ChatGPT-Like Large-Scale Foundation Models for Prognostics and Health
Management: A Survey and Roadmaps
- URL: http://arxiv.org/abs/2305.06472v2
- Date: Fri, 12 May 2023 10:41:35 GMT
- Title: ChatGPT-Like Large-Scale Foundation Models for Prognostics and Health
Management: A Survey and Roadmaps
- Authors: Yan-Fu Li, Huan Wang, Muxia Sun
- Abstract summary: Prognostics and health management (PHM) technology plays a critical role in industrial production and equipment maintenance.
Large-scale foundation models (LSF-Models) such as ChatGPT and DALLE-E marks the entry of AI into a new era of AI-2.0.
This paper systematically expounds on the key components and latest developments of LSF-Models.
- Score: 8.62142522782743
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Prognostics and health management (PHM) technology plays a critical role in
industrial production and equipment maintenance by identifying and predicting
possible equipment failures and damages, thereby allowing necessary maintenance
measures to be taken to enhance equipment service life and reliability while
reducing production costs and downtime. In recent years, PHM technology based
on artificial intelligence (AI) has made remarkable achievements in the context
of the industrial IoT and big data, and it is widely used in various
industries, such as railway, energy, and aviation, for condition monitoring,
fault prediction, and health management. The emergence of large-scale
foundation models (LSF-Models) such as ChatGPT and DALLE-E marks the entry of
AI into a new era of AI-2.0 from AI-1.0, where deep models have rapidly evolved
from a research paradigm of single-modal, single-task, and limited-data to a
multi-modal, multi-task, massive data, and super-large model paradigm. ChatGPT
represents a landmark achievement in this research paradigm, offering hope for
general artificial intelligence due to its highly intelligent natural language
understanding ability. However, the PHM field lacks a consensus on how to
respond to this significant change in the AI field, and a systematic review and
roadmap is required to elucidate future development directions. To fill this
gap, this paper systematically expounds on the key components and latest
developments of LSF-Models. Then, we systematically answered how to build the
LSF-Model applicable to PHM tasks and outlined the challenges and future
development roadmaps for this research paradigm.
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