Xin, REN Shan, ZHANG Geng, ZHANG Yingfeng. New Pattern of Operation & Maintenance Data and Multi-modal Knowledge Driven Improvement Design for Complex Products[J]. Journal of Mechanical Engineering, 2025, 61(3): 91-104.

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